This study evaluated the competencies of graduating students at the Cebu Technological University-Carmen Campus in relation to eight employability attributes and assessed the alignment from the perspectives of students, teachers
across the five disciplines and HR professionals or student mentors from partner industries. The primary objective examined whether students’ self-assessments match teachers' evaluations and industry’s expectations in order to ensure that students can secure employment immediately after graduation. To achieve this, a descriptive-correlational research design was employed. A total of 275 respondents voluntarily participated in the study. Data were analyzed using Analysis of Variance (ANOVA) to determine significant differences in their assessments of employability attributes. Findings based on the ANOVA point out significant differences among the three respondent groups in four academic programs: Hospitality Management (systems thinking skills), Marine Engineering (all eight employability attributes), Industrial Technology (work ethics), and Education (leadership, management, information technology, and systems thinking skills). These differences in the data propose that existing school-industry partnerships may not be strong enough and that students still need to improve both skills and values through a reinforced alignment of employability attributes. To address these gaps, the study vouches for the
Implementation of an action plan for enhancing the alignment between graduating students' employability attributes and industry requirements. This plan motivates continued school-industry partnerships that comprise hands-on learning—not just towards the end of the course but throughout the whole program. This better prepares students for direct and significant employment after graduation.
TABLE OF CONTENTS
TITLE PAGE
APPROVAL SHEET
ABSTRACT
ACKNOWLEDGMENT
DEDICATION
TABLE OF CONTENTS
LIST OF TABLES
LIST OF FIGURES
Chapter 1 THE PROBLEM AND ITS SCOPE
Rationale of the Study
Theoretical Background
THE PROBLEM
Statement of the Problem
Null Hypothesis
Significance of the Study
Scope and Limitation
RESEARCH METHODOLOGY
Design
Flow of the Study
Environment
Respondents
Instrument
Data Gathering Procedures
Sampling Technique
Statistical Treatment of Data
Scoring Procedures
DEFINITION OF TERMS
Chapter 2 PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA
EMPLOYABILITY ATTRIBUTES OF STUDENTS
Basic Literacy and Numeracy Skills
Critical Thinking Skills
Leadership Skills
Management Skills
Interpersonal Skills
Information Technology Skills
Systems Thinking Skills
Work Ethics
SIGNIFICANT DIFFERENCES IN EMPLOYABILITY ATTRIBUTES
Basic Literacy and Numeracy Skills
Critical Thinking Skills
Leadership Skills
Management Skills
Interpersonal Skills
Information Technology Skills
Systems Thinking Skills
Work Ethics
Chapter 3 SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS
SUMMARY OF FINDINGS
CONCLUSIONS
RECOMMENDATIONS
Chapter 4 OUTPUT OF THE STUDY
AN ACTION PLAN FOR ENHANCING THE ALIGNMENT BETWEEN GRADUATING STUDENTS' EMPLOYABILITY ATTRIBUTES AND INDUSTRY REQUIREMENTS
Rationale
Objectives
Scheme and Implementation
BIBLIOGRAPHY
APPENDICES
Appendix A Transmittal Letter for the Campus Director
Appendix B Transmittal Letter for the Schools Division Superintendent of Cebu, Region VII
Appendix C Transmittal Letter for the Supervisors of the Public Schools District of Carmen
Appendix D Transmittal Letter for CTU-Carmen's Partnered Industries and Schools
Appendix E Transmittal Letter for the Teachers and Students of CTU-Carmen Campus
Appendix F Questionnaire for CTU-Carmen Campus Graduating Students
Appendix G Questionnaires for CTU-Carmen Campus Teachers
Appendix H Questionnaires for Partnered Industries of CTU-Carmen Campus
Appendix I Questionnaires for School Mentors of CTU-Carmen Campus
Appendix J Demographic Profile of the Respondents According to their Desired Career
Appendix K Demographic Profile of the Respondents According to Type of Industry and Educational Level
Appendix L Graphical Comparison of Perceptions of Employability Attributes Across Different Academic Programs
Appendix M Findings on Employability Attributes
Editorial note: Parts of the appendices are nor part of the publication due to copyright issues.
ABSTRACT
ALIGNMENT BETWEEN THE EMPLOYABILITY ATTRIBUTES OF GRADUATING STUDENTS AND INDUSTRY REQUIREMENTS
WILSON A. JERUSALEM
Cebu Technological University - Carmen Campus
This study evaluated the competencies of graduating students at the Cebu Technological University-Carmen Campus in relation to eight employability attributes, assessed the alignment from the perspectives of students, teachers across the five disciplines, and HR professionals or student mentors from partner industries. The primary objective examined whether students’ self-assessments match teacher’s evaluations and industry’s expectations in order to ensure that students can secure employment immediately after graduation. To achieve this, a descriptive-correlational research design was employed. A total of 275 respondents voluntarily participated in the study. Data were analyzed using Analysis of Variance (ANOVA) to determine significant differences in their assessments of employability attributes. Findings based on the ANOVA point out significant differences among the three respondent groups in four academic programs: Hospitality Management (Systems Thinking Skills), Marine Engineering (all eight employability attributes), Industrial Technology (Work Ethics), and Education (Leadership, Management, Information Technology, and Systems Thinking Skills). These differences in the data propose that existing school-industry partnerships may not be strong enough, and that students still need to improve both skills and values through a reinforced alignment of employability attributes. To address these gaps, the study vouches for the implementation of An Action Plan for Enhancing the Alignment between Graduating Students' Employability Attributes and Industry Requirements. This plan motivates continued school-industry partnerships that comprise hands-on learning—not just towards the end of the course, but throughout the whole program. This better prepares students for direct and significant employment after graduation.
Keywords: Skills, Core values, Attributes, Respondent groups, Academic disciplines
ACKNOWLEDGMENT
Exhausting all possibilities to make this study a reality was, indeed, something for which I am grateful during my time in the United States. There were many instances when I felt like giving up due to my busy schedule while trying catching up. Sometimes, I asked myself why I had to pursue further studies. Did I really need this for my priestly ministry? I could have chosen the comfortable path by not pursuing this study. However, I realized that I was doing this not for myself, but for the Church. With that in mind, I told myself, “I have to continue and persevere.”
I finally made it through, not by my effort alone, but by the support and guidance of the following individuals who tirelessly dedicated their skills to help me succeed. They deserve recognition.
I thank the Almighty God, most of all, for the gentle reminder that each work completed out of love is pleasing to Him. Above and beyond, I thank Him for granting me energy and resolve to pursue His will regardless of life’s trials and struggles.
I am overwhelmingly thankful to Dr. Anthony S. Ilano, Campus Director, in giving me consent to conduct this study, and to my thesis adviser, Dr. Purity V. Mata, for her assiduousness in making recommendations, improvements, and providing relevant sources connected to the study. Because of her assistance, I felt assured in pursuing this study. I would like to express my appreciation to the panel of examiners: Dr. Don Roel G. Arias, Dr. Emardy T. Barbecho, and Dr. Anna Marie C. Neiz. They provided me with their assurance and encouragement and thoroughly substantiated this study in its entirety. Their excellence has contributed significantly to producing another important output necessary for supporting our graduating students.
I am grateful to my family, finally, for their prayers, lifting me up in supplication for success in all undertakings for the good of the Church.
Wilson A. Jerusalem
Researcher
DEDICATION
This study is offered to God for choosing me to be one of His priests in the Archdiocese of Cebu. Yes, I will receive this honor with a Master’s degree in Education, but all of this is for His Church.
I am thankful to my family, and friends for their never-ending support. I at all times count on them. My success is theirs too.
Every success is just the beginning of something new. This study opens up new concerns and priorities. Whatever the next endeavor may be, I am certain that I can pursue it because of all of them who are there for me, no matter what. I can’t thank them enough.
Wilson A. Jerusalem
Researcher
LIST OF TABLES
Distribution of Respondent Groups
Demographic Profile of the Respondents According to Age
Demographic Profile of the Respondents According to Gender
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Basic Literacy and Numeracy Skills in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Basic Literacy and Numeracy Skills in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Basic Literacy and Numeracy Skills in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Basic Literacy and Numeracy Skills in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Basic Literacy and Numeracy Skills in Education as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Critical Thinking Skills in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Critical Thinking Skills in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Critical Thinking Skills in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Critical Thinking Skills in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Critical Thinking Skills in Education as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Leadership Skills in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Leadership Skills in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Leadership Skills in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Leadership Skills in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Leadership Skills in Education as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Management Skills in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Management Skills in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Management Skills in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Management Skills in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Management Skills in Education as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Interpersonal Skills in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Interpersonal Skills in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Interpersonal Skills in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Interpersonal Skills in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Interpersonal Skills in Education as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Information Technology Skills in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Information Technology Skills in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Information Technology Skills in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Information Technology Skills in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Information Technology Skills in Education as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Systems Thinking Skills in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Systems Thinking Skills in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Systems Thinking Skills in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Systems Thinking Skills in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Systems Thinking Skills in Education as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Work Ethics in Hospitality Management as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Work Ethics in Marine Engineering as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Work Ethics in Fisheries as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Work Ethics in Industrial Technology as Perceived by the Respondent Groups
One-Way Analysis of Variance on the Differences in Employability Attributes in terms of Work Ethics in Education as Perceived by the Respondent Groups
LIST OF FIGURES
1 Conceptual Framework
2 Flow of the Study
3 Location Map of the Research Environment
Chapter 1 THE PROBLEM AND ITS SCOPE
Rationale
In the global setting, the increasing number of higher education institutions and the incessant growth of industries have reformed the changing aspects of employability. Education has turned out to be a common priority, with families and societies placing high importance on academic triumph as a means of obtaining future employment. Students across the world are currently confronted with various academic program choices based on individual goals and economic situations. Regardless of the increasing number of graduates across a number of disciplines, a shared global challenge sticks it out: the misalignment between what graduates have in terms of skills and competencies, and what industries require. This matter, often termed “job mismatch,” is not just a consequence of a shortage of available jobs, but relatively disengage between educational yields and labor market demands. A strategic and collaborative partnership between academic institutions and industries is thus crucial in addressing this gap. Such partnership comprises the consistent review and co-development of curricula to guarantee that the employability attributes covering essential skills, values, and attitudes attained by students are aligned with the growing opportunities of the global workforce.
However, skills are only one feature of employability. Universities are not just training grounds for technical abilities—they are institutions accountable for nurturing both content knowledge and essential attributes that upkeep longterm employability (Oraison et al., 2019). To meet global industry standards, curriculum content must be regularly reviewed and enhanced to ensure relevance and responsiveness. Education mismatch remains a recognized issue when graduates’ qualifications do not correspond to job requirements, as noted in studies that examine educational and workforce gaps (Kiang Tal et al., 2016). Addressing this mismatch requires narrowing employability attributes to two major areas: skills and core values, which are essential for workplace adaptability. Collaboration between schools and industries is crucial in fostering this alignment through joint teaching and industry-based training initiatives (Ibeneme & Ashiebi, 2022). When these sectors work closely, the transfer of usable skills becomes more effective. Besides, forming trust, joint ownership, and mutual investment is important in promoting sustainable partnerships, as operative alignment rests heavily on the quality of the relationship between schools and industries (Badgett, 2016). This kind of teamwork is illustrated by the Gateway to Industry Schools Program in Australia, which shows how shared strategies can link the gap between education and employment (Flynn et al., 2016). Such worldwide models focus on the need for resilient institutional partnerships to build reliable learning experiences that improve employability results.
The decision to conduct this research stemmed from the need to produce localized, empirical data that could upkeep curriculum improvement and develop the employability results of graduating students at Cebu Technological University-Carmen Campus. While prior studies have explored the alignment between graduates’ attributes and industry requirements in overall or nationwide settings, this study offers a context-specific inquiry by focusing on how the skills and core values assimilated by students through five academic disciplines align with actual industry demands. By narrowing the emphasis to an exact institution, the research offers valuable insights into the sole challenges and opportunities encountered by Cebu Technological University-Carmen students as they get ready to enter the workforce. Likewise, the study’s localized scope made straight contrasts with other study limited, emphasizing the significance of conducting institution-based studies that address particular academic and industry frameworks.
This study holds valuable implications mutually within the Philippine educational setting and in the wider global framework. In the Philippines, it helps in addressing the persistent concern of education-employment mismatch by proposing localized facts that can guide academic institutions mainly Cebu Technological University-Carmen Campus in aligning their curriculum with actual industry needs. By ascertaining gaps between what students are equipped with and what employers necessitate, the results can help form more receptive strategies and curricular improvements that improve the employability of graduates. On a worldwide scale, the study supports current global discussions about connecting education and employment through resilient partnerships between schools and industries. It strengthens the idea that employability attributes mainly skills and core values must develop in response to shifting worldwide labor market demands. As economies become gradually consistent, the significance of this research covers beyond national limits, offering perceptions that may profit other emerging nations striving to develop their graduates’ readiness for a competitive workforce. Eventually, this study stimulates the vision of higher education as a shared space where academic learning and industry practice come across to empower future professionals.
Theoretical Background
This study is anchored on three main theories and relevant legal bases that serve as the groundwork for understanding and outlining the previous claims addressed here. These theoretical and legal frameworks mutually build up the structure of the research.
The Signalling Theory. Like Human Capital (HC) theory, Signalling Theory (Stiglitz, 1975, as cited in Cai, 2013) takes up a relationship between graduates in the hunt for jobs and employers. Shivoro et al. (2018) expound that graduates send signals of their capabilities to possible employers by presenting the knowledge and skills they attained in university, and that employability attributes such as skills, knowledge, and core values are vital indicators of a graduate’s potential. These attributes are assessed by employers through applications and portfolios, which serve as signals of work readiness. The authors underscore that higher education serves as a platform for graduates to show these capabilities, and that alignment between graduate attributes and industry requirements can only be realized when schools and industries work in partnership and often review curriculum content together.
The employability attributes skills and core values assimilated in school are significant elements in acquiring employment, as they signal graduates' capabilities to industries. But, if these attributes do not align with industry employability requirements, employment becomes incredible. In the first place, the school is accountable for this alignment. Thus, schools must make sure that the curriculum content aligns with industry employability requirements. Teachers should not only depend on the drafted curriculum and corresponding textbooks but should similarly attest the content alongside industry employability standards by associating with industries worldwide. This alignment is only accomplished when schools and industries cooperate and often review curriculum content together. Since higher education plays a vital role in developing employability attributes, schools should take the initiative to connect with industries, as they are the main agents in improving students' skills and core values.
The Human Capital Theory (Becker, 1964) is possibly the earliest formalized theory explaining the education mismatch occurrence. It claims that the skills learned through education signify human capital, and that investing in it leads to higher productivity and returns to education. The theory correspondingly proposes that salaries are primarily determined by the supply of human capital (Kiang Tal et al., 2016). Even though this theory emphasizes only the skill attribute as human capital for work, it also points out that employability attributes should be aligned with industry employability requirements for graduating students to be employed.
Building on this hypothetical underpinning, current literature accentuates the importance of collaboration between schools and industries in attaining such alignment. Ibeneme and Ashiebi (2022) underline the dangers of school and industry functioning in isolation, declaring that significant collaboration arises through ongoing, constant communication. Their study, The Extent of School¬Industry Collaboration for Achieving Technical Education Graduates' Industrial Usability in Cross River State, stresses that consistent dealings between these two nurturing agents is indispensable to build a mutual vision for technical education. Such collaboration, guarantees that students ’skills and core values are developed successfully, bringing about graduates who are ready for employment instantly after finishing school. Finally, this strengthens the need for a sustained and intended partnership between schools and industries in aligning employability attributes with labor market requirements.
The Technological Theory states that the existence of over-education and under-education is mainly due to technological changes. Kiang Tal et al. (2016) claimed that the fast pace of innovation leads companies to hunt for over¬educated folks who have attained school-provided technological skills that current employees may lack. These persons are esteemed since innovations and technological improvement are presumed to be better managed by more educated workers. As such, overeducated workers are the ones employers favor to retain, investing in their training and recompensing them with longer tenure. In contrast, undereducated workers are time and again confined to dead-end jobs, receiving minimal benefits or investment from employers. This difference highlights the significance of aligning curriculum content with industry employability requirements; if not, graduating students risk becoming undereducated workers if their skills and core values are not appropriately enhanced in school.
An implication of these persistent mismatches, further underscored by the Endogenous Theory of Professionalization, is the increase of degree inflation, augmented pressure on those with lower degrees, underemployment, and incompetence in the labor market (Ghaffarzadegan et al., 2017). These consequences are indications of the similar root problem—the misalignment between the employability attributes developed in schools and those truly required in the industries.
Republic Act No. 10968 or An Act of Institutionalizing the Philippine Qualifications Framework (PQF), Establishing the PQF-National Coordinating Council (NCC) and Appropriating Funds Thereof. According to Section 2 of this law, the policy of the State is to institutionalize the PQF or the Philippine Qualifications Framework to inspire learning that is lasting, make available employees with exact training standards and qualifications aligned with industry standards, and hold individuals responsible for attaining corresponding learning results. The PQF, therefore, is accountable for reminding the nurturing agents of their obligation to review curriculum content together so as to positively realize the alignment between the employability attributes of graduating students and industry employability requirements. The State guarantees that training and educational institutions abide by with exact standards and are responsible for attaining corresponding learning outcomes (RA 10968, Sec. 2).
CMO No. 13, Series of 2016 - Implementing Guidelines for Industry Partnerships Under the Sectoral Engagements Component of the IRSE Grants. This CHED Memorandum Order states that sectoral engagements with industry partners were established and counted in the IRSE (Instruction, Research, Sectoral, and Engagement) Grants to address the continuing problem of job-skills mismatch in the labor sector, which arises from, among other causes, the misalignment of classroom instruction with industry necessities, outdated industry experience among faculty, or the absence of such experience, and the lack of sustainable and substantial connections between academe and industry (CHED Memorandum Order 13, 2016). The CMO adds that these conditions yield graduates who are not equipped with the essential skills to sufficiently do tasks in the industry and involve excessive training charges for industry counterparts (CMO 13, 2016). Sectoral engagements with industry partners aim to directly address these concerns by letting faculty to work directly in industry, in that way increasing the importance and effect of classroom instruction (CMO 13, 2016). The Commission hereby issues the Implementing Guidelines for Industry Partners under the Sectoral Engagements Component of the IRSE Grants, to describe the procedures for the setting up of such partnerships and the transfer of said engagements, for the guidance of all prospective industry partners (CMO 13, 2016). With this Memorandum Order, the nurturing agents are obliged to work together and review curriculum content for the alignment of employability attributes with industry employability requirements. The Commission on Higher Education shall strive to categorize industry partners from among reliable corporations or umbrella organizations/sector coalitions in key sectors and shall sign a Memorandum of Agreement with them to officially start the partnership under the IRSE Grants (CMO 13, Article 2).
Republic Act No. 11448 or Transnational Higher Education Act. This Act is one of the legal bases for addressing the substantial mismatch found all over the Philippines. It states that the State makes available quality education important to the varying wants of the people and society (RA 11448, 2018). The State shall also attempt to update the Philippine higher education sector and present worldwide quality standards and proficiency into the country to make higher education internationally competitive, invite gifted students, faculty, and staff, and develop the country’s human resource base (RA 11448, 2018). The State shall improve combined arrangements between Philippine universities and training institutes, on the one hand, and foreign universities, on the other, and identifies that higher education shall work for as a principal instrument for producing productive knowledge, innovation, and technology to improve the appropriate technical and higher-order skills required to compete in the knowledge economy and make certain resource generation (RA 11448, 2018).
Illustrations are not included in the reading sample
Figure 1. Conceptual Framework
The persistent issue of job mismatch is addressed in this study by assessing how the employability attributes that graduates should attain align with the requirements set by industries. The Department of Labor and Employment (DOLE) has recognized skills mismatch and insufficient qualifications as main reasons behind the low hiring rate, which stood at only 9% during its prior job fairs (Pasion, 2017). This problem frequently stems from a lack of continued cooperation between schools and industries that this study brings up to as nurturing agents. These agents must mutually review and frequently bring up to date the curriculum to meet industry standards.
The Job Competition Model proposed by Thurow (1975) argues that wages are determined not solely by education but by job characteristics, emphasizing that employability requirements must align with the attributes students develop before graduation. Kiang Tal et al. (2016) further explain that job mismatch especially over-education occurs when workers pursue qualifications beyond what their jobs require, often to stay competitive in the labor queue. This concept is also supported by the Assignment Framework, which explains that mismatch arises when workers’ qualifications do not correspond with job complexity and task demands (Kiang Tal et al., 2016). Such misalignment results in varying performances among individuals with similar educational backgrounds, thereby reinforcing the need to match graduates' attributes with industry expectations.
As stated by Piatos (2022), about 40% of Filipino workers are deliberated overqualified for the works they hold. Although the Philippine Statistics Authority (as cited in Piatos, 2022) reported a progress in employment data—with the employment rate escalating to 94.8% in July 2022—concerns as regards job mismatch continue. This stresses the need for schools and industries to create tougher collaboration in curriculum scheme and skills training.
Addressing this concern entails constant and effective communication between educational institutions and industries. Badgett (2016) highlighted that the lasting triumph of school-industry partnerships rests on consistent and clear communication. However, this is frequently condensed to trifling engagements, for instance a single meeting. For alignment to be sustained, nurturing agents must vigorously take part in regular discussions, curriculum planning, and monitoring of graduate outcomes. Such hard works must be reinforced by institutional mechanisms, with Republic Acts and CHED Memorandum Orders. Badgett (2016) further stressed that educators, school leaders, and policymakers should be involved constantly in sustaining and strengthening these partnerships. Devoid of such partnership, the gap between employability attributes and industry requirements will probably continue.
Rosenberg’s (2012) study, Basic Employability Skills: A Triangular Design Approach, made use of a triangular framework including students, teachers, and industry professionals to gauge eight core employability attributes—basic literacy and numeracy, critical thinking, management, leadership, interpersonal skills, information technology proficiency, systems thinking, and work ethic. Yet, his inquiry evaluated graduates as a general group without distinguishing among academic programs and used a skills-based scoring method. In distinction, this study assesses employability alignment across five specific academic disciplines at CTU-Carmen Campus by means of a frequency scale (Always, Sometimes, Rarely, Never), proposing an added nuanced and program-specific inquiry.
In the same way, Majid et al. (2022), in their study Eight Dimensions of Basic Employability Skills: A Survey on the Academics’ Level of Awareness, accentuated the need of 21st-century soft skills for graduate employability. Their investigation focused exclusively on faculty standpoints from four academic divisions, exclusive of the perspectives of students and industry professionals. Although they employed a Likert scale, this study presents a wide-ranging, multi¬perspective scheme that includes comment from students, faculty, and industry allies.
Both studies emphasize the significance of aligning basic employability skills with workplace demands. On the other hand, the current investigation progresses this argument by analyzing the level of alignment in a definite institutional setting and through various participants. As Rosenberg (2012) stated that the gap among employers, educators, and students continues to develop, strengthening the determination of addressing this matter through targeted, inclusive, and discipline-specific evaluations. Similarly, Majid et al. (2022) stress the vital role of soft skills in employability—a basis this study builds upon through directly assessing how these features are recognized and appreciated through diverse respondent groups.
THE PROBLEM
Statement of the Problem
The study assessed the employability attributes of the graduating students of Cebu Technological University - Carmen Campus for the academic year 2024-2025 as basis for an Action Plan.
In detail, the study answers the subsequent queries:
1. What are the employability attributes of the graduating students of Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education, as perceived by respondent groups in terms of the following skills:
1.1. Basic Literacy and Numeracy;
1.2. Critical Thinking;
1.3. Leadership;
1.4. Management;
1.5. Interpersonal;
1.6. Information Technology;
1.7. Systems Thinking; and
1.8. Work Ethics?
2. Are there significant differences in the respondent groups' perceptions as regards the employability attributes for each program?
3. Based on the findings, what particular action plan can be recommended?
Null Hypothesis
The succeeding assumptions were tested at the 0.05 level of significance.
1. Ho: There is no significant difference in the perception of employability attributes among the respondent groups in the Hospitality Management program.
2. Ho: There is no significant difference in the perception of employability attributes among the respondent groups in the Marine Engineering program.
3. Ho: There is no significant difference in the perception of employability attributes among the respondent groups in the Fisheries program.
4. Ho: There is no significant difference in the perception of employability attributes among the respondent groups in the Industrial Technology program.
5. Ho: There is no significant difference in the perception of employability attributes among the respondent groups in the Education program.
Significance of the Study
This study is particularly useful for the succeeding sectors and entities:
Government. This study also calls on government agencies—the Commission on Higher Education (CHED), the Department of Trade and Industry (DTI), and the Department of Labor and Employment (DOLE)—to put in force legal frameworks that entail all involved parties to sustain alignment between employability attributes and industry requirements, in so doing addressing the concern of job mismatch.
School Administrators. This study further reminds school Administrators of their obligation to take the initiative in sustaining communication with industries. This study also functions as an important notice of a prior study by Badgett, which underlined that schools' duties consist of, but are not limited to, making sure that students have a fruitful learning experience. This experience should reassure students to ponder unfavorably, rather than solely chasing grades. Furthermore, it was also indicated that schools should be able to express how their partnerships will really influence their ability to offer significant education (Badgett, 2016).
Partner Industries / Schools. The study likewise functions as a vital reminder to schools and industries as regards their obligation to a resilient partnership, aimed at aligning curriculum content (which should enhance employability attributes) with job features that echo industry employability requirements. This alignment guarantees that any school-business partnership provides implicitly to students' readiness for professional and personal victory after bringing to an end their formal education (Badgett, 2016).
Teachers. Particularly, this study supports teachers at Cebu Technological University - Carmen Campus reexamine the curriculum content to decide whether it is still aligned with industry advances, in so doing making the most of the alignment of graduating students' employability attributes with industry requirements.
Students. This study is of countless support to college students in the Philippines who are getting ready for direct employment after graduation, as it addresses the prevalent and noteworthy misalignment of employability attributes and industry requirements that leads to job mismatch.
Future Researchers. This study supports future researchers on how the educational institutions can familiarize curricula to meet the progressing needs of industries; in addition, it recommends scrutinizing industry demands, the efficacy of educational programs, and the role of partnerships between schools, industry, and government. Moreover, it underlines the need for governments to carry out legal frameworks guaranteeing continued alignment between employability attributes and industry requirements, addressing job mismatches. Future researchers can further explore these extents to boost graduate employability and make stronger collaboration between schools, industry, and government.
Scope and Limitation
The emphasis of this study on the alignment between employability attributes and industry requirements has already been underscored by copious scholars through worldwide settings. Particularly, employers in today’s worldwide labor market place in order graduate’s practical skills over academic performance, accentuating the necessity to match what students learn with what the workplace demands (Harvey, 2000, as cited in Ahmad et al., 2011).
RESEARCH METHODOLOGY
The overall triangular design approach of the research process was presented to guarantee the precision and consistency of the data. This research fell under the general classification of quantitative research, as it focused on gathering and evaluating numerical data to draw deductions by means of tables that comprise actual data. The study is an analytical research, as the data collected were evaluated to validate the inferences. The methodology has this order: research design, flow of the study, research environment, research respondents, research instruments, data gathering procedures, data analysis, and scoring procedures applied in the study.
Design
This study made use of quantitative research to address the problem at hand. Concerning the quantitative design, this study used a descriptive- correlational research design, which connects the descriptive approach—used to recapitulate and present facts as regards the assumed variables—and the correlational approach, which defines the relationships among the gathered variables (Fraenkel et al., 2019).
This study used a conclusive research design, which involved the gathering, demonstration, scrutiny, and interpretation of variables to produce findings that could be applied in addressing the research problem. The data from survey questionnaires were collected from the designated teachers, students, and partnered industries of Cebu Technological University-Carmen Campus.
Flow of the Study
This part used the Input-Process-Output Model, or the IPO Model. This model provided the outline for the study, specifying the overall approach.
Input: In the first phase of the IPO Model, the queries suggested in this study form its contents. These queries are defining features in whether or not the Cebu Technological University-Carmen Campus aligns employability attributes with industry requirements. The queries cover the seven skills: Basic Numeracy and Literacy Skills, Critical Thinking Skills, Leadership Skills, Management Skills, Interpersonal Skills, Information Technology Skills, Systems Thinking Skills, and Core Values (Work Ethic). Ready-made queries were used by the researcher, with minor revisions in the subject and order of the queries.
Process: The second phase of the IPO Model corresponds to a series of activities, based on facts from survey questionnaires, used to bring about the preferred outcomes for the study's Input. The survey questionnaires were disseminated to a number of professors at the Cebu Technological University¬Carmen Campus, graduating students from the same school, partnered industries, and school mentors. Their answers were collected to determine whether the graduating students are fully competent to enter the workforce, and to evaluate whether there is alignment between employability attributes and industry requirements. These were determined likewise to give weight to the process—Frequency, Percentage, Mean, Standard Deviation, and Analysis of Variance.
Output: The third phase of the IPO Model focuses on the outcomes after gathering, presenting, and evaluating the figures. Based on the true answers of CTU-Carmen Campus students, teachers, partnered industries, or school mentors, the output of the survey questionnaires indicated whether the school’s graduating students are fully competent in the 7 skills and core values. Likewise, this presented the alignment between the employability attributes that are supposed to be acquired and industry requirements, and their ability to be employed instantly after graduation. An action plan was introduced after the data were collected and interpreted.
INPUT
• Employability attributes of the graduating students of Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education, as perceived by the respondent groups in terms of the following skills:
1.1. Basic Literacy and Numeracy;
1.2. Critical Thinking;
1.3. Leadership;
1.4. Management;
1.5. Interpersonal;
1.6. Information Technology;
1.7. Systems Thinking; and 1.8. Work Ethic.
• Significant differences in the perceptions of the respondent groups regarding the employability attributes across the different programs.
PROCESS
• Transmittal Letter to the CD
• Transmittal Letter to the SDS
• Transmittal Letter to the PSDS
• Frequency
• Percentage
• Mean
• Standard Deviation
• Analysis of Variance
Environment
This study, basically, was conducted at the Cebu Technological University Carmen Campus, through the support of several partner industries and schools. The campus is in Poblacion, Carmen, Cebu, right along R.M. Durano Avenue, and covers about 72,000 square meters. There is relatively a variety of programs for undergraduate and graduate students.
At present, in terms of undergraduate programs, the College of Education Arts and Sciences has programs, the Bachelor of Elementary Education (BEED), Bachelor of Secondary Education major in Mathematics (BSED-Math), and the Bachelor of Technology and Livelihood Education major in Home Economics (BTLED-HE). The College of Technology has two programs, the Bachelor of Industrial Technology Major in Computer Technology, and BS Hospitality Management, and the College of Fisheries and Allied Sciences, and the College of Maritime Sciences.
The graduate studies, the university offers the succeeding programs: the Master of Arts in Education, Major in Administration and Supervision, and the MA in Vocational Education, Master in Fisheries and Aquatic Sciences, and two Doctorate Programs — Doctor of Development Education (Dev.Ed.D.) and Doctor of Philosophy in Fisheries and Aquatic Sciences.
Numerous partner industries and locations requested privacy. Hence, their buildings are left out from the Location Map of the Research Environment. The researcher upholds confidentiality by keeping all names and facts strictly private.
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Respondents
The 275 respondents of this study comprised of the following: 31 CTU- Carmen Instructors; 182 graduating students from five Cebu Technological University-Carmen programs; and 62 individuals consisting of HR Professionals, Immediate Supervisors, and School Mentors from partner industries and schools. Samples were taken from the several programs to guarantee proper illustration. The programs comprised BS Hospitality Management, BS Marine Engineering, BS Fisheries, BS Industrial Technology, and Education (BEEd, BTLEd, and BSEdMath).
Besides, before the dissemination of the survey questionnaires, transmittal letters were secured to make sure a smooth distribution procedure.
For the student-respondents, the questionnaires were randomly disseminated through the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education. A reliable employee from Cebu Technological University-Carmen Campus helped the process. Random sampling was conducted by getting ready a list of graduating students from every program and opting for 40 participants for each program (not including Fisheries, which had only 22 qualified students). The selection was assisted by the said employee, who guaranteed that only students who freely decided to participate received the survey forms. Once accomplished, the questionnaires were collected by the selected teachers-in-charge and returned to the same reliable employee. The researcher personally collected the accomplished questionnaires.
Correspondingly, for the teacher-respondents, random sampling was also applied. A list of faculty members handling every academic program was acquired, and a random selection of teachers was made for each program to join in the study.
The same reliable employee of Cebu Technological University-Carmen helped in the dissemination and collection of the questionnaires. Only those who provided their approval took part in the survey. After the teacher-respondents responded the questionnaires, these were given back through the teachers-in- charge and forwarded back to the reliable employee, from whom the researcher personally collected the accomplished forms.
The respondents from partner industries and schools—specifically HR professionals, immediate supervisors, and school mentors—the researcher personally handled both the distribution and collection of the questionnaires. The participants were randomly selected from a list of personnel provided by the partner organizations. The same principle of voluntary participation applied.
Table 1
Distribution of Respondents Using Random Sampling
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Table 1 presents the number of respondents for students, teachers, and industries who of their own accord took part in the survey. It demonstrates that the number of student respondents is higher, with a total of 182, followed by industries with a total of 62, and a lower number of teacher respondents, tallying 31.
Table 2
Demographic Profile of the Respondents According to Age
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Table 2 presents the ages of students, teachers, and industries who freely answered the survey. The outcome indicated that with 126 participants for
student respondents, 22 years old or younger is the utmost age group, whereas the lowermost age groups are 26 and 27 years old, with simply one respondent from every category. Concerning the group of teachers, the uppermost age group is 50 years old and above, with eight respondents, whereas the lowermost age groups are 46-50 years old, 26-30 years old, and 25 years and below, with two teachers in every category. Finally, for industries, the uppermost age group is 46-50 years old, with 15 respondents, and the lowermost is 25 years and below, with one respondent.
Table 3
Demographic Profile of the Respondents According to Gender
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Table 3 shows the sexual category of respondents from students, teachers, and industries who freely took part in the survey. It specifies that among student respondents, the topmost gender is female, with 104 participants. For teachers, the topmost gender is male, with 16 participants. For industries, the topmost gender is female, with 41 participants.
Instrument
This study made use of a survey questionnaire by Rosenberg (2012) to acquire, measure, and evaluate the facts. Of the questionnaire that included 47 items, respondents rated every item on a scale from 1 to 4. The same instrument was used for all the respondent groups. The survey questionnaire created by Rosenberg (2012) is appropriate for this study because it is intended to measure key employability attributes that are directly aligned with industry requirements. The instrument’s 47 statements provided a comprehensive assessment of competencies such as skills, behaviors, and work-related attitudes needed for evaluating graduate employability.
Data Gathering Procedures
The method used in data gathering is handled with precaution. First, the respondents were informed ahead as regards the purpose of the study before the data collection initiated. Second, they were instructed that the questionnaires will be collected individually to guarantee the confidentiality of their answers. Above all, informed consent was acquired from the participants. This informed them to make sure informed consent and voluntary participation, as informed consent is a necessary principle of research ethics that permits participants to freely enter research with complete facts as regards their participation and to provide consent before participating (University of Oxford, n.d.).
Before data collection, transmittal letters, signed by the researcher, thesis adviser, and dean of the Graduate School, were sent by the researcher to the Campus Director of Cebu Technological University-Carmen Campus, asking for approval to conduct the survey and distribute the questionnaires to the a number of respondents. Upon approval by the director, the survey was initiated.
Sampling Technique
The data collected from the survey questionnaires, which were disseminated through random sampling and were used for statistical analysis.
The respondents were provided the survey questionnaires to answer. Before answering the questions, the purpose and content of the questionnaires were expounded to them. They were informed that the questionnaires were intended to address the serious job mismatch concern in the Philippines through the alignment of employability attributes with industry requirements. The respondents were cheered to respond the questions in all conscience.
The respondents' responses would not result in any negative penalties for them, as the data were not used against them. Instead, their responses contributed to the achievement of this study in addressing the recognized problem.
Another transmittal letter, signed by the Schools Division Superintendent, Senen Priscilo P. Paulin CESO V, was likewise secured, along with the PSDS endorsement letter signed by Mr. Glicerio L. Camongay, Public Schools District Supervisor-Department of Education-Carmen District.
Statistical Treatment of Data
The collected data were statistically evaluated using Microsoft Excel (Version 2010). Descriptive statistics, comprising mean and standard deviation, were calculated to summarize the dataset or the central tendency and dispersion of the answers. The mean was utilized to define the average answer, while the standard deviation measured the variability within the data. For inferential statistics, a one-way analysis of variance (ANOVA), was conducted to determine if there were significant differences between groups—teachers, students, HR Professionals, and school mentors. The Excel Data Analysis Toolpak, with a significance level set at 0.05, was utilized to do the test. Here, the p-value, p < 0.05, that designates a statistically significant difference, and the p-value, p > 0.05, that recommends no significant difference, are the bases of the interpretation of the ANOVA results. Besides, the hypothesis testing approach, where the null hypothesis (H0) holds that there was no significant difference between the ratings of employability attributes by the respondent groups, and the alternative hypothesis (H1) affirms that a significant difference occurred, was followed in the study. This statistical treatment helped measure whether students’ self-assessed employability attributes aligned with industry expectations.
The data, after being evaluated by the researcher, are guaranteed that they are handled with caution to sustain their confidentiality.
Scoring Procedures
In calculating the score based on the data collected, this study used the 4- Point Likert Scale for Agreement (Formplus, 2022). This scoring technique comprises four agreement scales: Always, Sometimes, Rarely, and Never. These scales were evaluated based on the respondents' responses. To know the frequency of a specific scale, the Mode was determined. To ascertain the average answer based on the specified scales, the Mean was likewise computed. In addition, the subsequent measures were identified: Frequency, Percentage, Standard Deviation, and Analysis of Variance. The rating scale ranges, starting from 4.00, each category spans 0.75 units: Always (3.26-4.00), Sometimes (2.51-3.25), Rarely (1.76-2.50), and Never (1.00-1.75, were calculated by dividing the overall range (4-1=3) by the four categories, resulting in an interval of 0.75.
Students and Teachers Evaluation Criteria for Employability
Attributes
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A. Industries and School Mentors Evaluation Criteria for Employability Requirements
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DEFINITION OF TERMS
The terms utilized operationally in this study are defined to guarantee a better understanding.
Basic Literacy and Numeracy Skills — These are defined in the SCANS report as the ability to read, write, speak, listen, and do basic mathematical techniques.
Critical Thinking Skills — These comprise the ability to think ingeniously, make decisions, and solve problems as cited from SCANS.
HR Professionals and/or Supervisors — These refer to individuals in charge of operations in partner industries who freely took part in the research survey as evaluators of the students’ employability attributes.
Information Technology Skills — These include the ability to choose procedures, equipment, and tools to obtain and assess data as mentioned from SCANS.
Interpersonal Skills — These include the ability to work in teams, aid others to learn, provide customer service, negotiate agreements, resolve differences, and work in a multicultural organization as cited from SCANS.
Leadership Skills — These include the ability to encourage others to attain organizational goals as cited from Schermerhorn.
Management Skills — These include the activities of planning, organizing, leading, and controlling to meet organizational goals as mentioned from Schermerhorn.
Partner Industries — These refer to companies or organizations that work together with academic institutions to help train students and assess their employability. In this study, partner industries freely took part in the research by providing feedback through selected personnel.
School Mentors — These refer to representatives from partner schools who directly oversee and train CTU students in the course of practicum or immersion programs and who also freely took part in the research survey.
Schools — These refer to higher education institutions where students obtain content knowledge and skills. In this study, schools are likely to form partnerships with industries to align education with employment requirements.
Systems Thinking Skills — These include the ability to comprehend and operate within social, organizational, and technological systems.
Chapter 2 PRESENTATION, ANALYSIS, AND INTERPRETATION OF DATA
The results of the survey questionnaires are presented comprehensively in this chapter. The data collected from the survey were evaluated and interpreted subsequently. These are presented in tabular layout and addressed separately, following the queries presented in the statement of the problem.
The triangular approach utilized in this study comprises of students, teachers, and human resource professionals, supervisors, or school mentors. In this section, we aim to define the alignment of employability attributes with industry employability requirements based on the answers from these three groups of respondents. To evaluate the differences in answers among these groups, ANOVA (Analysis of Variance) was used to spot a few significant variations in the answers and find the level to which the groups vary in their viewpoints.
1. Employability Attributes of Students
This section deliberated the results on the employability attributes of graduating students based on the survey answers. The outcomes were linked to both local and global settings and were reinforced by appropriate theoretical frameworks and legal bases that advocate the significance of employability in education and workforce readiness.
1.1. Basic Literacy and Numeracy Skills
The column chart below indicates the insights of the respondent groups concerning the employability attributes of students in Basic Literacy and Numeracy Skills, as reflected through the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
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As exposed in the column chart, the insights of students, teachers, and field-based evaluators—HR professionals, supervisors, and school mentors— showed varying levels of Basic Literacy and Numeracy Skills through academic programs. In Hospitality Management, students’ evaluation of themselves was always competent indicating a total mean of 3.33 and standard deviation of 0.51. Teachers, in contrast, assessed them higher at 3.80 with a standard deviation of 0.33, whereas HR professionals or supervisors provided a rating of 3.52 with 0.48 standard deviation. In Marine Engineering, students’ self-evaluation indicates the lowermost level at 2.85 with 0.47 standard deviation. Teachers provided a significantly higher rating of 3.80 with 0.40 standard deviation, and HR professionals or supervisors assessed them highest at 3.85 with 0.30 standard deviation. Fisheries students deliberated themselves sometimes competent with a mean of 3.25 and standard deviation of 0.56, while teachers evaluated them at 3.60 with 0.42, and HR professionals or supervisors provided 3.35 with 0.55. In Industrial Technology, evaluations through all groups were closely aligned. Students had 3.56 with 0.61 standard deviation, teachers assessed 3.54 with 0.57, and HR professionals or supervisors provided 3.82 with 0.34. Education students assessed themselves always competent with a mean of 3.38 and standard deviation of 0.50. Teachers provided 3.70 with 0.47, whereas school mentors assessed the skills as always necessary with 3.47 and 0.31.
The outcomes point out substantial repercussions for key parties. CHED, DOLE, and DTI should toughen curriculum alignment and policies to address skills gaps, particularly in Marine Engineering and Fisheries. School administrators must monitor student competencies and implement targeted academic provision. Partner industries, HR professionals, supervisors, and school mentors must sustain partnership with schools to guarantee graduates meet workplace expectations. Teachers are exhilarated to align teaching with hands-on skill demands, while students should be more hands-on in improving essential competencies. For future researchers, the outcomes point toward the deeper need for inquiry into gaps awareness and the adeptness of school¬industry alignment.
These outcomes point out substantial impacts both locally and worldwide. In the Philippine setting, the alignment perceived in programs like Hospitality Management, Industrial Technology, and Education replicates affirmative efforts toward incorporating education with industry demands, in keeping with national objectives for employability and economic growth. Yet, the misalignment in Marine Engineering and Fisheries designates a need for localized curriculum evaluation, improved skills development programs, and tougher school-industry coordination, principally in areas where these segments are vital to source of revenue. On a worldwide scale, these differences underline the significance of aligning graduate competencies with global workforce standards. As Filipino graduates continue to hunt for chances overseas, principally in maritime and technical grounds, gaps in self-perceived readiness may hamper worldwide effectiveness. Guaranteeing reliable literacy and numeracy skills through all programs supports not merely national progress but similarly the worldwide mobility and employability of Filipino graduates.
The differences and alignments in insights of Basic Literacy and Numeracy Skills among students, teachers, and workplace-based evaluators— HR professionals, supervisors, and school mentors—replicate key theoretical and legal foundations. Signaling theory elucidates that students’ self-evaluations function as indicators of their skills, although these are not constantly aligned with employer expectations. Human capital theory highlights that these skills are vital assets that impact employability, particularly apparent in aligned programs such as Industrial Technology and Education. Technological theory highlights the danger of mismatch due to progressing industry demands, as seen in the misalignments perceived in Marine Engineering and Fisheries. These results are reliable with Rosenberg’s (2012) study and Majid’s (2022) research, which accentuate that the alignment of students’ essential skills with industry expectations is vital for graduate employability. Legitimately, RA No. 10968 and RA No. 11448 dictate that educational results be matched with industry standards and societal needs, while CMO No. 13, s. 2016 endorses active partnership between academic institutions and industry stakeholders to guarantee that such alignment is attained.
Generally, there was alignment in the insight of Basic Literacy and Numeracy Skills among most respondent groups in Hospitality Management, Industrial Technology, and Education, where students, teachers, and either HR professionals or school mentors reliably rated these skills as always competent or always necessary. In contrast, no alignment was perceived in Marine Engineering and Fisheries, where students assessed themselves as simply sometimes competent, while teachers and industry representatives assessed the same skills as always competent or always necessary.
1.2. Critical Thinking Skills
The perceptions of the respondent groups regarding the employability attributes of students in terms of Critical Thinking Skills are illustrated in the column chart below, which covers the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
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The column chart indicates that in Hospitality Management, it is perceived that students’ assessment of themselves has an overall mean score of 3.38 with standard deviation of 0.49. Teachers’ evaluation to students is higher at 3.75 with a standard deviation of 0.31, whereas HR professionals’ evaluation is 3.40 with a standard deviation of 0.53. Industrial Technology students’ mean score is 3.51 with a standard deviation of 0.62. Teachers provided 3.52 with 0.47, and HR professionals gave 3.48 with 0.55. In the Education program, students’ evaluation of themselves is 3.39 with a standard deviation of 0.50. Teachers’ assessment is 3.50 with 0.45, whereas school mentors rated the skill 3.71 with a standard deviation of 0.42. In contrast, Marine Engineering exhibited misalignment. Students’ evaluation of themselves is lower at 2.77 with a standard deviation of 0.52, whereas teachers evaluated them at 3.69 with 0.60, and HR professionals at 3.79 with 0.42. Fisheries students’ assessment is 3.14 with a standard deviation of 0.56. Teachers’ evaluation is at 3.53 with a standard deviation of 0.39. HR professionals assessed Fisheries students at 3.00 with a standard deviation of 0.41.
These results have essential insinuations for a number of stakeholders. For the government, mainly CHED, DTI, and DOLE, the misalignment in Marine Engineering and Fisheries calls for reinforced policy execution, curriculum assessment, and improved partnership between school and industry to guarantee students’ critical thinking skills meet labor market criteria. School administrators are exhilarated to assess instructional schemes and learning results, particularly in programs with perception gaps, to endorse more precise self-assessment and skill development. Partner industries, HR professionals, supervisors, and school mentors should be responsible for regular, planned feedback to academic institutions to aid standardize training with real-world demands. For teachers, the outcomes stress the need to align classroom activities and evaluations thoroughly with critical thinking outcomes, whereas guiding students toward more accurate self-evaluations. Students need to be responsible, likewise, for improving core employability skills and look for provision where gaps keep going. Finally, future researchers need to discover the roots of misalignment, assess the efficacy of interventions, and scrutinize how self-perception influences employability in particular areas.
The findings denote main concerns for both local and global settings. The alignment manifested in Hospitality Management, Industrial Technology, and Education, in the Philippine context, emphasizes an improvement of schools and industries in providing students with the critical thinking skills requisite for employment. Nonetheless, the misalignment in Marine Engineering and Fisheries highlights otherwise the need for interventions like curriculum updates, tougher industry-academe partnerships. Worldwide, the observed gaps raise concerns regarding the international competitiveness of graduates in technical and maritime fields. As Filipino professionals continue to take part in the global workforce, mainly in high-demand sectors, guaranteeing consistent growth and insight of critical thinking skills is important to sustain global employability standards and answer efficiently to international labor market demands.
The alignment of Critical Thinking Skills in Hospitality Management, Industrial Technology, and Education, and the misalignment in Marine Engineering and Fisheries, support a number of theoretical and legal frameworks. Signaling theory proposes that graduates connect their readiness to employers through self-perceived skills; yet, the misalignment perceived in Marine Engineering and Fisheries designates that these signals may be weak or inaccurate, possibly affecting employability. Human capital theory strengthens the idea that critical thinking is a core asset contributing to work readiness, and its inconsistent growth across programs may decline students’ labor market value. Technological theory further enlightens how growing industry demands can produce mismatches between education and job requirements, which could clarify the skills gaps in more focused fields like Marine Engineering. In the Philippine setting, RA No. 10968 orders the alignment of students’ qualifications with industry demands, and RA No. 11448 stresses the significance of a responsive education to societal and economic changes. Furthermore, in order to guarantee graduates meet workplace standards, the industry-academe partnerships are accorded great importance by CHED Memorandum Order No. 13, series of 2016. These findings similarly align with the assumptions of Rosenberg (2012) and Majid (2022), in which both of whom accentuate that employability hinges on how well student competencies match industry demands—in soft skills such as critical thinking. The current gaps suggest a need to strengthen evaluation accuracy, curricular significance, and school¬industry partnership to warrant graduates are well prepared for both local and global employment.
Generally, there was alignment in the perception of Critical Thinking Skills among Hospitality Management, Industrial Technology, and Education respondent groups, where students, teachers, and either HR professionals or school mentors consistently perceived these skills as always competent or always necessary. In contrast, no alignment was perceived in Marine Engineering and Fisheries, where students regarded themselves only sometimes competent, while teachers and industry representatives viewed these skills as always competent or necessary, signifying a gap between self-assessment and external expectations.
1.3. Leadership Skills
The column chart below presents the perceptions of the respondent groups concerning the employability attributes of students in Leadership Skills across the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
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The column chart indicates that the majority of Hospitality Management students regarded themselves as always competent in leadership skills, with a mean score of 3.57 and a standard deviation of 0.48. Their teachers assessed them higher at 3.83 with a standard deviation of 0.23, whereas HR professionals deliberated these skills always necessary, giving a mean score of 3.67 and a standard deviation of 0.46. In Marine Engineering, students evaluated themselves as sometimes competent, with a mean score of 3.11 and a standard deviation of 0.39. Their teachers, nevertheless, regarded them as always competent, with a mean score of 3.43 and a standard deviation of 0.76, whereas HR professionals toughly accentuated the necessity of leadership skills with a mean score of 4.00 and a standard deviation of 0.00. Fisheries students regarded themselves always competent, with a mean score of 3.47 and a standard deviation of 0.58, which aligned closely with their teachers’ evaluation of 3.53 and a standard deviation of 0.45. HR professionals in the fisheries sector deliberated leadership skills always necessary, assigning a mean score of 3.30 and a standard deviation of 0.26, although they identified perseverance toward goal fulfillment as only sometimes necessary. Industrial Technology students described being always competent, with a mean score of 3.67 and a standard deviation of 0.54, which was consistent with the teachers’ rating of 3.43 and a standard deviation of 0.45. HR professionals correspondingly deliberated these skills as always necessary with 3.58 as mean score and 0.46 as standard deviation. Education students, however, considered themselves as always competent in leadership with 3.52 as mean score and 0.47 as standard deviation. Their teachers bequeathed the highest rating with 3.90 as mean score and 0.17 as standard deviation. Whereas, school mentors evaluated these skills as always necessary with 3.84 as mean score and 0.33 as standard deviation.
These results hold substantial insinuations for a number of stakeholders in education and workforce growth. For the government, mainly CHED, DTI, and DOLE, the misalignment in Marine Engineering accentuates the need to reexamine competency frameworks and toughen monitoring mechanisms to guarantee that leadership skills are efficiently developed and aligned with national employment demands. School administrators must assess the student’s self-assessments to boost leadership development programs, mainly in technical fields where perception gaps are apparent. Partner industries, HR professionals, supervisors, and school mentors have an essential role in providing regular feedback to guarantee that training remains significant for students’ readiness for real-world demands. For teachers, the gap in Marine Engineering emphasizes the significance of not only teaching leadership skills but likewise assisting students recognize and confidently apply them. Students are encouraged to reflect unfavorably on their own abilities and search for opportunities to toughen their leadership aptitudes through training and mentorship. With that, future researchers should discover the root bases of these perception gaps, measure the efficacy of existing leadership training styles, and endorse targeted interventions to link the gap between educational outcomes and workplace demands.
These findings denote that, locally, the Philippines must continue firming up its leadership growth initiatives across academic programs to warrant graduates are adequately equipped for the demands of the workforce. The perceived alignment in most programs echoes growth in incorporating employability skills into education, but the misalignment in Marine Engineering signals a need for program-specific improvements, particularly in student self¬confidence and self-awareness. This calls for a closer school-industry partnership to guarantee leadership aptitudes are both imparted and acknowledged by students, as accentuated in national policies like RA 10968 and CHED Memorandum Order No. 13, s. 2016. Worldwide, the results echo a common challenge where technical disciplines frequently face gaps between educational planning and perceived readiness. This underlines the significance of promoting leadership as a universal competency, not just in industry or education sectors, but as well in science, technology, engineering, and maritime fields. As global industries become more interconnected and tough, institutions worldwide must improve systems to frequently align students' self-perceptions with global employer expectations through vigorous evaluation, feedback, and mentorship programs.
The findings, which indicate alignment in the perception of leadership skills among most respondent groups in Hospitality Management, Fisheries, Industrial Technology, and Education—but then a notable misalignment in Marine Engineering—can be scrutinized through the lens of established theories and legal bases. Signaling theory proposes that students’ perceived competence in leadership serves as a signal to potential employers; accordingly, the misalignment in Marine Engineering may decline the students’ employability signal and lessen their confidence in the job market. From the standpoint of Human Capital Theory, leadership skills denote a critical form of human capital that contributes to a graduate’s productivity and importance to employers. The gap in Marine Engineering underscores a probable underdevelopment or under recognition of this capital. In the meantime, Technological Theory suggests that education systems may lapse in adapting leadership training to present workplace expectations because of the swift progress of industries, feasibly leading to such mismatches. Thus, it remains highly relevant the mandates from the three legal bases: the call to align student skills with industry demands (RA 10968), make sure that education keeps pace with societal and technological changes (RA 11448), and toughen school-industry partnerships through regular feedback and curriculum updates (CHED Memorandum Order No. 13, s. 2016). These policy directions have been supported by Rosenberg (2012) who underlined that leadership is a core employability attribute required across sectors, and Majid (2022) who accentuated that leadership development should be on purpose and included into both academic and practical training. The misalignment perceived in Marine Engineering, consequently, has local and global impact which does not only indicates an area for targeted improvement but also strengthens the wider need for alignment between education and labor market demands.
Overall, an alignment was perceived among the respondent groups in Hospitality Management, Fisheries, Industrial Technology, and Education, where students, teachers, and either HR professionals or school mentors consistently assessed these leadership skills as always competent or always necessary. Nonetheless, a notable no alignment was perceived in Marine Engineering, where students regarded themselves as only sometimes competent, whereas teachers and HR professionals deliberated leadership skills as always competent or necessary.
1.4. Management Skills
The perceptions of the respondent groups concerning the employability attributes of students in relation to Management Skills are depicted in the column chart below, which highlights data from the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
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The column chart presents that the majority of Hospitality Management students find themselves always competent in their management skills, with an overall mean score of 3.47 and a standard deviation of 0.50. Their teachers evaluated them as always competent, with a mean score of 3.67 and a standard deviation of 0.41, which the students affirm. HR professionals in the hospitality sector considered these skills always necessary, with a mean score of 3.59 and a standard deviation of 0.50. In contrast, the majority of Marine Engineering students perceived themselves as only sometimes competent, with a mean score of 2.83 and a standard deviation of 0.49. However, their teachers viewed them as always competent, with a mean score of 3.50 and a standard deviation of 0.69, while HR professionals regarded these skills as always necessary, assigning the highest possible mean score of 4.00 and a standard deviation of 0.00. The majority of Fisheries students rated themselves always competent, with a mean score of 3.28 and a standard deviation of 0.61. Their teachers shared this assessment, with a mean score of 3.63 and a standard deviation of 0.52. HR professionals, however, considered management skills only sometimes necessary for fisheries students, with a mean score of 2.94 and a standard deviation of 0.47. In the Industrial Technology program, most students perceived themselves as always competent, with a mean score of 3.58 and a standard deviation of 0.61. Teachers likewise rated them as always competent, with a mean score of 3.36 and a standard deviation of 0.54, aligning with student perceptions. HR professionals regarded these skills as always necessary, with a mean score of 3.32 and a standard deviation of 0.47. Lastly, the majority of Education students considered themselves always competent in management skills, with a mean score of 3.37 and a standard deviation of 0.50. Their teachers agreed, rating them at 3.46 with a standard deviation of 0.51, and school mentors viewed these skills as always necessary, giving a mean score of 3.80 and a standard deviation of 0.37.
The findings suggest several key implications for stakeholders in education and workforce development. For government agencies such as CHED, DTI, and DOLE, the observed alignment in Hospitality Management, Industrial Technology, and Education indicates that policies and frameworks aimed at employability development—such as outcomes-based education and industry¬academic alignment—are producing intended results in certain fields. However, the misalignment in Marine Engineering and Fisheries highlights the need for targeted policy interventions to strengthen leadership and management skill training in technical programs. This could mean revisiting curriculum standards or expanding industry immersion requirements. For school administrators, the findings call for enhanced internal review of program-specific curricula, particularly in Marine Engineering and Fisheries, to ensure that soft skills like management are not undervalued. Partner industries, HR professionals, supervisors, and school mentors are reminded of their critical role in communicating current workplace demands to the academe through continuous feedback, collaboration, and real-world training opportunities. For teachers, the results underscore the need to foster realistic self-assessment in students and to integrate more applied learning experiences that develop managerial competencies. Students, on the other hand, are encouraged to actively engage in developing soft skills beyond academic mastery, as employer expectations increasingly demand well-rounded graduates. Lastly, future researchers are invited to explore the causes of perception gaps—especially in Marine Engineering and Fisheries—and to investigate interventions that may bridge these gaps, contributing to more responsive and effective education-to- employment pathways.
The findings imply that, in the local Philippine context, certain academic programs such as Hospitality Management, Industrial Technology, and Education are effectively developing students' management skills in line with industry expectations, as shown by the alignment among students, teachers, and HR professionals or school mentors. This alignment suggests that these programs are succeeding in preparing students for workplace demands. However, the misalignment observed in Marine Engineering and Fisheries reveals areas where students' self-perceptions of their management skills fall short of what is expected by professionals in the field. This gap indicates a need for improved curriculum design, student engagement, or industry exposure to better prepare graduates for real-world responsibilities. On a global scale, the findings reflect a continuing concern about the disconnect between educational preparation and employer expectations, particularly in technical fields. In a globally competitive labor market, such gaps may affect the international employability of graduates and highlight the importance of consistent alignment between education and workplace competencies across sectors.
The findings reflect key insights drawn from established theories and legal frameworks. From the lens of Signaling Theory, students in Hospitality Management, Industrial Technology, and Education appear to be effectively signaling their management competencies to employers, as supported by the alignment in perceptions across respondent groups. Conversely, the misalignment in Marine Engineering and Fisheries suggests a weak signal from students, potentially affecting their employability. According to Human Capital Theory, the alignment in some programs indicates that the skills developed by students are recognized as valuable assets in the labor market, while the gaps in other fields point to inefficiencies in skill development that may hinder workforce readiness. Technological Theory also helps explain these mismatches, as rapidly evolving industry demands—especially in technical sectors—can result in graduates being underprepared or overqualified for certain roles. These findings are consistent with Rosenberg's (2012) assertion that core competencies like management must be explicitly integrated and reinforced in curricula, and with Majid’s (2022) conclusion that alignment between academic preparation and industry needs is crucial for graduate success. Legally, the results underscore the relevance of RA No. 10968, which promotes the alignment of student qualifications with industry standards, and RA No. 11448, which mandates educational responsiveness to evolving societal needs. Similarly, CHED Memorandum Order No. 13, s. 2016, which encourages deeper industry-academe collaboration, remains highly pertinent, especially for programs where misalignment persists. Together, these perspectives emphasize the urgent need for continual curriculum evaluation, improved industry-academe collaboration, and stronger focus on employability attributes to ensure that graduates are equipped for both local and global workforce demands.
Overall, there was alignment in the perception of management skills among the respondent groups in Hospitality Management, Industrial Technology, and Education, where students, teachers, and either HR professionals or school mentors consistently rated these skills as always competent or always necessary. In contrast, no alignment was observed in Marine Engineering, where students perceived themselves as only sometimes competent, while their teachers and HR professionals viewed management skills as always competent or necessary. Similarly, Fisheries showed misalignment, as students and teachers considered themselves and their learners always competent, yet HR professionals rated these skills as only sometimes necessary, reflecting a gap between educational preparation and workplace expectations.
1.5. Interpersonal Skills
The column chart below shows the perceptions of the respondent groups regarding the employability attributes of students in Interpersonal Skills across the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Illustrations are not included in the reading sample
The column chart presents that the majority of Hospitality Management students considered themselves always competent in their interpersonal skills, with a mean score of 3.68 and a standard deviation of 0.44. Their teachers agreed, rating them always competent with a mean of 3.83 and a standard deviation of 0.41, while HR professionals found such skills always necessary, with a mean of 3.70 and a standard deviation of 0.42. In contrast, Marine Engineering students rated themselves only sometimes competent, with a mean of 3.03 and a standard deviation of 0.41, while their teachers rated them always competent with a mean of 3.78 and a standard deviation of 0.25, and the HR professionals viewed these skills as always necessary, giving the highest possible mean score of 4.00 with no deviation. Fisheries students reported themselves as always competent with a mean of 3.60 and a standard deviation of 0.53, with teachers agreeing with a mean of 3.72 and a standard deviation of 0.44, but the HR professionals considered interpersonal skills only sometimes necessary with a mean of 3.25 and a standard deviation of 0.44. Industrial Technology students rated themselves always competent with a mean of 3.76 and a standard deviation of 0.39, echoed by their teachers with a mean of 3.62 and a standard deviation of 0.46, while the HR professionals also considered such skills always necessary with a mean of 3.67 and a standard deviation of 0.39. Lastly, Education students rated themselves always competent with a mean of 3.64 and a standard deviation of 0.45, supported by their teachers’ perfect score of 4.00 and a standard deviation of 0, and school mentors considered these skills always necessary with a mean of 3.86 and a standard deviation of 0.31.
These findings have significant implications for various stakeholders. For government agencies such as CHED, DTI, and DOLE, the alignment in most programs suggests that current policies are supporting the development of interpersonal skills, but the misalignment in Marine Engineering highlights the need for targeted interventions, curriculum review, and stronger academe¬industry collaboration to ensure soft skills are effectively developed. School administrators can use these insights to evaluate program effectiveness and introduce initiatives to strengthen interpersonal skills training, particularly in programs with noted misalignment. Partner industries, HR professionals, supervisors, and school mentors are encouraged to take a more active role in mentoring, feedback, and curriculum enhancement to bridge perception gaps and ensure workplace readiness. Teachers may need to reflect on their assessment methods and collaborate with industry partners to provide students with real-world applications of interpersonal skills. For students, the findings emphasize the importance of self-awareness and continuous development of soft skills, encouraging them to seek feedback and engage in activities that build interpersonal competence. Lastly, future researchers may investigate the root causes of misalignment, particularly in Marine Engineering, and explore effective strategies or interventions to enhance students’ confidence and interpersonal skill development across various academic disciplines.
Based on the data, the findings have meaningful implications for both local (Philippine) and global contexts. Locally, in the Philippines, the alignment observed in most programs such as Hospitality Management, Fisheries, Industrial Technology, and Education indicates that many higher education institutions are successfully fostering interpersonal skills that meet both academic and industry expectations. This suggests that efforts by CHED and other educational bodies to promote employability skills are bearing fruit. However, the lack of alignment in Marine Engineering raises concerns about specific programs where students may not feel adequately prepared, highlighting the need for targeted curriculum improvement, confidence-building interventions, and stronger collaboration between educational institutions and industry stakeholders. Addressing these gaps is crucial for enhancing the employability and competitiveness of Filipino graduates, especially in technical fields where interpersonal skills are increasingly essential. Globally, these findings underscore the universal importance of soft skills as key employability traits valued across industries. The alignment in most programs reflects a growing recognition that education must not only impart technical knowledge but also develop essential human skills such as communication, teamwork, and adaptability—skills that are critical in diverse, multicultural, and technologically integrated workplaces. Meanwhile, the misalignment in Marine Engineering may reflect a broader global challenge in technical fields where soft skills are often underemphasized in favor of hard skills. Therefore, these insights can inform global discussions on curriculum development, lifelong learning, and workforce readiness, especially in sectors with international mobility like engineering and maritime professions.
The alignment in the perception of interpersonal skills among respondent groups in Hospitality Management, Fisheries, Industrial Technology, and Education—where students, teachers, and either HR professionals or school mentors consistently rated these skills as always competent or always necessary—demonstrates a strong implementation of Human Capital Theory, which views education as an investment in the development of skills that enhance employability and productivity. This alignment also supports Signaling Theory, as it sends a clear and positive signal to employers that graduates from these programs are well-prepared in both technical and interpersonal competencies. In contrast, the misalignment observed in Marine Engineering— where students rated themselves only sometimes competent, while teachers and industry professionals viewed interpersonal skills as always necessary— indicates a potential gap in self-perception or training, which weakens the employability signal and calls for targeted intervention. Through the lens of Technological Theory, the findings reflect how educational programs are responding to the evolving demands of modern industries that increasingly require collaboration, communication, and adaptability—skills that should be integrated even more deliberately in technically focused programs like Marine Engineering. These insights are reinforced by legal frameworks such as RA No. 10968 (Philippine Qualifications Framework Act), which mandates alignment between educational outcomes and industry needs, and RA No. 11448 (Transnational Higher Education Act), which emphasizes global competitiveness—especially relevant for fields like Marine Engineering. Additionally, CHED Memorandum Order No. 13, s. 2016 underscores the importance of outcomes-based education that includes interpersonal skills as graduate attributes, further validating the alignment observed in Hospitality Management. The findings also resonate with the frameworks of Rosenberg (2012), who highlighted interpersonal and teamwork skills as essential workplace competencies, and Majid et al. (2022), who stressed the need for industry¬academe collaboration to bridge skill gaps. Therefore, these findings suggest that while most programs are effectively developing interpersonal competencies in line with policy, theory, and industry standards, programs like Marine Engineering require focused efforts to improve students’ self-perception and interpersonal readiness, ensuring the holistic formation of graduates fit for both local and global labor markets.
Overall, there is alignment in the perception of interpersonal skills among the respondent groups in Hospitality Management, Fisheries, Industrial Technology, and Education, where students, teachers, and either HR professionals or school mentors consistently rated these skills as always competent or always necessary. In contrast, Marine Engineering showed no alignment, as students perceived themselves as only sometimes competent, while their teachers and industry professionals viewed interpersonal skills as always competent or necessary.
1.6. Information Technology Skills
The perceptions of the respondent groups concerning the employability attributes of students in relation to Information Technology Skills are illustrated in the column chart below, which summarizes data from the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
rated themselves as always competent in their information technology skills, with a mean score of 3.29 and a standard deviation of 0.59. Similarly, their teachers evaluated them as always competent, with a mean score of 3.33 and a standard deviation of 0.45, while HR professionals considered these skills always necessary, with a mean score of 3.59 and a standard deviation of 0.57. In Marine Engineering, students perceived themselves as only sometimes competent, with a mean score of 2.95 and a standard deviation of 0.40, while their teachers rated them as always competent, with a mean score of 3.60 and a standard deviation of 0.49—an assessment that students did not share. HR professionals in the marine engineering field considered information technology skills always necessary, assigning the highest mean score of 4.00 with no deviation. Fisheries students viewed themselves as sometimes competent, with a mean score of 3.14 and a standard deviation of 0.70, whereas their teachers rated them as always competent, with a mean score of 3.48 and a standard deviation of 0.40. However, HR professionals considered these skills only sometimes necessary, with a mean score of 3.00 and a standard deviation of 0.26. In Industrial Technology, students viewed themselves as always competent, with a mean score of 3.59 and a standard deviation of 0.55. Their teachers shared this view, rating them as always competent with a mean score of 3.53 and a standard deviation of 0.42, while HR professionals also regarded these skills as always necessary, with a mean score of 3.57 and a standard deviation of 0.49. Lastly, Education students rated themselves as always competent in information technology skills, with a mean score of 3.26 and a standard deviation of 0.59. Their teachers also rated them as always competent, with a mean score of 3.55 and a standard deviation of 0.46, although the students sometimes disagreed. School mentors considered these skills always necessary, with a mean score of 3.90 and a standard deviation of 0.30.
Based on these findings, there are important implications for various stakeholders. For government agencies such as CHED, DTI, and DOLE, the alignment in most programs affirms that current policies promoting employability and digital literacy are effective, particularly in Hospitality Management, Fisheries, Industrial Technology, and Education. However, the misalignment in Marine Engineering signals the need for policy review and the development of targeted programs to enhance student confidence and competence in information technology skills—especially critical in a technologically driven field. School administrators can use these insights to assess the effectiveness of IT integration across programs and to implement support mechanisms—such as workshops or lab-based interventions—in courses where student self¬assessment does not align with institutional or industry expectations. For partner industries, HR professionals, supervisors, and school mentors, the findings reinforce the value of sustained collaboration with educational institutions to ensure that students graduate with industry-relevant IT skills. Their active role in curriculum co-development, internships, and feedback loops is essential, especially in Marine Engineering, to address the perceived skill gap. Teachers are encouraged to examine and adjust their instructional strategies and assessment tools to ensure students not only acquire IT competencies but also recognize and feel confident in using them. This is especially necessary in programs where student self-perception diverges from teacher evaluations. For students, the findings highlight the importance of self-awareness and active engagement in skill development, particularly in areas where they may underestimate their competencies. Lastly, future researchers may explore the underlying causes of misalignment in Marine Engineering, examine student confidence and digital readiness, and assess the impact of intervention programs designed to bridge the gap between perceived and actual competence in information technology skills.
Based on the data, the implications for both local (Philippine) and global aspects are significant. Locally, in the Philippines, the alignment in Information Technology (IT) skills perception among students, teachers, and industry representatives in Hospitality Management, Fisheries, Industrial Technology, and Education reflects the positive impact of national efforts—such as CHED’s outcomes-based education and the integration of digital competencies across curricula—to prepare students for the digital demands of the workforce. However, the misalignment in Marine Engineering signals a gap between student confidence and actual industry expectations, highlighting the need for targeted interventions, enhanced digital training, and more practical exposure in that program. This insight is critical for national competitiveness and workforce readiness in industries like maritime, where IT is increasingly essential. Globally, the findings underscore the growing recognition that IT skills are not only technical assets but also foundational to employability across diverse sectors. The alignment in most Philippine programs suggests that local graduates may be prepared to compete in the global job market, particularly in fields where digital competency is a standard requirement. However, the disconnect in Marine Engineering mirrors a global trend in some technical fields where digital skill development may lag behind evolving technological demands. This emphasizes the need for international benchmarking, cross-border educational collaborations, and continuous upskilling to ensure that graduates are not only locally employable but globally competitive in an increasingly digitalized world.
The implications for both local and global aspects align closely with relevant theories, legal frameworks, and the models of Rosenberg (2012) and Majid (2022). Locally, the alignment in the perception of Information Technology (IT) skills among students, teachers, and industry representatives in programs like Hospitality Management, Fisheries, Industrial Technology, and Education reflects the effective implementation of CHED’s outcomes-based education and national efforts to integrate digital competencies into higher education curricula. This supports the Human Capital Theory, which views education as an investment in skills that enhance productivity and employability, and Signaling Theory, as the consistent assessment of IT skills across stakeholders sends a positive signal to employers about graduate readiness. In contrast, the misalignment in Marine Engineering—where students rate themselves as only sometimes competent while teachers and industry see IT skills as always necessary—highlights a gap in student confidence or training, suggesting the need for enhanced digital education, targeted interventions, and practical exposure. This disconnect also reflects the challenges emphasized by Technological Theory, which underscores the pressure on education systems to adapt to rapid technological change. Globally, the findings show that Filipino graduates, particularly from aligned programs, are increasingly prepared for a digital workforce, while the Marine Engineering gap mirrors international trends where technical fields may underdevelop soft and digital skills. These implications resonate with RA No. 10968 (Philippine Qualifications Framework Act), which promotes alignment between education and labor market needs, and RA No. 11448 (Transnational Higher Education Act), which emphasizes the global competitiveness of Filipino graduates. The alignment also supports the principles of CHED Memorandum Order No. 13, s. 2016, which highlights IT skills as part of graduate outcomes. Moreover, the findings affirm Rosenberg’s framework that includes technological literacy as a core employability skill and Majid’s call for stronger industry-academe collaboration to address skills mismatches. Thus, while most Philippine programs demonstrate effective alignment with theoretical and legal standards, Marine Engineering requires focused reforms to ensure students not only possess IT skills but also recognize and confidently apply them—thereby enhancing both national workforce readiness and global competitiveness.
Overall, there is alignment in the perception of Information Technology skills among the respondent groups in Hospitality Management, Fisheries, Industrial Technology, and Education, where students, teachers, and either industry representatives or school mentors generally rated these skills as always competent or always necessary. However, Marine Engineering showed no alignment, as students perceived themselves as only sometimes competent, while their teachers rated them as always competent and industry representatives viewed these skills as always necessary.
1.7. Systems Thinking Skills
The column chart below presents the perceptions of the respondent groups regarding the employability attributes of students in Systems Thinking Skills across the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Illustrations are not included in the reading sample
The column chart shows that the majority of Hospitality Management students find themselves always competent in their systems thinking skills, with an overall mean score of 3.28 and a standard deviation of 0.60. Similarly, their teachers evaluated them as always competent, with a mean score of 3.31 and a standard deviation of 0.51, while the industry considered their skills always necessary, with a higher mean score of 3.66 and a standard deviation of 0.50. In contrast, the majority of Marine Engineering students find themselves sometimes competent, with a mean of 2.83 and a standard deviation of 0.53, whereas their teachers rated them always competent, with a mean score of 3.57 and a standard deviation of 0.65, a view the students do not share. The Marine Engineering industry, however, rated their skills as always necessary, giving the highest mean score of 4.00 and a standard deviation of 0.00. Meanwhile, the majority of Fisheries students also find themselves sometimes competent, with a mean score of 3.06 and a standard deviation of 0.69, while their teachers rated them always competent, with a mean score of 3.48 and a standard deviation of 0.44, and the industry considered their systems thinking skills only sometimes necessary, with a mean score of 2.68 and a standard deviation of 0.47. The majority of Industrial Technology students rated themselves always competent, with a mean score of 3.64 and a standard deviation of 0.47, which aligned with their teachers’ assessment of a mean score of 3.49 and a standard deviation of 0.43, and the industry also deemed their skills always necessary, with a mean score of 3.61 and a standard deviation of 0.53. Lastly, the majority of Education students viewed themselves as always competent, with a mean score of 3.26 and a standard deviation of 0.58, and their teachers shared this assessment with a mean score of 3.52 and a standard deviation of 0.48, although some students disagreed. School mentors, however, rated their systems thinking skills as always necessary, with a mean score of 3.82 and a standard deviation of 0.35.
Based on these data, the findings carry significant implications for various stakeholders. For government agencies such as CHED, DTI, and DOLE, the general alignment in most disciplines indicates that current policies like outcomes-based education and workforce readiness initiatives are effective, though the misalignment in Marine Engineering calls for targeted interventions and closer industry-academe collaboration. School administrators can view the results as validation of existing strategies in programs like Hospitality Management, Industrial Technology, and Education, while also recognizing the need to reassess curricular and support mechanisms in Marine Engineering. Partner industries, HR professionals, supervisors, and school mentors are encouraged to maintain strong engagement with schools and enhance internship and mentoring programs to ensure that graduate competencies meet workplace demands. Teachers must reflect on their evaluation practices, especially in areas where their perceptions differ from those of students, and adopt more student¬centered strategies to foster realistic self-assessment. Students are reminded to seek feedback and align their self-perceptions with actual expectations, especially in fields like Marine Engineering where confidence may not match required competency levels. Lastly, future researchers are encouraged to investigate the factors contributing to perception gaps and to explore the long¬term effects of systems thinking skills on employment and career success. Overall, the findings underscore the need for ongoing collaboration among all education and labor stakeholders to ensure that systems thinking skills are effectively taught, accurately assessed, and aligned with industry expectations.
The findings have significant implications for both local and global contexts. Locally, in the Philippines, they affirm that national efforts such as CHED’s outcomes-based education, DTI’s promotion of industry-academe collaboration, and DOLE’s workforce readiness programs are positively influencing the alignment between educational outcomes and industry expectations, particularly in Hospitality Management, Industrial Technology, and Education. However, the evident misalignment in Marine Engineering highlights the need for targeted improvements in curriculum delivery, student support, and stronger partnerships with local maritime industries. Globally, the general alignment in key programs reflects the country’s growing capacity to produce graduates equipped with essential 21st-century competencies, such as systems thinking, making them competitive in the international labor market, especially in fields like hospitality and education. The misalignment in Marine Engineering, however, carries broader implications, considering the Philippines’ significant role in supplying maritime professionals worldwide; addressing this gap is critical to sustaining the country’s global reputation and competitiveness. Overall, the findings call for sustained collaboration among educational institutions, industries, and government agencies to ensure that systems thinking skills are effectively cultivated and aligned with both local workforce needs and global competency standards.
The findings are highly relevant to several foundational theories, national legal bases, and employability frameworks. First, under Human Capital Theory, the alignment between students’ perceived systems thinking skills and industry expectations in most disciplines confirms that investments in education—such as curriculum enhancement and teacher development—translate into increased productivity and employability. Signaling Theory is also reflected, particularly in programs like Hospitality Management and Education, where consistent perceptions across stakeholders suggest that credentials and skill demonstrations reliably signal job readiness. Technological Theory further explains the relevance of embedding systems thinking as a core competency in response to the rapidly evolving demands of technologically driven industries. Legally, the findings affirm the goals of Republic Act No. 10968 (Philippine Qualifications Framework Act), which ensures alignment between educational outcomes and labor market requirements, and Republic Act No. 11448 (Transnational Higher Education Act), which supports international quality standards in education—especially critical in globally competitive fields like Marine Engineering. The results also support CHED Memorandum Order No. 13, s. 2016, which promotes strong industry-academe collaboration for curriculum relevance and graduate employability. Finally, the findings reflect the framework of Rosenberg (2012) and Majid (2022), who emphasized that employability is a shared responsibility among students, educators, employers, and policymakers. The data highlight how collaborative efforts contribute to aligned perceptions and readiness in most programs, while gaps—such as those found in Marine Engineering—indicate areas where closer stakeholder coordination is needed to ensure that graduates develop competencies that meet both local and global industry expectations.
Overall, there is general alignment in the perception of Systems Thinking skills among most respondent groups in Hospitality Management, Industrial Technology, and Education, where students, teachers, and industry or school mentors consistently viewed the skills as always competent and necessary. In Fisheries, partial alignment is observed, as students considered themselves sometimes competent, which corresponds with the industry's view that these skills are sometimes necessary, though teachers rated them higher. However, a clear misalignment exists in Marine Engineering, where students rated themselves lower than their teachers and industry representatives, who both viewed the skills as always competent and necessary.
1.8. Work Ethics
The perceptions of the respondent groups regarding the employability attributes of students in relation to Work Ethics are depicted in the column chart below, which summarizes the data across the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Illustrations are not included in the reading sample
The column chart shows that the majority of Hospitality Management students find themselves always competent in their work ethic, with a mean score of 3.56 and a standard deviation of 0.45. Similarly, the majority of their teachers evaluated them as always competent, with a mean score of 3.62 and a standard deviation of 0.73—an assessment the students agree with. The Hospitality Management industry also considered their work ethic to be always necessary, with a mean score of 3.76 and a standard deviation of 0.33. In contrast, the majority of Marine Engineering students find themselves sometimes competent, with a mean score of 2.86 and a standard deviation of 0.65, while their teachers rated them always competent, with a mean score of 3.74 and a standard deviation of 0.26—an evaluation the students do not agree with. The Marine Engineering industry viewed their work ethic as always necessary, with a mean score of 3.96 and a standard deviation of 0.07. The majority of Fisheries students rated themselves always competent, with a mean score of 3.51 and a standard deviation of 0.65, which aligns with their teachers’ evaluation of always competent, with a mean score of 3.76 and a standard deviation of 0.41. The Fisheries industry, however, considered their work ethic to be always necessary but gave a slightly lower mean score of 3.32 and a standard deviation of 0.41. Similarly, the majority of Industrial Technology students viewed themselves as always competent, with a mean score of 3.66 and a standard deviation of 0.51, while their teachers evaluated them as sometimes competent, with a mean score of 3.24 and a standard deviation of 0.61—an assessment the students do not agree with. The Industrial Technology industry rated their work ethic as always necessary, with a mean score of 3.82 and a standard deviation of 0.35. Lastly, the majority of Education students viewed themselves as always competent in their work ethic, with a mean score of 3.54 and a standard deviation of 0.51, which aligns with their teachers’ evaluation of always competent, with a mean score of 3.69 and a standard deviation of 0.29. School mentors also considered their work ethic to be always necessary, with a mean score of 3.87 and a standard deviation of 0.13.
Based on these data, the findings have important implications for various stakeholders in education, labor, and industry. For government agencies such as CHED, DTI, and DOLE, the general alignment in most disciplines indicates that current policies promoting employability skills—such as CHED’s Outcomes- Based Education (OBE) framework, DTI’s industry-academe collaboration initiatives, and DOLE’s job readiness programs—are producing positive results in cultivating strong work ethic among students. However, the misalignment in Marine Engineering suggests the need for targeted policy interventions and capacity-building efforts to address gaps in students’ self-awareness and confidence, possibly through better feedback systems or mentoring programs. For school administrators, the findings affirm the effectiveness of existing programs in most disciplines and highlight the need to review and strengthen student support services, performance evaluation, and student-industry engagement, particularly in programs with misaligned perceptions. For partner industries, HR professionals, supervisors, and school mentors, the alignment in perceptions reinforces the importance of their continued collaboration with schools to co-develop internship programs, workplace simulations, and performance-based assessments that shape work ethic early on. The misalignment in Marine Engineering, however, calls on industry partners to provide more structured feedback and mentorship to help students better internalize professional expectations. For teachers, the findings emphasize the need to engage in more reflective and student-centered evaluation practices, ensuring students are aware of and aligned with how their competencies are assessed, particularly in programs where teacher and student perceptions differ. For students, the findings serve as a call to actively seek feedback, reflect on their competencies honestly, and engage in opportunities that build their confidence and align their self-perception with workplace standards. Finally, for future researchers, the data provide a valuable foundation for exploring the causes of perception gaps, especially in fields like Marine Engineering, and for evaluating the effectiveness of educational strategies aimed at strengthening employability attributes such as work ethic.
Based on these data, the findings have important implications for both local and global aspects of education and workforce development. Locally, in the Philippine context, the alignment in most disciplines—such as Hospitality Management, Fisheries, Industrial Technology, and Education—suggests that national initiatives like CHED’s Outcomes-Based Education (OBE), DTI’s industry-academe collaboration efforts, and DOLE’s employability programs are effectively fostering strong work ethic among students that matches labor market expectations, thereby enhancing the relevance and quality of higher education.
However, the misalignment in Marine Engineering, where students perceive themselves as only sometimes competent while teachers and industry rate them highly, highlights a need for improved feedback systems, mentoring, and student self-awareness interventions in maritime programs. Globally, the overall alignment in work ethic supports the international competitiveness of Filipino graduates, particularly in fields like hospitality, education, and technical trades where work ethic is a critical employability trait. Yet, the disconnect in Marine Engineering could have broader global implications, as the Philippines is a leading provider of maritime professionals, and issues in student self-perception may impact global confidence in their readiness. Addressing this gap is essential not only for maintaining the country's global reputation in maritime labor but also for supporting the success and well-being of Filipino workers abroad. Thus, the findings underscore the need for continuous collaboration among educational institutions, industries, and government bodies to ensure that graduates possess both the competence and confidence required to meet local and global workforce demands.
Based on these details, the findings are highly relevant to Human Capital Theory, Signaling Theory, Technological Theory, key Philippine legal and policy frameworks, and the perspectives of Rosenberg (2012) and Majid (2022). Human Capital Theory emphasizes that education increases individual productivity and employability, which is affirmed by the alignment in work ethic across Hospitality Management, Fisheries, Industrial Technology, and Education—indicating that educational investments are translating into industry-valued competencies. However, the misalignment in Marine Engineering reveals a gap in this investment’s perceived effectiveness, suggesting the need for stronger student development and confidence-building efforts. Signaling Theory is evident where students’ perceived competence aligns with teacher and industry assessments, signaling job readiness; yet, in Marine Engineering, the students’ low self¬assessment weakens the signal, potentially affecting employment outcomes. Technological Theory underscores the role of education in responding to evolving workplace demands, and the observed alignment reflects institutions’ success in integrating 21st-century soft skills like work ethic—though the Marine Engineering gap indicates further attention is needed in nurturing adaptive, professional traits. These findings also support Republic Act No. 10968 (Philippine Qualifications Framework Act) by demonstrating how learning outcomes align with labor needs in most fields, while calling for targeted improvements in programs with misalignment. Likewise, Republic Act No. 11448 (Transnational Higher Education Act) emphasizes global competitiveness, especially critical in Marine Engineering where perception gaps may impact the international reputation of Filipino graduates. CHED Memorandum Order No. 13, s. 2016, promoting industry-academe collaboration, is validated where alignment exists, and its strengthened implementation is necessary where it does not. Lastly, the findings mirror the framework of Rosenberg (2012) and Majid (2022), who assert that employability is a shared responsibility among students, educators, industries, and policymakers—evident in the successful alignment across most disciplines and the need for collaborative action to address misalignment in Marine Engineering.
Overall, there is alignment in terms of Work Ethic across most disciplines—namely Hospitality Management, Fisheries, Industrial Technology, and Education—as the majority of students perceived themselves as always competent, and industry representatives or school mentors regarded work ethic as always necessary for students. However, in Marine Engineering, there is a clear misalignment, as students viewed themselves as only sometimes competent, while their teachers and industry representatives consistently rated them much higher, indicating a gap in self-perception and external evaluation.
2. Significant Differences in Employability Attributes
2.1. Basic Literacy and Numeracy Skills
The ANOVA on the differences in employability attributes in basic literacy and numeracy skills, as perceived by the respondent groups, is presented in Tables 44 to 48, which correspond to the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Table 4
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Basic Literacy and Numeracy Skills in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding basic literacy and numeracy skills required for the Hospitality Management program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding basic literacy and numeracy skills between at least two groups (F(2, 65) = 3.012, p = 0.56).
Since the overall ANOVA was not statistically significant (F(2, 65) = 3.012, p = 0.56), no post-hoc comparisons were conducted.
Table 5
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Basic Literacy and Numeracy Skills in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding basic literacy and numeracy skills required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding basic literacy and numeracy skills between at least two groups (F(2, 47) = 18.652, p = 0.000).
Tukey’s HSD test for multiple comparisons revealed statistically significant differences in the mean values of LNS between students and teachers (p = 0.000, 95% CI = [-1.4336, -0.4764]) as well as between students and industry partners (p = 0.000, 95% CI = [-1.5782, -0.4318]).
There was no statistically significant difference between teachers and industry partners (p = 0.984).
Table 6
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Basic Literacy and Numeracy Skills in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding basic literacy and numeracy skills required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding basic literacy and numeracy skills between at least two groups (F(2, 29) = 0.969, p = 0.391).
Since the overall ANOVA was not statistically significant (F(2, 29) = 0.969, p = 0.391), no post-hoc comparisons were conducted.
Table 7
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Basic Literacy and Numeracy Skills in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding basic literacy and numeracy skills required for the Industrial Technology program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding basic literacy and numeracy skills between at least two groups (F(2, 61) = 1.476, p = 0.237).
Since the overall ANOVA was not statistically significant (F(2, 61) = 1.476, p = 0.237), no post-hoc comparisons were conducted.
Table 8
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Basic Literacy and Numeracy Skills in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding basic literacy and numeracy skills required for the Education program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding basic literacy and numeracy skills between at least two groups (F(2, 54) = 1.335, p = 0.272).
Since the overall ANOVA was not statistically significant (F(2, 54) = 1.335, p = 0.272), no post-hoc comparisons were conducted.
2.2. Critical Thinking Skills
The ANOVA on the differences in employability attributes in critical thinking skills, as perceived by the respondent groups, is presented in Tables 49 to 53, which correspond to the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education. These tables offer a detailed breakdown of how critical thinking skills are perceived across the different programs, shedding light on any notable variations or trends that emerge within each group. By comparing the responses, we can better understand how each discipline values and develops these key employability attributes.
Table 9
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Critical Thinking Skills in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding critical thinking skills required for the Hospitality Management program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding critical thinking skills between at least two groups (F(2, 65) = 1.490, p = 0.233).
Since the overall ANOVA was not statistically significant (F(2, 65) = 1.490, p = 0.233), no post-hoc comparisons were conducted.
Table 10
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Critical Thinking Skills in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding critical thinking skills required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding critical thinking skills between at least two groups (F(2, 47) = 13.703, p = 0.000).
Tukey’s HSD test for multiple comparisons revealed statistically significant differences in the mean values of CTS between students and teachers (p = 0.001, 95% CI = [-1.4754, -0.3718]) as well as between students and industry partners (p = 0.001, 95% CI = [-1.6818, -0.3599]).
There was no statistically significant difference between teachers and industry partners (p = 0.955, 95% CI = [-0.9108, 0.7164]).
Table 11
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Critical Thinking Skills in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding critical thinking skills required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding critical thinking skills between at least two groups (F(2, 29) = 1.609, p = 0.217).
Since the overall ANOVA was not statistically significant (F(2, 29) = 1.609, p = 0.217), no post-hoc comparisons were conducted.
Table 12
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Critical Thinking Skills in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding critical thinking skills required for the Industrial Technology program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding critical thinking skills between at least two groups (F(2, 61) = 0.019, p = 0.981).
Since the overall ANOVA was not statistically significant (F(2, 61) = 0.019, p = 0.981), no post-hoc comparisons were conducted.
Table 13
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Critical Thinking Skills in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding critical thinking skills required for the Education program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding critical thinking skills between at least two groups (F(2, 54) = 1.918, p = 0.157).
Since the overall ANOVA was not statistically significant (F(2, 54) = 1.918, p = 0.157), no post-hoc comparisons were conducted.
1.3. Leadership Skills
The ANOVA on the differences in employability attributes in leadership skills, as perceived by the respondent groups, is presented in Tables 54 to 58, which correspond to the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Table 14
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Leadership Skills in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding leadership skills required for the Hospitality Management program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding leadership skills between at least two groups (F(2, 65) = 1.022, p = 0.366).
Since the overall ANOVA was not statistically significant (F(2, 65) = 1.022, p = 0.366), no post-hoc comparisons were conducted.
Table 15
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Leadership Skills in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding leadership skills required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding leadership skills between at least two groups (F(2, 47) = 8.341, p = 0.001).
Tukey’s HSD test for multiple comparisons revealed a statistically significant difference in the mean values of LS between students and industry partners (p = 0.001, 95% CI = [-1.4450, -0.3350]).
There was no statistically significant differences were found between students and teachers (p = 0.220, 95% CI = [-0.7867, 0.1400]) or between teachers and industry partners (p = 0.122, 95% CI = [-1.2499, 0.1165]).
Table 16
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Leadership Skills in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding leadership skills required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding leadership skills between at least two groups (F(2, 29) = 0.241, p = 0.787).
Since the overall ANOVA was not statistically significant (F(2, 29) = 0.241, p = 0.787), no post-hoc comparisons were conducted.
Table 17
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Leadership Skills in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding leadership skills required for the Industrial Technology program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding leadership skills between at least two groups (F(2, 61) = 0.697, p = 0.502).
Since the overall ANOVA was not statistically significant (F(2, 61) = 0.697, p = 0.502), no post-hoc comparisons were conducted.
Table 18
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Leadership Skills in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding leadership skills required for the Education program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding leadership skills between at least two groups (F(2, 54) = 3.898, p = 0.026).
Tukey’s HSD test for multiple comparisons revealed that there were no statistically significant differences in the mean values of LS among the three groups. The comparison between students and industry partners approached significance (p = 0.079, 95% CI = [-0.6723, 0.0295]), while no significant differences were found between students and teachers (p = 0.109, 95% CI = [-0.8362, 0.0662]) or between teachers and industry partners (p = 0.954, 95% CI = [-0.5867, 0.4594]).
1.4. Management Skills
The ANOVA on the differences in employability attributes in management skills, as perceived by the respondent groups, is presented in Tables 59 to 63, which correspond to the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education. By analyzing these tables, we can see how each program's participants—students, teachers, and industry professionals—differ in their views on what management skills are most important for employability.
Table 19
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Management Skills in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding management skills required for the Hospitality Management program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding leadership skills between at least two groups (F(2, 65) = 0.694, p = 0.503).
Since the overall ANOVA was not statistically significant (F(2, 65) = 0.694, p = 0.503), no post-hoc comparisons were conducted.
Table 20
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Management Skills in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding management skills required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding management skills between at least two groups (F(2, 47) = 13.421, p = 0.000).
Tukey’s HSD test for multiple comparisons revealed statistically significant differences in the mean values of MS between students and teachers (p = 0.009, 95% CI = [-1.2053, -0.1447]) and between students and industry partners (p = 0.000, 95% CI = [-1.8102, -0.5398]).
There was no statistically significant difference between teachers and industry partners (p = 0.278, 95% CI = [-1.2819, 0.2819]).
Table 21
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Management Skills in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding management skills required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding management skills between at least two groups (F(2, 29) = 1.722, p = 0.196).
Since the overall ANOVA was not statistically significant (F(2, 29) = 1.722, p = 0.196), no post-hoc comparisons were conducted.
Table 22
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Management Skills in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding management skills required for the Industrial Technology program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding management skills between at least two groups (F(2, 61) = 1.423, p = 0.249).
Since the overall ANOVA was not statistically significant (F(2, 61) = 1.423, p = 0.249), no post-hoc comparisons were conducted.
Table 23
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Management Skills in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding management skills required for the Education program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding management skills between at least two groups (F(2, 54) = 3.386, p = 0.041).
Tukey’s HSD test for multiple comparisons revealed a statistically significant difference in the mean values of MS between students and industry partners (p = 0.032, 95% CI = [-0.8219, -0.0315]).
There were no statistically significant differences between students and teachers (p = 0.905, 95% CI = [-0.5978, 0.4186]) or between teachers and industry partners (p = 0.359, 95% CI = [-0.9262, 0.2520]).
1.5. Interpersonal Skills
The ANOVA on the differences in employability attributes in interpersonal skills, as perceived by the respondent groups, is presented in Tables 64 to 68, which correspond to the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Table 24
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Interpersonal Skills in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding interpersonal skills required for the Hospitality Management program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding interpersonal skills between at least two groups (F(2, 65) = 0.338, p = 0.714).
Since the overall ANOVA was not statistically significant (F(2, 65) = 0.338, p = 0.714), no post-hoc comparisons were conducted.
Table 25
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Interpersonal Skills in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding interpersonal skills required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding interpersonal skills between at least two groups (F(2, 47) = 19.534, p = 0.000).
Tukey’s HSD test for multiple comparisons revealed statistically significant differences in the mean values of IS between students and teachers (p = 0.000, 95% CI = [-1.1482, -0.3407]) and between students and industry partners (p = 0.000, 95% CI = [-1.4503, -0.4830]).
There was no statistically significant difference between teachers and industry partners (p = 0.641, 95% CI = [-0.8176, 0.3731]).
Table 26
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Interpersonal Skills in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding interpersonal skills required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding interpersonal skills between at least two groups (F(2, 29) = 1.101, p = 0.346).
Since the overall ANOVA was not statistically significant (F(2, 29) = 1.101, p = 0.346), no post-hoc comparisons were conducted.
Table 27
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Interpersonal Skills in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding interpersonal skills required for the Industrial Technology program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding interpersonal skills between at least two groups (F(2, 61) = 0.564, p = 0.572).
Since the overall ANOVA was not statistically significant (F(2, 61) = 0.564, p = 0.572), no post-hoc comparisons were conducted.
Table 28
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Interpersonal Skills in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding interpersonal skills required for the Education program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding interpersonal skills between at least two groups (F(2, 54) = 2.950, p = 0.061).
Since the overall ANOVA was not statistically significant (F(2, 54) = 2.950, p = 0.061), no post-hoc comparisons were conducted.
1.6. Information Technology Skills
The ANOVA on the differences in employability attributes in information technology skills, as perceived by the respondent groups, is presented in Tables 69 to 73, which correspond to the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Table 29
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Information Technology Skills in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding information technology skills required for the Hospitality Management program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding information technology skills between at least two groups (F(2, 65) = 2.020, p = 0.141).
Since the overall ANOVA was not statistically significant (F(2, 65) = 2.020, p = 0.141), no post-hoc comparisons were conducted.
Table 30
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Information Technology Skills in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding information technology skills required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding information technology skills between at least two groups (F(2, 47) = 17.483, p = 0.000).
Tukey’s HSD test for multiple comparisons revealed statistically significant differences in the mean values of ITS between students and teachers (p = 0.002, 95% CI = [-1.0748, -0.2229]) and between students and industry partners (p = 0.000, 95% CI = [-1.5638, -0.5434]).
There was no statistically significant difference between teachers and industry partners (p = 0.273, 95% CI = [-1.0328, 0.2233]).
Table 31
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Information Technology Skills in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding information technology skills required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding information technology skills between at least two groups (F(2, 29) = 0.885, p = 0.423).
Since the overall ANOVA was not statistically significant (F(2, 29) = 0.885, p = 0.423), no post-hoc comparisons were conducted.
Table 32
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Information Technology Skills in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding information technology skills required for the Industrial Technology Skills program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding information technology skills between at least two groups (F(2, 61) = 0.045, p = 0.956).
Since the overall ANOVA was not statistically significant (F(2, 61) = 0.045, p = 0.956), no post-hoc comparisons were conducted.
Table 33
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Information Technology Skills in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding information technology skills required for the Education program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding information technology skills between at least two groups (F(2, 54) = 7.114, p = 0.002).
Tukey’s HSD test for multiple comparisons revealed a statistically significant difference in the mean values of ITS between students and industry partners (p = 0.001, 95% CI = [-1.0423, -0.2214]).
There were no statistically significant differences between students and teachers (p = 0.405, 95% CI = [-0.8111, 0.2445]) or between teachers and industry partners (p = 0.362, 95% CI = [-0.9603, 0.2634]).
1.7. Systems Thinking Skills
The ANOVA on the differences in employability attributes in systems thinking skills, as perceived by the respondent groups, is presented in Tables 74 to 78, which correspond to the five academic programs: Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education.
Table 34
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Systems Thinking Skills in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding systems thinking skills required for the Hospitality Management program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding systems thinking skills between at least two groups (F(2, 65) = 3.406, p = 0.039).
Tukey’s HSD test for multiple comparisons revealed a statistically significant difference in the mean values of STS between students and industry partners (p = 0.033, 95% CI = [-0.7415, -0.0260]).
There were no statistically significant differences between students and teachers (p = 0.991, 95% CI = [-0.6211, 0.5592]) or between teachers and industry partners (p = 0.366, 95% CI = [-0.9736, 0.2680]).
Table 35
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Systems Thinking Skills in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding systems thinking skills required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding systems thinking skills between at least two groups (F(2, 47) = 12.777, p = 0.000).
Tukey’s HSD test for multiple comparisons revealed statistically significant differences in the mean values of STS between students and teachers (p = 0.007, 95% CI = [-1.3024, -0.1833]) and between students and industry partners (p = 0.000, 95% CI = [-1.8417, -0.5011]).
There was no statistically significant difference between teachers and industry partners (p = 0.426, 95% CI = [-1.2536, 0.3965]).
Table 36
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Systems Thinking Skills in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding systems thinking skills required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding systems thinking skills between at least two groups (F(2, 29) = 1.985, p = 0.156).
Since the overall ANOVA was not statistically significant (F(2, 29) = 1.985, p = 0.156), no post-hoc comparisons were conducted.
Table 37
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Systems Thinking Skills in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding systems thinking skills required for the Industrial Technology program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding systems thinking skills between at least two groups (F(2, 61) = 0.274, p = 0.762).
Since the overall ANOVA was not statistically significant (F(2, 61) = 0.274, p = 0.762), no post-hoc comparisons were conducted.
Table 38
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Systems Thinking Skills in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding systems thinking skills required for the Education program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding systems thinking skills between at least two groups (F(2, 54) = 4.824, p = 0.012).
Tukey’s HSD test for multiple comparisons revealed a statistically significant difference in the mean values of STS between students and industry partners (p = 0.010, 95% CI = [-0.9987, -0.1162]).
There were no statistically significant differences between students and teachers (p = 0.508, 95% CI = [-0.8305, 0.3043]) or between teachers and industry partners (p = 0.531, 95% CI = [-0.9522, 0.3634]).
1.8. Work Ethics
The ANOVA on the differences in employability attributes in work ethics, as perceived by the respondent groups, is presented in Tables 79 to 83, which correspond to the five academic programs: Hospitality Management, Marine
Engineering, Fisheries, Industrial Technology, and Education.
Table 39
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Systems Work Ethics in Hospitality Management as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding work ethics required for the Hospitality Management program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding work ethics between at least two groups (F(2, 65) = 1.374, p = 0.260).
Since the overall ANOVA was not statistically significant (F(2, 65) = 1.374, p = 0.260), no post-hoc comparisons were conducted.
Table 40
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Work Ethics in Marine Engineering as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
*. The mean difference is significant at the 0.05 level.
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding work ethics required for the Marine Engineering program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding work ethics between at least two groups (F(2, 47) = 10.611, p = 0.000).
Tukey’s HSD test for multiple comparisons revealed statistically significant differences in the mean values of WE between students and teachers (p = 0.005, 95% CI = [-1.5121, -0.2426]) and between students and industry partners (p = 0.003, 95% CI = [-1.8639, -0.3433]).
There was no statistically significant difference between teachers and industry partners (p = 0.829, 95% CI = [-1.1621, 0.7097]).
Table 41
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Work Ethics in Fisheries as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding work ethics required for the Fisheries program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding work ethics between at least two groups (F(2, 29) = 0.724, p = 0.494).
Since the overall ANOVA was not statistically significant (F(2, 29) = 0.724, p = 0.494), no post-hoc comparisons were conducted.
Table 42
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Work Ethics in Industrial Technology as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding work ethics required for the Industrial Technology program.
A one-way ANOVA revealed that there was a statistically significant difference in responses regarding work ethics between at least two groups (F(2, 61) = 3.471, p = 0.037).
Tukey’s HSD test for multiple comparisons revealed a statistically significant difference in the mean values of WE between teachers and industry partners (p = 0.028, 95% CI = [-1.0903, -0.0502]).
There were no statistically significant differences between students and teachers (p = 0.101, 95% CI = [-0.8867, 0.0622]) or between students and industry partners (p = 0.498, 95% CI = [-0.4932, 0.1773]).
Table 43
One-Way Analysis of Variance on the Differences in Employability Attributes in Terms of Work Ethics in Education as Perceived by the Respondent Groups
Illustrations are not included in the reading sample
A one-way ANOVA was performed to compare the effect of respondent type (students, teachers, and industry professionals) on their responses regarding work ethics required for the Education program.
A one-way ANOVA revealed that there was not a statistically significant difference in responses regarding work ethics between at least two groups (F(2, 54) = 2.467, p = 0.094).
Since the overall ANOVA was not statistically significant (F(2, 54) = 2.467, p = 0.094), no post-hoc comparisons were conducted.
Chapter 3 SUMMARY OF FINDINGS, CONCLUSION, AND RECOMMENDATIONS
This chapter presents a summary of the results from the survey. After thoroughly considering the findings, conclusions are drawn, followed by recommendations to help both nurturing agents address the job mismatch issue and provide suggestions to help graduating students secure employment immediately after graduation.
SUMMARY OF FINDINGS
This study gathered data from three key groups: students, teachers, and HR professionals (or school mentors), in order to assess their perspectives on the importance of seven skills: basic literacy and numeracy skills, critical thinking skills, leadership skills, management skills, interpersonal skills, information technology skills, and systems thinking skills, as well as core values, including work ethic. The five following findings include:
1. General Alignment with Notable Areas of Misalignment. Based on the data, misalignment is evident primarily in Marine Engineering across all assessed skills, including work ethic, systems thinking, critical thinking, leadership, management, interpersonal, information technology, and basic literacy and numeracy skills, where students consistently rated themselves as only sometimes competent, while teachers and industry representatives rated them as always competent or necessary. In the Fisheries discipline, misalignment is also observed in critical thinking skills, where students perceived themselves as sometimes competent, teachers rated them as always competent, and industry viewed them as only sometimes necessary. Additionally, management and interpersonal skills in Fisheries showed misalignment, as students and teachers considered them always competent, while industry representatives regarded them as only sometimes necessary. These discrepancies highlight significant gaps between student self-perceptions and the expectations of educators and industry stakeholders.
2. Mismatch between Industry Expectations and Student Self-Perception in Employability Skills. Industry stakeholders consistently view employability skills as necessary, but student self-perception does not always reflect this, especially in technical fields like Marine Engineering. The data reveals a consistent trend: industry stakeholders across all disciplines—particularly in technical fields like Marine Engineering—regard employability skills such as work ethic, systems thinking, critical thinking, leadership, management, interpersonal communication, and information technology skills as always necessary for students to succeed in the workplace. However, Marine Engineering students, in particular, do not perceive themselves as possessing these competencies to the same degree. In all assessed areas, they consistently rated themselves as only sometimes competent, showing a lack of confidence or a disconnect in understanding how their abilities align with professional standards.
3. Inconsistent Integration of Critical Soft Skills in Academic Programs. Soft skills such as leadership, communication, and critical thinking are often undervalued or inconsistently developed across disciplines, even though industries rate them as highly necessary. The data highlights that soft skills such as leadership, communication (interpersonal skills), and critical thinking are not consistently integrated or developed across disciplines, even though industries rate them as highly necessary for workplace success. This inconsistency is most prominent in Marine Engineering, where students rated themselves as only sometimes competent across all key employability areas—including leadership, critical thinking, and interpersonal skills—while both teachers and industry representatives rated them as always competent or necessary. This significant gap points to a possible lack of emphasis on the practical development of these soft skills within the curriculum, or a failure to help students recognize and internalize their own capabilities. In Fisheries, a similar pattern emerges. Students rated themselves as sometimes competent in critical thinking, while teachers considered them always competent, and industry viewed the skill as only sometimes necessary, revealing confusion or inconsistency about its importance and expected performance. Moreover, in management and interpersonal skills, students and teachers aligned positively, yet industry stakeholders rated the necessity of these skills lower, suggesting a mismatch in how schools and industries prioritize or understand soft skill development.
4. Gaps in Student Assessment Linked to Limited School-Industry Communication. Lack of sustained collaboration and communication between schools and industries results in inconsistent evaluation of student competencies and expectations. The data highlights that limited and inconsistent collaboration between schools and industries contributes to gaps in student competency assessments. In Marine Engineering, students consistently rated themselves as only sometimes competent, while teachers and industry rated them much higher, revealing a disconnect in feedback and expectations. Similarly, in Fisheries, mismatches in evaluating critical thinking, management, and interpersonal skills suggest unclear alignment between academic preparation and industry needs. These discrepancies point to the need for sustained school-industry communication to ensure that student assessments accurately reflect real-world competency requirements.
5. Delayed Industry Exposure Hinders Student Readiness and School-to- Work Transition. Late exposure of students to real-world industry practices limits their ability to accurately assess their own readiness and hinders smoother transition from school to work. The data reveals that students, particularly in Marine Engineering, consistently perceive themselves as only sometimes competent across essential employability skills such as work ethic, critical thinking, leadership, and IT skills, while teachers and industry stakeholders assess them as always competent or their skills as always necessary. This persistent misalignment suggests that students may lack firsthand experience with real-world industry expectations, limiting their ability to accurately evaluate their own readiness for the workforce. In Fisheries, similar gaps appear in critical thinking, management, and interpersonal skills, where student and teacher ratings align but differ from industry assessments.
These patterns indicate that late or insufficient exposure to industry practices may prevent students from developing the confidence, awareness, and adaptability needed for a smoother transition from school to work. Early and structured immersion in actual industry settings—such as through internships, mentoring, or simulation-based learning—can bridge this gap, helping students calibrate their self-assessments and prepare more effectively for professional environments.
CONCLUSIONS
Based on a careful analysis of the data, the following conclusions are drawn to address the study's focus on aligning employability attributes with industry requirements.
As to the null hypothesis—which states that there is no significant difference in the perception of employability attributes among the respondent groups in the Hospitality Management, Marine Engineering, Fisheries, Industrial Technology, and Education programs—the results indicate that the null hypothesis should be rejected in four programs and for specific attributes, as the p-values fall below the 0.05 threshold. In the Hospitality Management program, Systems Thinking Skills had a p-value of 0.039, indicating a significant difference in perception among the groups. In the Marine Engineering program, all eight employability attributes yielded significant differences, with the following p- values: 0.000 for Basic Literacy and Numeracy Skills, 0.000 for Critical Thinking Skills, 0.001 for Leadership Skills, 0.000 for Management Skills, 0.000 for Interpersonal Skills, 0.000 for Information Technology Skills, 0.000 for Systems Thinking Skills, and 0.000 for Work Ethic. The Industrial Technology program also showed significant difference for Work Ethic with a p-value of 0.0375. Meanwhile, in the Education program, significant differences were found in Leadership Skills (p = 0.026), Management Skills (p = 0.041), Information Technology Skills (p = 0.002), and Systems Thinking Skills (p = 0.012). These results clearly indicate that the perceptions of the respondent groups vary significantly in these programs and attributes, thus leading to the rejection of the null hypothesis in those areas.
On the other hand, the null hypotheses that fail to be rejected—because the p-values are above the threshold of 0.05—correspond to four programs and specific employability attributes. In the Hospitality Management program, the following attributes did not show significant differences: Basic Literacy and Numeracy Skills (p = 0.056), Critical Thinking Skills (p = 0.233), Leadership Skills (p = 0.366), Management Skills (p = 0.503), Interpersonal Skills (p = 0.714), Information Technology Skills (p = 0.141), and Work Ethic (p = 0.260). In the Fisheries program, the p-values were: 0.391 for Basic Literacy and Numeracy Skills, 0.217 for Critical Thinking Skills, 0.787 for Leadership Skills, 0.196 for Management Skills, 0.346 for Interpersonal Skills, 0.423 for Information Technology Skills, 0.156 for Systems Thinking Skills, and 0.494 for Work Ethic. The Industrial Technology program showed no significant differences for the following: Basic Literacy and Numeracy Skills (p = 0.237), Critical Thinking Skills (p = 0.981), Leadership Skills (p = 0.502), Management Skills (p = 0.249), Interpersonal Skills (p = 0.572), Information Technology Skills (p = 0.956), and Systems Thinking Skills (p = 0.762). Meanwhile, in the Education program, no significant differences were found in Basic Literacy and Numeracy Skills (p = 0.272), Critical Thinking Skills (p = 0.157), Interpersonal Skills (p = 0.061), and Work Ethic (p = 0.094). These p-values indicate that the respondent groups had relatively similar perceptions of these employability attributes in the respective programs.
The Signalling Theory posits that graduates signal their capabilities to prospective employers through the knowledge and skills acquired during their education. It is known if students really signal their capabilities through the programs that do not reject the null hypothesis. The Hospitality Management includes Basic Literacy and Numeracy Skills, Critical Thinking Skills, Leadership Skills, Management Skills, Interpersonal Skills, Information Technology Skills, and Work Ethic; Fisheries includes Basic Literacy and Numeracy Skills, Critical Thinking Skills, Leadership Skills, Management Skills, Interpersonal Skills, Information Technology Skills, Systems Thinking Skills, and for Work Ethic; Industrial Technology includes Basic Literacy and Numeracy Skills, Critical Thinking Skills, Leadership Skills, Management Skills, Interpersonal Skills, Information Technology Skills, and Systems Thinking Skills; and Education includes Basic Literacy and Numeracy Skills, Critical Thinking Skills, Interpersonal Skills, and Work Ethic.
The Human Capital Theory says that education increases a person’s productivity and helps them earn more in the labor market by building valuable skills. This idea holds true, but the study shows that some academic programs may need better alignment with what employers expect. For instance, we have the Hospitality Management’s Systems Thinking Skills; Marine Engineering’s Basic Literacy and Numeracy Skills, Critical Thinking Skills, for Leadership Skills, Management Skills, Interpersonal Skills, Information Technology Skills, Systems Thinking Skills, and Work Ethic; Industrial Technology’s Work Ethic; and the Education’s Leadership Skills, Management Skills, Information Technology Skills, and Systems Thinking Skills. These results suggest that while the human capital theory remains valid, some fields may benefit from more targeted training or adjustments to better meet labor market needs.
The Technological Theory explains how fast-changing technology creates new job demands that often require highly trained and specialized workers. This idea remains true, and the study shows both strengths and areas that need improvement when it comes to preparing students for these changes. This is true for programs that failed to reject the null hypothesis, as mentioned above, and areas that need improvement for those that rejected the null hypothesis.
To address these issues, schools and industries need to work closely together. This partnership should go beyond job placements and focus on regular communication, joint curriculum reviews, and continuous updates to better match industry needs. By building long-term, open partnerships, both schools and industries can better prepare students for the workforce. This approach will help students connect theoretical knowledge with practical skills, making them more employable.
RECOMMENDATIONS
In light of the study’s five key findings and the relevant legal frameworks— such as Republic Act No. 10968, Republic Act No. 11448, and CHED Memorandum Order No. 13, Series of 2016—the following concrete recommendations are proposed to bridge the gap between education and industry requirements. These recommendations directly address the identified issues: General Alignment with Notable Areas of Misalignment, Mismatch between Industry Expectations and Student Self-Perception in Employability Skills, Inconsistent Integration of Critical Soft Skills in Academic Programs, Gaps in Student Assessment Linked to Limited School-Industry Communication, and Delayed Industry Exposure Hinders Student Readiness and School-to-Work Transition. The following recommendations include:
1. Teachers and industries can maintain competence through continuous professional development, staying updated on industry trends, and collaborating to review and improve the curriculum. Regular feedback from companies and joint evaluations with CHED will help keep programs aligned with labor market needs.
2. It is recommended that schools address the discrepancies and gaps between student self-assessments, teacher evaluations, and industry expectations by implementing regular calibration sessions and feedback mechanisms to better align perceptions and competencies.
3. Since Marine Engineering students do not perceive themselves as possessing employability skills to the same degree, programs should provide targeted skills workshops, mentoring, and practical industry exposure to help students recognize and develop the competencies expected by employers.
4. Academic institutions should integrate essential soft skills—literacy, numeracy, communication, leadership, critical thinking, management, and work ethic—alongside technical competencies. Collaboration with industry, as promoted by CHED Memorandum Order No. 13, ensures graduates are well-rounded and prepared for workplace demands.
5. Regular communication between schools and industry partners should be institutionalized to address misalignments in student and teacher evaluations versus industry expectations. CHED and related agencies can support this through industry-academe councils, feedback sessions, and joint curriculum planning to ensure programs remain relevant to workplace needs.
6. Mismatches in evaluating critical thinking, management, and interpersonal skills in Fisheries indicate unclear alignment with industry needs. This can be addressed through regular communication with industry partners, early student exposure to workplaces, and joint curriculum planning to ensure relevant instruction.
Implementing these recommendations will help educational institutions align with industry needs (RA 10968; RA 11448; CHED MO No. 13), enhance graduate employability, and strengthen school-industry collaboration to meet evolving workforce demands.
Chapter 4 OUTPUT OF THE STUDY
AN ACTION PLAN FOR ENHANCING THE ALIGNMENT BETWEEN
GRADUATING STUDENTS' EMPLOYABILITY ATTRIBUTES AND INDUSTRY
REQUIREMENTS
WILSON A. JERUSALEM
May 2025
I. Rationale
These days, several students graduate deprived of all the skills employers are in the hunt for—and that is becoming a real concern. As job markets continue to change, schools need to keep up by bringing up-to-date what and how they teach. This action plan is all about aiding schools and industries work more closely together so students are better equipped for the workforce. It focuses on making sure what is imparted in classrooms matches what firms really need. The outcomes from this study, together with national policies like Republic Act No. 10968 (Philippine Qualifications Framework), Republic Act No. 11448 (Industry and Education Partnership), and CHED Memorandum Order No. 13, Series of 2016, altogether indicate one thing: collaboration is fundamental. This plan lays out simple, doable steps to support students build the right skills and make it easier for employers to look for job-ready graduates.
II. Objectives
The aim of improving the alignment between graduating students' employability attributes and industry requirements is for the subsequent motives:
1. To make stronger Educational and Industry Partnerships;
2. To encourage Lifelong Learning and Skills Development;
3. To Incorporate Soft Skills and Technical Competencies;
4. To reinforce Continuous Communication between Schools and Industries;
5. To provide students early industry exposure; and
6. To implement government licensing conditions for industries, requiring them to form formal partnerships with educational institutions to align workforce skills with industry demands.
III. Scheme and Implementation
The succeeding outlines the approach and steps for implementation:
1. The researcher recommends establishing advisory boards with industry and academic partners to frequently update the curriculum, improve courses that align with industry needs, and commend new programs through partnerships, following CHED guidelines, with yearly reviews for ongoing significance.
2. The researcher recommends offering flexible learning options aligned with industry needs and encouraging employers to sponsor training programs in partnership with educational institutions, with accountability shared by institutions, employers, and government bodies for instant execution and updates.
3. The researcher recommends rereading and going over curricula to include soft skills training together with technical courses, executing practical projects to improve these skills, with educational institutions, faculty, and industry specialists accountable for updates within 6 months and continuous monitoring afterwards.
4. The researcher recommends consistent meetings and digital platforms for industry and academic institutions to exchange visions and cooperate with each other on curriculum updates, with quarterly consultations and workshops for ongoing execution.
5. The researcher recommends developing structured internship, apprenticeship, and fieldwork programs for early industry exposure, reassuring companies to be responsible for mentorship aligned with workforce needs, with ongoing development and direct execution.
6. The researcher recommends promoting for policy improvements that necessitate industries to form partnerships with educational institutions before getting a government license, in partnership with DTI, DOLE, and other stakeholders, with a 1-2 year timeline for promotion and execution.
AN ACTION PLAN FOR ENHANCING THE ALIGNMENT BETWEEN GRADUATING STUDENTS' EMPLOYABILITY ATTRIBUTES AND INDUSTRY REQUIREMENTS
Illustrations are not included in the reading sample
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APPENDICES
Appendix A
Transmittal Letter for the CTU-CARMEN CAMPUS DIRECTOR
This page is nor part of the publication due to copyright issues.
Appendix B
Transmittal Letter for the Schools Division Superintendent of Cebu, Region VII
This page is nor part of the publication due to copyright issues.
Appendix C
Transmittal Letter for the Supervisors of the Public Schools District of Carmen
This page is nor part of the publication due to copyright issues.
Appendix D
Transmittal Letter for CTU-Carmen's Partnered Industries and Schools
This page is nor part of the publication due to copyright issues.
Appendix E
Transmittal Letter for the Teachers and Students of CTU-Carmen Campus
This page is nor part of the publication due to
copyright issues.
Appendix F
Questionnaire for CTU-Carmen Campus Graduating Students
PART 1. RESPONDENT’S PROFILE
Direction: Please fill out the required information.
Name :
Age :
Gender :
Course :
Desired Career :
PART 2. ATTRIBUTES OF GRADUATING STUDENTS NECESSARY FOR
APPLYING FOR JOBS IN INDUSTRIES
Directions: Please answer the following questions by marking with a check (✓) the box that corresponds to your answer. The items listed are attributes of CTU- Carmen Campus graduating students that need to be acquired in school before applying forjobs in industries.
Note: This list of survey questions, from 1 to 47, is taken verbatim from an article by Stuart Rosenberg (Rosenberg, 2012).
ITEM NO. 1. Basic Literacy and Numeracy Skills
1. I can perform basic computations and approach practical problems with different mathematical techniques.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
2. I can organize basic ideas; communicate orally.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
3. I can organize basic thoughts, ideas, and messages in writing; create documents such as letters, directions, manuals, reports, graphs, and flow charts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
4. I can receive, attend to, interpret, and respond to basic verbal messages/cues.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
5. I have the ability to locate, understand, and interpret basic written information in documents such as manuals, graphs, and schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 2. Critical Thinking Skills
6. I can generate new ideas.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
7. I can specify goals and constraints, generate alternatives, consider risks, and evaluate and choose the best alternative.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
8. I can recognize problems and devise and implement a plan of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
9. I can organize and process symbols, pictures, graphs, objects and other information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
10. I can acquire and apply new knowledge and skills from multiple print and digital sources.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
11. I can discover a rule or principle underlying the relationship between two or more objects and apply it when solving a problem.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 3. Leadership Skills
12. I can exert a high level of effort and persevere toward goal attainment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
13. I believe in my own self-worth and maintain a positive view of myself.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
14. I can set personal goals, monitor progress, exhibit self-control and take responsibility for my actions.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
15. I can choose ethical courses of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
16. I can communicate ideas to justify positions, persuade and convince others, and responsibly challenge existing procedures and policies.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 4. Management Skills
17. I can select goal-relevant activities, rank them, allocate time, and prepare and follow schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
18. I can use or prepare budgets, make forecasts, keep records, and make adjustments to meet objectives.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
19. I can acquire, store, allocate, and use materials or space efficiently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
20. I can assess skills and distribute work accordingly, evaluate performance and provide feedback.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 5. Interpersonal Skills
21. I contribute to group efforts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
22. I help others to learn.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
23. I work to satisfy customers’ expectations. [ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
24. I work toward agreements involving the exchange of resources, and resolve divergent interests.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
25. I work well with men and women from diverse backgrounds.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
26. I can demonstrate understanding, friendliness, adaptability, empathy, and politeness in group settings.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 6. Information Technology Skills
27. I can choose procedures, tools or equipment including computers and related technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
28. I understand overall intent and proper procedures for the setup and operation of equipment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
29. I can prevent, identify, or solve problems with equipment, including computers and other technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
30. I can identify the need for data, obtain data from existing sources or create it, and evaluate its relevance and accuracy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
31. I can organize, process, and maintain written or computerized records and other forms of information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
32. I can select and analyze information and communicate the results to others in oral, written, graphic, pictorial or multimedia methods.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
33. I can employ computers to acquire, organize, analyze and communicate information, and demonstrate some proficiency with standard software.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 7. Systems Thinking Skills
34. I know how social, organizational, and technological systems work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
35. I can distinguish trends, and predict the impacts of actions on system operations.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
36. I make suggestions to modify existing systems to improve products and services and develop new or alternative systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
37. I know how to assess the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
38. I know how to recognize the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 39. I understand the interaction and interrelationship of systems within an organization.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 40. I understand the interaction and interrelationship of systems in a global economy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 8. Work Ethic
41. I attend required organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 42. I am on time for organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
43. I achieve organizational and personal goals independently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
44. I complete work on-time.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
45. I understand organizational protocols and procedures.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
46. I demonstrate a positive attitude at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
47. I am dependable at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
Appendix G
Questionnaires for CTU-Carmen Campus Teachers
PART 1. RESPONDENT’S PROFILE
Direction: Please fill out the required information.
Name :
Age :
Gender :
Academic Discipline:
PART 2. ATTRIBUTES OF GRADUATING STUDENTS NECESSARY FOR APPLYING FOR JOBS IN INDUSTRIES
Directions: Please answer the following questions by marking (✓) the box that corresponds to your answer. The items listed below are attributes of CTU- Carmen Campus graduating students that are necessary to acquire before applying for jobs in the industry.
Note: This list of survey questions (1 to 47) is taken verbatim from an article by Stuart Rosenberg (Rosenberg, 2012), with the original subject "I" changed to "Our Graduating Students."
ITEM NO. 1. Basic Literacy and Numeracy Skills
1. Our Graduating Students can perform basic computations and approach practical problems with different mathematical techniques.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
2. Our Graduating Students can organize basic ideas; communicate orally.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
3. Our Graduating Students can organize basic thoughts, ideas, and messages in writing; create documents such as letters, directions, manuals, reports, graphs, and flow charts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
4. Our Graduating Students can receive, attend to, interpret, and respond to basic verbal messages/cues.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
5. Our Graduating Students have the ability to locate, understand, and interpret basic written information in documents such as manuals, graphs, and schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 2. Critical Thinking Skills
6. Our Graduating Students can generate new ideas.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
7. Our Graduating Students can specify goals and constraints, generate alternatives, consider risks, and evaluate and choose the best alternative.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
8. Our Graduating Students can recognize problems and devise and implement a plan of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
9. Our Graduating Students can organize and process symbols, pictures, graphs, objects and other information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
10. Our Graduating Students can acquire and apply new knowledge and skills from multiple print and digital sources.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
11. Our Graduating Students can discover a rule or principle underlying the relationship between two or more objects and apply it when solving a problem.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 3. Leadership Skills
12. Our Graduating Students can exert a high level of effort and persevere toward goal attainment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
13. Our Graduating Students believe in my own self-worth and maintain a positive view of myself.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
14. Our Graduating Students can set personal goals, monitor progress, exhibit self-control and take responsibility for my actions.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
15. Our Graduating Students can choose ethical courses of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
16. Our Graduating Students can communicate ideas to justify positions, persuade and convince others, and responsibly challenge existing procedures and policies.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 4. Management Skills
17. Our Graduating Students can select goal-relevant activities, rank them, allocate time, and prepare and follow schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
18. Our Graduating Students can use or prepare budgets, make forecasts, keep records, and make adjustments to meet objectives.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
19. Our Graduating Students can acquire, store, allocate, and use materials or space efficiently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
20. Our Graduating Students can assess skills and distribute work accordingly, evaluate performance and provide feedback.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 5. Interpersonal Skills
21. Our Graduating Students contribute to group efforts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
22. Our Graduating Students help others to learn.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
23. Our Graduating Students work to satisfy customers’ expectations.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
24. Our Graduating Students work toward agreements involving the exchange of resources, and resolve divergent interests.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
25. Our Graduating Students work well with men and women from diverse backgrounds.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
26. Our Graduating Students can demonstrate understanding, friendliness, adaptability, empathy, and politeness in group settings.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 6. Information Technology Skills
27. Our Graduating Students can choose procedures, tools or equipment including computers and related technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
28. Our Graduating Students understand overall intent and proper procedures for the setup and operation of equipment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
29. Our Graduating Students can prevent, identify, or solve problems with equipment, including computers and other technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
30. Our Graduating Students can identify the need for data, obtain data from existing sources or create it, and evaluate its relevance and accuracy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
31. Our Graduating Students can organize, process, and maintain written or computerized records and other forms of information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
32. Our Graduating Students can select and analyze information and communicate the results to others in oral, written, graphic, pictorial or multimedia methods.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
33. Our Graduating Students can employ computers to acquire, organize, analyze and communicate information, and demonstrate some proficiency with standard software.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 7. Systems Thinking Skills
34. Our Graduating Students know how social, organizational, and technological systems work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
35. Our Graduating Students can distinguish trends, and predict the impacts of actions on system operations.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 36. Our Graduating Students make suggestions to modify existing systems to improve products and services and develop new or alternative systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
37. Our Graduating Students know how to assess the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
38. Our Graduating Students know how to recognize the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
39. Our Graduating Students understand the interaction and interrelationship of systems within an organization.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 40. Our Graduating Students understand the interaction and interrelationship of systems in a global economy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
41. Our Graduating Students attend required organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 42. Our Graduating Students are on time for organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 43. Our Graduating Students achieve organizational and personal goals independently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
44. Our Graduating Students complete work on-time.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
45. Our Graduating Students understand organizational protocols and procedures.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 46. Our Graduating Students demonstrate a positive attitude at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
47. Our Graduating Students are dependable at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
Appendix H
Questionnaires for Partnered Industries of CTU-Carmen Campus
PART 1. RESPONDENT’S PROFILE
Direction: Fill out the required information.
Name :
Age :
Gender :
Type of Industry :
Name of Industry :
PART 2. GRADUATES' ATTRIBUTES AND REQUIREMENTS IN THE HIRING PROCESS
Directions: Please answer the following questions by marking the box (✓ ) that corresponds to your answer. The items listed below are attributes of recent college graduates that you might consider as requirements in the hiring process.
Note: This list of survey questions (1 to 47) is taken verbatim from an article by Stuart Rosenberg (Rosenberg, 2012), with the only change being that the original subject, 'I,' has been replaced with the phrase, 'It is important for the graduates to.'
ITEM NO. 1. Basic Literacy and Numeracy Skills
1. It is important for the graduates to perform basic computations and approach practical problems with different mathematical techniques.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 2. It is important for the graduates to organize basic ideas; communicate orally.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 3. It is important for the graduates to organize basic thoughts, ideas, and messages in writing; create documents such as letters, directions, manuals, reports, graphs, and flow charts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 4. It is important for the graduates to receive, attend to, interpret, and respond to basic verbal messages/cues.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
5. It is important for the graduates to have the ability to locate, understand, and interpret basic written information in documents such as manuals, graphs, and schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 2. Critical Thinking Skills
6. It is important for the graduates to generate new ideas.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
7. It is important for the graduates to specify goals and constraints, generate alternatives, consider risks, and evaluate and choose the best alternative.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
8. It is important for the graduates to recognize problems and devise and implement a plan of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
9. It is important for the graduates to organize and process symbols, pictures, graphs, objects and other information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
10. It is important for the graduates to acquire and apply new knowledge and skills from multiple print and digital sources.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
11. It is important for the graduates to discover a rule or principle underlying the relationship between two or more objects and apply it when solving a problem.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 3. Leadership Skills
12. It is important for the graduates to exert a high level of effort and persevere toward goal attainment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 13. It is important for the graduates to believe in my own self-worth and maintain a positive view of myself.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 14. It is important for the graduates to set personal goals, monitor progress, exhibit self-control and take responsibility for my actions.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 15. It is important for the graduates to choose ethical courses of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 16. It is important for the graduates to communicate ideas to justify positions, persuade and convince others, and responsibly challenge existing procedures and policies.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 4. Management Skills
17. It is important for the graduates to select goal-relevant activities, rank them, allocate time, and prepare and follow schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 18. It is important for the graduates to use or prepare budgets, make forecasts, keep records, and make adjustments to meet objectives.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 19. It is important for the graduates to acquire, store, allocate, and use materials or space efficiently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 20. It is important for the graduates to assess skills and distribute work accordingly, evaluate performance and provide feedback.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 5. Interpersonal Skills
21. It is important for the graduates to contribute to group efforts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
22. It is important for the graduates to help others to learn.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
23. It is important for the graduates to work to satisfy customers’ expectations.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
24. It is important for the graduates to work toward agreements involving the
exchange of resources, and resolve divergent interests.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
25. It is important for the graduates to work well with men and women from diverse backgrounds.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
26. It is important for the graduates to demonstrate understanding, friendliness, adaptability, empathy, and politeness in group settings.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 6. Information Technology Skills
27. It is important for the graduates to choose procedures, tools or equipment including computers and related technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
28. It is important for the graduates to understand overall intent and proper procedures for the setup and operation of equipment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
29. It is important for the graduates to prevent, identify, or solve problems with equipment, including computers and other technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
30. It is important for the graduates to identify the need for data, obtain data from existing sources or create it, and evaluate its relevance and accuracy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
31. It is important for the graduates to organize, process, and maintain written or computerized records and other forms of information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
32. It is important for the graduates to select and analyze information and communicate the results to others in oral, written, graphic, pictorial or multimedia methods.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
33. It is important for the graduates to employ computers to acquire, organize, analyze and communicate information, and demonstrate some proficiency with standard software.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 7. Systems Thinking Skills
34. It is important for the graduates to know how social, organizational, and technological systems work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 35. It is important for the graduates to distinguish trends, and predict the impacts of actions on system operations.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 36. It is important for the graduates to make suggestions to modify existing systems to improve products and services and develop new or alternative systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 37. It is important for the graduates to know how to assess the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 38. It is important for the graduates to know how to recognize the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 39. It is important for the graduates to understand the interaction and interrelationship of systems within an organization.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 40. It is important for the graduates to understand the interaction and interrelationship of systems in a global economy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
41. It is important for the graduates to attend required organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
42. It is important for the graduates to be on time for organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
43. It is important for the graduates to achieve organizational and personal goals independently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
44. It is important for the graduates to complete work on-time.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
45. It is important for the graduates to understand organizational protocols and procedures.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
46. It is important for the graduates to demonstrate a positive attitude at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
47. It is important for the graduates to be dependable at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
Appendix I
Questionnaires for School Mentors of CTU-Carmen Campus
1. RT 1. RESPONDENT’S PROFILE
Direction: Fill out the required information.
Name :
Age :
Gender :
Type of Industry :
Name of Industry :
2. RT 2: GRADUATES' ATTRIBUTES AND REQUIREMENTS IN THE HIRING PROCESS
Directions: Please answer the following questions by marking the box (✓ ) that corresponds to your answer. The items listed below are attributes of recent college graduates that you might consider as requirements in the hiring process.
Note: This list of survey questions (1 to 47) is taken verbatim from an article by Stuart Rosenberg (Rosenberg, 2012), with the only change being that the original subject, 'I,' has been replaced with the phrase, 'It is important for the graduates to.'
ITEM NO. 1. Basic Literacy and Numeracy Skills
1. It is important for the graduates to perform basic computations and approach practical problems with different mathematical techniques.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 2. It is important for the graduates to organize basic ideas; communicate orally.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 3. It is important for the graduates to organize basic thoughts, ideas, and messages in writing; create documents such as letters, directions, manuals, reports, graphs, and flow charts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
4. It is important for the graduates to receive, attend to, interpret, and respond to basic verbal messages/cues.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 5. It is important for the graduates to have the ability to locate, understand, and interpret basic written information in documents such as manuals, graphs, and schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 2. Critical Thinking Skills
6. It is important for the graduates to generate new ideas.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
7. It is important for the graduates to specify goals and constraints, generate alternatives, consider risks, and evaluate and choose the best alternative.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
8. It is important for the graduates to recognize problems and devise and implement a plan of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
9. It is important for the graduates to organize and process symbols, pictures, graphs, objects and other information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
10. It is important for the graduates to acquire and apply new knowledge and skills from multiple print and digital sources.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
11. It is important for the graduates to discover a rule or principle underlying the relationship between two or more objects and apply it when solving a problem.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 3. Leadership Skills
12. It is important for the graduates to exert a high level of effort and persevere toward goal attainment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 13. It is important for the graduates to believe in my own self-worth and maintain a positive view of myself.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 14. It is important for the graduates to set personal goals, monitor progress, exhibit self-control and take responsibility for my actions.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
15. It is important for the graduates to choose ethical courses of action.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
16. It is important for the graduates to communicate ideas to justify positions, persuade and convince others, and responsibly challenge existing procedures and policies.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 4. Management Skills
17. It is important for the graduates to select goal-relevant activities, rank them, allocate time, and prepare and follow schedules.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 18. It is important for the graduates to use or prepare budgets, make forecasts, keep records, and make adjustments to meet objectives.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 19. It is important for the graduates to acquire, store, allocate, and use materials or space efficiently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 20. It is important for the graduates to assess skills and distribute work accordingly, evaluate performance and provide feedback.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 5. Interpersonal Skills
21. It is important for the graduates to contribute to group efforts.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
22. It is important for the graduates to help others to learn.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
23. It is important for the graduates to work to satisfy customers’ expectations.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
24. It is important for the graduates to work toward agreements involving the
exchange of resources, and resolve divergent interests.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
25. It is important for the graduates to work well with men and women from diverse backgrounds.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
26. It is important for the graduates to demonstrate understanding, friendliness, adaptability, empathy, and politeness in group settings.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 6. Information Technology Skills
27. It is important for the graduates to choose procedures, tools or equipment including computers and related technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
28. It is important for the graduates to understand overall intent and proper procedures for the setup and operation of equipment.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
29. It is important for the graduates to prevent, identify, or solve problems with equipment, including computers and other technology.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
30. It is important for the graduates to identify the need for data, obtain data from existing sources or create it, and evaluate its relevance and accuracy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
31. It is important for the graduates to organize, process, and maintain written or computerized records and other forms of information.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
32. It is important for the graduates to select and analyze information and communicate the results to others in oral, written, graphic, pictorial or multimedia methods.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
33. It is important for the graduates to employ computers to acquire, organize, analyze and communicate information, and demonstrate some proficiency with standard software.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 7. Systems Thinking Skills
34. It is important for the graduates to know how social, organizational, and technological systems work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 35. It is important for the graduates to distinguish trends, and predict the impacts of actions on system operations.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 36. It is important for the graduates to make suggestions to modify existing systems to improve products and services and develop new or alternative systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 37. It is important for the graduates to know how to assess the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 38. It is important for the graduates to know how to recognize the efficient operation of social, organizational and technological systems.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER 39. It is important for the graduates to understand the interaction and interrelationship of systems within an organization.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
40. It is important for the graduates to understand the interaction and interrelationship of systems in a global economy.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
ITEM NO. 8. Work Ethic
41. It is important for the graduates to attend required organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
42. It is important for the graduates to be on time for organizational meetings and events.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
43. It is important for the graduates to achieve organizational and personal goals independently.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
44. It is important for the graduates to complete work on-time.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
45. It is important for the graduates to understand organizational protocols and procedures.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
46. It is important for the graduates to demonstrate a positive attitude at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
47. It is important for the graduates to be dependable at work.
[ ] ALWAYS [ ] SOMETIMES [ ] RARELY [ ] NEVER
Appendix J
Demographic Profile of the Respondents According to their Desired Career
Illustrations are not included in the reading sample
Appendix K
Illustrations are not included in the reading sample
Appendix L
Graphical Comparison of Perceptions of Employability Attributes Across Different
Illustrations are not included in the reading sample
Appendix M
Findings on Employability Attributes
Illustrations are not included in the reading sample
[...]
Acheter maintenant
- Citation du texte
- Wilson Jerusalem (Auteur), 2025, Alignment Between The Employability Attributes of Graduating Students and Industry Requirements, Munich, GRIN Verlag, https://www.grin.com/document/1695568
