The influence of social networks on students' learning achievements

Outline

Outline

List of Abbreviations

List of Figures

List of Tables

1 Introduction to the topic
1.1 Relevance of the topic
1.2 Research objectives and structure of the thesis

2 Conceptual framework
2.1 Social capital
2.2 Learning achievements

3 Methodology
3.1 Initial and pilot study
3.2 Categorisation of the literature and literature review

4 The influence of social networks on students’ learning achievements
4.1 Network composition
4.2 Components of social capital
4.2.1 Structural dimension of social capital
4.2.2 Relational dimension of social capital
4.2.3 Resource-based dimension of social capital
4.3 Moderators and mediators of social capital and learning achievements
4.4 Contingencies of social capital
4.5 Discussion of the findings

5 Recommendations for practice

6 Conclusion and future research

Bibliography

Appendix

Abstract

This study raises an understanding of social network relationships among students and especially, how these ties affect the students’ learning achievements positively by creating social capital in designated networks. The thesis investigates the concept and measurement of social capital in university settings by applying a literature review. Thus, this study analyses the present and past literature by a systematic literature search and suggesting a model that connects students’ backgrounds, social capital at university and students’ learning achievements. Finally, results are presented and discussed, which show that all three dimensions of social capital influence students learning achievements in higher educational settings. However, not all specific components influence the different variables in the same manner and some have no influence. Furthermore, recommendations and directions for further research are provided. In sum, the study finds that a student’s social capital, generated from his or her social relations with parents, teachers and other peers, has a significant influence on the learning achievements.

List of Abbreviations

Abbildung in dieser Leseprobe nicht enthalten

List of Figures

Figure 1: Growth of the literature appearance about social capital

Figure 2: Version 1 of the conceptual framework towards social capital and learning achievements

Figure 3: Methodical procedure during the literature search

Figure 4: Pre-conclusion: Version 2 of the conceptual framework towards social capital and learning achievements

Figure 5: Main conclusion - Final version of the framework of social capital and its influence on learning achievements

List of Tables

Table 1: Overview of criteria to include or exclude literature

Table 2: Overview of the studies about the influence of social networks and their results

1 Introduction to the topic

Human capital plays an important role in school, college and organisations all over the world. For different areas of research, it is important to identify how new knowledge is created and spread. Therefore, social network analyses can be utilised, in order to determine knowledge and information flows. This in turn contributes to estimate or even predict the learning achievements of students. Here, the first research question arises: How do social networks influence students’ learning achievements? Additionally, this thesis wants to demonstrate where future research is suggested to tend to as a second research aim. Prior to this, fundamental questions like, “What is social capital?” and, “How can learning achievements be clustered?” shall be answered.

1.1 Relevance of the topic

“[C]onnections are grounded in the history of a market. Certain people have met frequently. Certain people have sought out specific others. Certain people have completed exchanges with one another” (Burt 2000, p. 348).

The previous quote emphasises that connectedness is an important part of humans’ everyday life. People interact with other people over time and form a set of actors with defined relations

- social networks (cf. Wasserman/Faust 1994, p. 20). Network research is a relatively new area of science (cf. Stegbauer 2010, p. 11) and gained a research boom during the last decades (cf. Brandes et al. 2013, p. 12). There is no social science discipline, where network perspective is not discussed: On the one hand, the 1970s and ‘80s were shaped through more social network analysis techniques, whereas the 1990s on the other hand, beard a higher theoretical interest in social networks. This can be ascribed to the fact that social network analyses create a new sociological aspect on social settings, compared to classic approaches like the actor view (cf. Stegbauer/Häußling 2010, p. 13). Remarkably a trend towards networking can also be noted down, as there is a more frequent usage of cooperative learning strategies. It remains steady with altering circumstances in organisations that progressively involve employees to work in teams, to have good interpersonal competencies, valuing individual dissimilarities and handling complex news (cf. Baldwin/Bedell/Johnson 1997, p. 1369). Consequently, human capital can generate a sustainable advantage because it is difficult to copy (cf. Hatch/Dyer 2004, p. 1172). Frequent studies concentrated on so-called human capital (cf. Hitt et al. 2001, p. 13), whereby scientists relied on it as an indicator for performance measures (cf. Wang/Chang 2005, p. 226). Further studies indicated that profitable earnings come from the equivalent human capital (cf. Mincer 1993, p. 372), and also revealed that companies with educated employees can induce organisational members, in order to combine their existing knowledge with acquired knowledge, or recombine their existing knowledge in better ways (cf. Shu et al. 2012, p. 131). In other words, employees are expected to foster new ideas more frequently. Consequently, researchers focus more on the impact of interpersonal social networks and specific relations among social network participants (cf. Wasserman/Faust 1994, p. 199; cf. Granovetter 2005, p. 34). Especially, when it comes to career success, having the right contacts and relationships plays an increasingly important role (cf. Michael/Yukl 1993, p. 328; cf. Wanberg/Kanfer/Banas 2000, p. 491; cf. Wolff/Moser 2009, p. 196).

On top of that, social and economic growth of a country are interrelated with the students’ learning achievements, because they are expected to be the future entrepreneurs and potentially the economic leaders of our society (cf. Teixeira/Rocha 2010, p. 663). On these grounds, it is important to have a deeper look into how knowledge is shared, not only in organisations, but also in schools, colleges and universities as well (cf. Schmitt/Sixt 2014, p. 68). In higher academic surroundings, social networks provide human capital as an output while the contributions into this process are students themselves. The attendance of different types of students may also impact the output received by other learners (cf. Rothschild/White 1995, p. 574). To date, many scholars already focused on the school setting. For instance, Sun (1999) proved the importance of community social capital in examining school performance. The findings state that amongst others, socioeconomic parts of a community validate the relations between communal construction and school performance (cf. Sun 1999, p. 403). A further study presented that community capital, including social capital, is a strong predictor of school outcomes (cf. Porfeli et al. 2009, p. 72). Thus, it is an important issue to investigate which factors contribute to students’ academic success, who become, as stated before, new resources in a company and further create a value for society (cf. Herschel 2012, p. 14 f.; cf. Strom/Sanchez/Downey-Schilling 2011, p. 9).

Indeed, it can be declared that nowadays social networks are an influential occurrence for students and enable the production of social capital (cf. Fischer/Scharff/Ye 2004, p. 349). Some central aspects affecting students’ academic achievements are high standards for learning and learning networks among professionals (cf. Klem/Connell 2004, p. 262). In addition, some researchers have recognised that social integration is also a central factor to academic achievements (cf. Tinto 1997, p. 611; cf. Hosen/Solovey-Hosen 2003, p. 84).

Especially, concerning social capital and its benefits, Lin (1999) refers to Bourdieu (1986) who suggested that there are resources fixed within family and members of the environment, so it is important to make use of those resources. The fundamental assumption that lies within the concept of social capital is uncomplicated and easy: investing in social relationships due to expected returns (cf. Lin 1999, p. 34). Consequently, it is assumable that social network constructions clarify what makes some individuals more productive and effective in their knowledge utilisation than others. Hence, the social network position and network structure are related to students’ achievements (cf. Cadima/Ojeda/Monguet 2012, p. 301). In this regard, it can be noted that networking is becoming more appreciated as a factor influencing students’ achievements, but creates difficulties with it in examining this issue (cf. Thomas 2000, p. 592). Therefore, social network analysis methods deliver an efficient tool for visualising networks by analysing ties among several actors (cf. Cross/Borgatti/Parker 2001, p. 215 f.). Such visualised social networks could be roommates, friends, fellow students or professionals and be tested if they affect learning achievements, consisting of grades, information, persistence, and satisfaction (cf. Sacerdote 2001, p. 690; cf. Zimmerman 2003, p. 11; cf. Ojeda/Navarro/Morales 2010, p. 216; cf. Sacks/Graves 2012, p. 80; cf. Lavy/Sand 2012, p. 2). Hence, it is important to identify how students’ learning in combination with their surroundings, thus their relations, contributes to the career of college students. More knowledge about how networks are established and what students receive from their relations, would enable students to enter important relationships early in their careers. As a direct consequence, students might increase their achievements and pleasure with all aspects of their academic lives (cf. Hitchcock et al. 1995, p. 1108).

Amongst others, negative influences of social networks on achievements can occur (cf. Wentzel/Wigfield 1998, p. 164), but will not be discussed any further due to the limited scope of this master thesis. Nevertheless, the present literature review will investigate the current state of research and demonstrate how social networks affect students’ learning achievements. Furthermore, recommendations for practice will be derived and strategies for future research will be discussed based on the gathered information.

To ensure orientation and intelligibility, the next paragraph provides a comprehensible structure of the thesis. Further on, the following section states which research objectives shall be examined within the literature review, to shape and lead the study.

1.2 Research objectives and structure of the thesis

Research objectives: The first main objective of the present literature review is to give an overview of the state of the art concerning social capital and its influence on learning achievements. The second main purpose of this study is to examine whether and how social networks affect the learning achievements of students. For this purpose, only students attending (open) colleges, (open) universities or business schools will be examined. The findings will be compared and paid tribute to in a critical manner, so the work can be integrated into the present field of educational research. Furthermore, this thesis studies which other factors affect the relation between social capital and learning achievements by illustrating cases of contingencies, moderators and mediators. The research gap shall be highlighted, as there are more investigations needed to combine social capital and learning achievements in higher educational contexts, as well as missing reviews about the topic like meta-analyses or literature reviews. In succession, the thesis intends to support the research by proposing recommendations for action and summarising how social networks and learning achievements interrelate, since they play a significant role for academic and business settings. Finally, the found scope of research and its discussion will yield new areas that should be examined in the future.

Subsequently, after stating what objectives with regard to the influence of social networks will be examined, two research questions can be initiated to guide this study:

- Research Question 1: How do social networks influence students’ learning achievements?
- Research Question 2: Where shall future research be heading to?

Structure of the thesis: The beginning of this present review, the first chapter, depicts the relevance of social capital and learning achievements in connection to the development of studies about human capital, social capital and social networks. Chapter 2 abstracts the key concepts with their explanations about social capital and highlights the different perspectives which have been developed over time: sociological, network-based and educational. Those are necessary to reduce the complexity of the social capital frameworks. For the further course, definitions of persistence, satisfaction, grade point average, grades and information exchange matter concerning the student’s learning achievements (cf. Sun 1999, p. 425; cf. Rosenbaum/Rochford 2008, p. 359; cf. Lomi et al. 2011, p. 1511). Learning achievements are clustered into these categories mentioned before, as there exists no single measurement tool for it (cf. Tent 2006, p. 863). Afterwards the methodology chapter, chapter 3, illustrates how the evaluated literature has been limited and selected. Thereby, the systematic techniques clarify how to find and structure the body of literature for such a review. The next section represents the main part of the thesis. Therefore, the constitution of different networks is described in chapter 4, introducing the important types of networks being considered in the following sections. Those are described as being either formal or informal. In the course of this study formal networks will relate to professionals and employees of the faculty, whereas informal networks will state the personal relations to roommates, fellow students, friends and family. Further on, the fourth chapter underlines the current state of research with regard to the networking effects on academic achievements (cf. Pascarella 2001; cf. Sacerdote 2001; cf. Zimmerman 2003). As a basis, the construct of individual social capital according to Fliaster (2007, 2014) is used. Thereby, the author distinguishes between structural and relational embeddedness of an actor, whereas the latter again is divided into ties and resources (cf. Fliaster 2014, p. 126). In sum, three enablers of social capital exist which in turn lead to three dimensions of social capital including relational, structural and resource-based social capital an actor can gain access to (cf. Fliaster 2007, p. 132). Considering that, each dimension will be analysed if it has an impact on students learning achievements. Additionally, moderators and mediators which influence networks as well, will be determined in order to complete the following discussion in subchapter 4.3 (cf. Zheng 2010, p. 174; cf. Eisenkopf 2010, p. 365). Then, contingencies (cf. Lin 1999, p. 42) which are synonymous to situational factors will be added to the literature review in part 4.4 to complete the required variables for the framework which is intended do be developed at the end of the thesis. In this context, limitations and critics of the studies are exposed (cf. Stinebrickner/Stinebrickner 2006, p. 1436), in order to discuss the ability of social networks that affect students’ achievements. Afterwards, based on all findings, chapter 5 forms practice-oriented recommendations. Those are divided into suggestions for students, academic institutions and business organisations, because all three components are interdependent in forming the future economy. Finally, the accomplishment of this master thesis results with a conclusion. Therefore, the final framework will be presented. At the same time, an interpretation of existing literature regarding new and current affairs will be illustrated.

After introducing the topic and highlighting the relevance for research, chapter 2 clarifies the definitions of social capital and learning achievements.

2 Conceptual framework

This section deals with the theoretical terms being essential for the comprehension of this examination. For this purpose, social capital is defined first. Different definitions developed in the course of time are controverted and delimited from each another. Thereby it is clarified why the framework of social capital from Alexander Fliaster (2007, 2014) is illustrated and discussed in particular further on. After that, the construct of learning achievements, the second key variable in the present work, is classified in this paragraph.

2.1 Social capital

“[I]ts effects lie in information, influence, and solidarity benefits that accrue to members of a collectivity (“bonding” social capital) and to actors, whether individual or collective, in their relations to other actors (“bridging” social capital). Its sources lie in the social relations among those actors, and these social relations can be differentiated (notionally) from relations of market exchange and of hierarchical authority” (Kwon/Adler 2014, p. 412).

Concerning this quote, social capital indicates one’s facility to gain benefits from social relationships with others. Current hypothetical and empirical works on social capital offer an almost analogous basis for understanding how social networks and connections can be understood. Before these days, the term social capital was independently developed and investigated by different researchers in different disciplines over different periods of time. As a result, there existed no uniform term (cf. Jans 2011, p. 11). Consequently, over the last decade a gradual interdisciplinary consolidation of social capital research came up (cf. Jans 2011, p. 16). The diagram on the next page shows even more how the popularity of social capital grew over the last decades. In the diagram, the horizontal axis shows the years from 1990 until today. The vertical axis represents the frequency of literature which comprised social capital. The search has been conducted in August 2015. The term social capital was searched in all databases from EBSCOhost to cover the whole scientific reputation. The phrase was combined as “social+capital” so that biases containing a wrong context could be excluded, when all headings with “social” or “capital” would have been considered. Furthermore, it was only searched in the title of literature, because when the phrase “social capital” is contained in the title, it can be derived that the phrase has a significant part in the certain work. It can be seen, that since the 1990s a more frequent appearance of social capital is highlighted. Even if there are some recessions in the graphic, the tendency of the whole diagram is positively rising. The decrease at the end can be explained, as the year 2015 has not ended yet and it is assumed that there are more articles to come.

Abbildung in dieser Leseprobe nicht enthalten

Figure 1: Growth of the literature appearance about social capital

Source: Own survey; Own illustration; Following Burkhart et al. (2011), p. 5

Due to a great amount of literature, it is not unexpected, that there exist several standpoints related to the theory of social capital (cf. Granovetter 1973, 2005; cf. Bourdieu 1986; cf. Coleman 1988; cf. Putnam 1993; cf. Nahapiet/Ghoshal 1998; cf. Lin 1999; cf. Burt 2005). The term social capital appeared in the work “the rural school community center” by Hanifan for the first time (cf. Hanifan 1916, p. 130) and more relevant evidence was discovered by Granovetter (1973), Coleman (1988), Putnam (1993) and Burt (1992). From the sociological perspective, Mark Granovetter (1973) was the first researcher who distinguished between strong and weak ties, hence social capital (cf. Granovetter 1973, p. 1361). He concluded that peoples’ know-how is narrowly linked with spacious features of social composition, but cannot be controlled by the individual (cf. Granovetter 1973, p. 1377). Most importantly, he described the strength of weak ties: Individuals get more new information through weak relations. Instead, people to whom one keeps strong connections, often are in the same circle of friends and the knowledge one obtains is not new. Individuals can get more new information from loose acquaintances, as those in turn have other relations from which they gain news. Despite, Granovetter (2005) pointed out that this benefit of weak ties only occurs partially, as interactions with acquaintances are limited as compared to those with close friends. Accordingly, holding various weak ties and nurturing a solid group cohesiveness, can lead to a valuable result (cf. Granovetter 2005, p. 34).

One theory promoting the concepts by Granovetter (1973, 2005) is the structural holes theory of social capital, developed by Burt (1992, 2000, 2001) using the network perspective (cf. Burt 2001, p. 35). The author understands social capital as a metaphor of benefits (cf. Burt 2000, p. 346). He suggests that an actor in a network transports at minimum three types of capital: human, financial, and social capital. Furthermore, the researcher claims that social capital differs based on which other actors are reached and how this is made (cf. Burt 1992, p. 9 ff.). In addition, social capital contains resources positioned within procedures and structures of collective exchange. So, social capital is shaped by those societal factors affecting the development of social relationships (cf. Nahapiet/Ghoshal 1998, p. 256). In this connection, also Lin (1999) focuses on the access to resources and its usage embedded within social networks (cf. Lin 1999, p. 30). In contrast to other authors, who focused on strengths of ties (e.g. Burt 1992, 1997), Coleman (1988) and later on Lin (1999), emphasise the point that social networks should include closed and open structures (cf. Coleman 1988, p. 106; Lin 1999, p. 32). Open networks encourage actors to build bridges, while closed networks facilitate familiar and mutual ties (cf. Lin 2001, p. 20).

From the educational perspective Coleman (1988) was one of the first scientists who wrote about the significance of social capital in learning environment. He highlights that social capital represents different sources of capital available (cf. Coleman 1988, p. 98). In a revised work, he expresses social capital as the range of resources an individual can get from the family network and the public institutes. In this sense, social capital plays a valuable role in developing mental or social skills of a young person (cf. Coleman 1990, p. 300), i.e. a student. Additionally, Bourdieu (1986) defines social capital as the summative of present or possible resources that are connected to property of a long-lasting network of reciprocal relationships, that offers its member network-owned capital (cf. Bourdieu 1986, p. 248). Furthermore, Putnam (2000) also highlights the complexity of social capital, by describing that human capital belongs to individual actors while social capital is connected to individuals’ social networks and the different types of exchange appearing (cf. Putnam 2000, p. 19). In other words, the valuable resource is not the network itself, but it is an intermediate by which a student can reach the resources inherited by other actors of a network. Summarising the several perspectives of social capital, they all have one aspect in common: For the most part, all definitions of social capital highlight its relevance as well as connecting social capital to individual actors or rarely to collective actors (cf. Jans 2003, p. 5).

To recapitulate, in the area of learning a wider typology of relations postulates a beneficial explanation of social capital: bonding and bridging connections (cf. de Jong 2010, p. 25). On the one site, it is important to remember that bonding social capital refers to contacts between people of a homogenous group. Therefore, within such a group strong relations can be established and borders become stronger to not let in people who are not qualified for the network (cf. Schuller/Baron/Field 2000, p. 10). On the contrary, bridging social capital refers to the development of contacts between heterogeneous individuals (cf. Putnam 2001, p. 28).

Finally, to substantiate a clear definition of social capital, a categorisation is selected which combines the most important characteristics of it. Therefore, social capital can be expressed as the the aggregation of resources, especially knowledge, but also emotional support and backing an actor appreciates due to the specific nature of his or her social network. Furthermore, the structural position in this network (e.g. proximity to structural holes), the characteristics of its dyadic relations network (e.g. trust) and the characteristics of the other network actors (e.g. their resources) can basically be exploited in order to achieve its targets for action (cf. Fliaster 2007, p. 119). Deriving from this definition, students can benefit from their social networks by gaining access to three enablers of social capital: structural, relational and resource-based access (cf. Fliaster 2007, p. 135; cf. Fliaster 2014, p. 126). For this thesis, latter enablers will be considered as dimensions and taken into account because they combine the most important statements according to social capital. The specific dimensions will be further examined in chapter 4 of the study.

2.2 Learning achievements

The fundamental sense of social capital lies in the values that social networks contain. Furthermore, it accentuates the various profits which occur through social networks due to different levels of capital. The diverse collaborations form ties as well as trust in other actors in the network and foster the exchange of information. However, the appreciation of fitting into the network can differ among people, namely students. Since there are clear sorts of social connections bringing people together for specific reasons, like students meeting and studying together for an exam, such types of interactions are more probable to spread social capital than others (cf. Davis 2009, p. 17). This indicates that several networks affect different outcomes in academic achievements: to illustrate, a recent work underlined that school social networks could increase pupils’ mathematical skills (cf. Gholson/Martin 2014, p. 19).

However, defining learning achievements can form a challenging assignment: the identification of the substantial facets affecting achievements, especially those of students, is one of the eldest and most difficult problems in educational psychology (cf. Helmke/Schrader 2006, p. 83). Therefore, studies use operationalization methods of learning achievements which are assumed to fit in both, school contexts as well as in the higher institutional contexts (cf. Helmke/Rindermann/Schrader 2008, p. 146).

Unfortunately, no single measurement can exactly compute the success or failure of learning. One attempt to do so involves grades as indicators for learning achievements (cf. Tent 2006, p. 873). Grades from students can function as an indicator for learning achievements because they can be easily compared and researchers access them quickly (from the examination office). Similarly, grades are more specific as compared to the grade point average (GPA) (cf. Schiefele et al. 2003, p. 190). Nevertheless, the GPA is often used to measure learning achievements (cf. de la Iglesia/Stover/Fernández Liporace 2014, p. 644). This construct belongs to the most examined predictors of achievements in college (cf. Helmke/Rindermann/Schrader 2008, p. 151; cf. Trapmann et al. 2007, p. 11). Furthermore, the GPA is a common and open-minded measurement tool of learning achievements at higher institutions. It postulates a complete examination of the student performance and is internationally predictable. Not only this, but grade point average is the single straight, universal and conventional measure which delivers a rational placing of academic achievement as well (cf. Young/Fry 2008, p. 8). Additionally, researchers use further procedures to compute degrees of achievements in education. Analysing the rates gathered from student surveys, information can be reviewed and three academic rates have been derived as variables of learning achievements: the rate of passed classes, rate of failed classes and finally the rate of classes dropped out (cf. de la Iglesia/Stover/Fernández Liporace 2014, p. 640). Besides, learning achievements can consist of the amount or types of information that students get from their social networks. A lot of studies examine the connection of social capital and new information (cf. Sun 1999, p. 425; cf. Sheng/Hartono 2015, p. 93). Information is an important variable to examine, because students who receive a lot of new knowledge or exchange information while learning, understand different subjects better, which will positively impact their learning procedures. Learning within a network, provides supplementary information, that might support actors to validate feedback for instance and perceive it as more correct and trustworthy. The greater the size of a network, the more extra information an actor can have access to, thus the more information exchange in terms of the feedback is gathered (cf. Patzelt/Lechner/Klaukien 2011, p. 804). To note, that some studies also examine students’ knowledge retention: A student is expected to have good learning achievements because of the individual’s social network. For example, if he or she learns together with fellow mates, he or she is expected to have a better retention of knowledge imparted in a course than those students educated in lecture-based classes (cf. Tran 2014, p. 131). Hence, information or information exchange can be considered as a variable of learning achievements for students in this study. Another factor which can be attached to learning achievements is a student’s retention at a higher institution (cf. DeBerard/Spielmans/Julka 2004, p. 335). Many researchers undertake investigations concerning how successful students’ networks influence their retention and achievement of their degree (cf. Strayhorn 2010, p. 307). So retention can be an indicator for students learning achievements. In this connection, the completion of the college or university is often thematised in educational studies. While research often proves friendship relations as a social capital source, learning achievements can be examined on the connection between friends’ resources and attaining a college degree (cf. Cherng/McCrory Calarco/Cao 2013, p. 79). Another factor which is often correlating with students’ achievements is student satisfaction. Satisfaction designates the degree of a student’s response with regard to his or her expectations of learning achievements in a certain subject. A student’s attitude might be reflective of the curriculum content like learning undertakings, group learners, or the teacher (cf. Sorden 2011, p. 9). After defining social capital and learning achievements, the following framework can be integrated into this work:

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Figure 2: Version 1 of the conceptual framework towards social capital and learning achievements

Source: Own survey from chapter 1 and 2; Own illustration

After the topic has been introduced and all theoretical origins and definitions have been specified, the next chapter puts a finer point on the the methodological process. It reveals the method of the literature review, by which the reader is able to retrace what and why specific literature was used.

3 Methodology

A literature review is a continuing process. Searching through literature, reading and writing are intertwined and a repeated process (cf. Ridley 2008, p. 80). Therefore, using a systematic range of steps is indispensable to avoid a lack of carefulness, because often reviews are not begun as authentic parts of investigatory scholarships. Unfortunately, they may deficit in reasonable processes of what the compilation of works is declaring. These analyses may be executed defectively by the scientist and regularly fail in rigidity. Likewise, for students, refining and making sense of a multitude of inconsistent proofs has been found to become more difficult. This is why new ways with the objectives of updating the practice and enhancing the information basis have been introduced. A literature review can be implemented into the other science areas to generate a consistent routine of understanding the process and improved exercise by emerging coherency-sensitive investigations (cf. Tranfield/Denyer/Smart 2003, p. 207). As a result, the collection of the studies which form this literature review have been accomplished through several stages (see table 1 and figure 2) that were continued along and based on Tranfield, Denyer and Smart’s (2003) and McFadden’s (2015) explanation of a literature review (cf. Tranfield/Denyer/Smart 2003, p. 213 ff.; cf. McFadden 2015, p. 129). For the methodology, relevant literature implies those studies. This this literature review was conducted in the period of time between May 2015 and September 2015.

3.1 Initial and pilot study

This literature review is systematised around an extensive framework which aims at preparing a new state of the art of both, social networks and learning achievements. Therefore, this chapter outlines the methodology followed to identify and evaluate relevant literature for the review. In the course of this overview, a quick impression of scholarly literature was performed by a simple test search on Google Scholar (cf. Oehlrich 2015, p. 23) with “social networks AND learning achievements” (about 356.000 search results).

The present review deals with social networks, their existing social capital and learning achievements from students in higher educational institutions. Thus, the first part of the initial analysis was a simple identification of search terms including keywords based on the first research question: “social networks AND learning achievements”. In addition, the search started with words considering each part of the topic a) keyword 1: social network* and b) keyword 2: learn* achievement*. Supplementary keywords related to both, the independent variable of interest (social networks) and the dependent variable (learning achievements) linked with thesaurus words like: (undegraduat* OR freshmen* OR freshman* OR student*) AND (performance* OR outcome* OR grade*). Further on, the context of research as college* OR universit* OR academic* OR high* institution*, has been added and the sample variable has been enlarged with the keyword “social capital” (cf. Jesson/Matheson/Lacey 2011, p. 27).

As a next step, the actual identification of the literature has been performed with the following electronic databanks and the keywords 1 AND 2: EBSCO Business Source Complete (47 peer-reviewed academic journals), ERIC (160 peer-reviewed academic journals), ScienceDirect (29.732 search results), ERIC (944 peer-reviewed publications), PsycINFO, PsycARTICLES, PsycBOOKS (474 search results), WISO-Net (162 search results), SocINDEX (73 search results), JSTOR (353.835 search results) (cf. Berger 2010, p. 68; cf. Kornmeier 2007, p. 112) and Mendeley Source (3.193.977 search results) provided by the literature management system. Additionally, relevant educational and sociological journals (like: Higher Education, Social Networks and American Sociological Review) were strictly of high relevance, due to the key emphasis of the thesis. To get more into the pedagogical sciences, also the database Fachportal Pädagogik (562 search results) was used (cf. Berger 2010, p. 67).

3.2 Categorisation of the literature and literature review

For the next step of the literature review, selection criteria were utilised to render the extent of the thesis more precisely, or in other words to make it practicable. Works included in this review were articles in journals, books, conference papers, working papers, meta-analyses, review and dissertations published in English and German language - to note that most of the studies found were in English language (about 97 percent). Especially, regarding the articles in journals, only peer-reviewed journals were provided for the review, to confirm the hypothetical quality (cf. Jesson/Matheson/Lacey 2011, p. 115; cf. Paul 2012, p. 16). Pre- published works, such as conference papers or working papers were only included, when they seemed to fit in appropriately as they presented new research findings. Another key criteria refers to the space of time to be masked. One aim of this literature review is to depict the state of art but also to show the evolution of social capital research and learning achievements over time. Therefore, this indicates a sizeable time horizon had to be consulted. So, the main focus lies on works from 1990 upstream, as the actuality of state of the art has to be assured. Publications before 1990 were excluded from the examination, while it was experienced that the literature about social networks has gained much more focus between 1990 and today, so that many of those findings would not be appropriate today. Besides, there was no study excluded because of its geographical origin. To increase the quality, especially journals ranked as A+, A and B in the VHB-JOURQUAL ranking were browsed through (cf. Schrader/Hennig-Thurau 2009, p. 184). Inappropriate fields have also been filtered out (e.g. social media networks, neurology networks and learning, students with learning disabilities) to ensure that false findings were disregarded. Afterwards, all academic works that did not represent an important contribution to social capital and learning achievement were further on removed and categorised by eliminating those that were not related to the subject, like “high school achievements”. Thus, for the empirical findings, only studies with college, university or faculty students were included. At this point, merely headings and in some cases the abstracts of the papers were read to select appropriate literature for the thesis. In sum, the several criteria were chosen referring to Jesson and colleagues (cf. Jesson/Matheson/Lacey 2011, p. 134).

Table 1: Overview of criteria to include or exclude literature

Source: Own illustration; Following Jesson/Matheson/Lacey (2011)

Abbildung in dieser Leseprobe nicht enthalten

In the next part, headings, keywords and their synonyms, were re-evaluated. Therefore, an extended search series was composed by adding diverse synonyms to the initial search string that the authors had used in their articles. Some studies were chosen manual, by reading through the reference lists of certain papers. More specifically, studies have been searched which fit into the several dimensions of social capital. In total, the literature identification and categorisation was refined repeatedly. After all selection criteria were added, a total of 30 studies came out, which could be used for the presentation of empirical findings (review) in chapter 4.2. Then in the fourth and last step, the review of the findings was performed by reporting the selected studies. An overview of the works and their findings is given at the end of the fourth chapter. For this, most of the studies which were chosen for the analysis were published between 2000 and 2015 (about 86 percent). This implies again, as proven in chapter 2.1., that the importance of research is up-to-date. Only two were theoretical analyses (cf. Robbins et al. 2004; cf. Topping 1998). This in turn confirms the scientific relevance of the present review. The studies were found in 26 journals, two dissertations and one conference paper as well.

Abbildung in dieser Leseprobe nicht enthalten

Figure 3: Methodical procedure during the literature search

Source: Own illustration; Following Tranfield/Denyer/Smart (2003); McFadden (2015)

This chapter elucidated the methods to structure the literature review and figure out important works about social networks and students’ learning achievements. Now, that all important studies have been figured out, they can be applied in the next part. The state of art can be documented and critically examined from different points of view in the discussion.

4 The influence of social networks on students’ learning achievements

Social capital can be generated out of many different network types and students have access to several networks, from which they can receive social capital. Those could be: family, roommates, friends, professionals, or other students. So, for the purpose of this examination, networks which gain much attention in the literature are analysed. This chapter presents studies which look into relations between social networks, their social capital and learning achievements, more in detail. They provide an overview of the current state of research, the progresses that have been made and what shortcomings exist in this field of research. In this context, specific studies, particularly those about networks at university, college or faculty, stay in the centre of interest. Furthermore, for each dimension of social capital it will be examined whether they affect learning achievements of students or not. To complete the initial framework, mediators, moderators and contingencies will be discovered. Afterwards a final discussion and summary of all empirical findings will close the fourth chapter.

4.1 Network composition

The term network is not only popular in everyday language, but also in a scientific discourse. Many publications prove that the concept of networking is in great demand (cf. Mayntz 2008, p. 750; cf. Wang et al. 2014, p. 454; cf. Funk 2014, p. 193). The importance of networks lies in the fact that different types of networks include different types of social capital (cf. Ream 2005, p. 202). From this it follows that the network composition relates to the features and resources which actors bear in the network. Furthermore, modifications in the composition of a network can encompass to differences in achievements through information, impact or support from others in one’s network. For instance, a dedicated student with well-informed friends may receive help from them in accomplishing a challenging task. Alternatively, an undergraduates achievement-oriented fellow student might apply pressure on the student to succeed (cf. Maroulis/Gomez 2008, p. 1904). Further, the network composition can be classified into two units: formal social networks and informal social networks. Formal networks refer to professional or academic relationships with a person. Informal networks refer to ties with other students, friends, peers or family (cf. Pucino/Penniston 2014, p. 203 f.; cf. Ream 2005, p. 215).

In the following, the several networks a student can access will be defined.

Informal networks providing bonding social capital

Family network: Family social capital includes family structure, number of siblings, and parental expectations (cf. Sandefur/Meier/Campbell 2006, p. 534). For instance, parents are essential in providing information related to education and future opportunities, establishing norms of expected behaviour and achievement, and assistance in navigating through the educational system (cf. Bankston/Zhou 2002, p. 304). To remark, the studies differ from families with a low, middle or high income, as well as the parents’ educational level (cf. Sun 1999, p. 415; cf. Zimmerman 2003, p. 10; cf. Cherng/McCrory Calarco/Kao 2013, p. 77).

Student-student network: An important element of freshmen’s achievements is their successful academic and communal integration into the university setting (cf. Tinto 2012a, p. 64). Therefore, an undergraduate’s skill to get access to social capital and then make use of it to his or her advantage depends on his or her embeddedness in networks and the structure of thsoe (cf. Moran 2005, p. 1147). The explicit concept behind embeddedness depends on a calculation of closeness. Closeness centrality measures can be conceptualised as the distance between a certain actor and his or her alters. This states that an actor who has a high closeness centrality has direct and indirect relations with the other participants of the network which can be reached by fewer steps (cf. Fliaster 2007, p. 222).

Peer network: Although adults have an essential impact on learning, research recommends that peer relations also play a meaningful role in the development of learning achievements (cf. Ames 1992, p. 268). A peer network is described as a group of individuals with the same rank, in which actors take the level, value or achievement of learning effects into account. The contrasting vocabulary implemented in the literature can cause confutation and thus needs more careful examination (cf. Topping 1998, p. 250). Nevertheless, peer networks embody a main part of social capital in educational settings (cf. Wells et al. 2011, p. 1). More specifically, peer networks characterise relations with a regularly social interaction among those participating in it. Moreover, members feel integrated into the community and a structure supporting the norms that brought the members together in the first place exists (cf. Rubin/Bukowski/Laursen 2009, p. 13).

Friendship network: Friendship relations among undergraduates are essential. Students connect with other students from which they can expect support. When friends communicate often, a student’s access to beneficial resources is expanded. Not only this, but friendship means that students are aware of the fact, that not every individual gets the same information, so that they spread it to everybody in the network who might not know the news. In addition, a good friendship network is able to increase both straight access to the information acquired by the students’ own connections and indirect access through friends of friends (cf. Baldwin/Johnson 1997, p. 1373).

Roommates: When students live in apartments, their flatmates may have an effect on how much they take delight in learning. At the same time, roommates can facilitate or oppose the intellectual conversations. Undergraduates can access social capital by using relations to informal networks. Thereby, spontaneous discussions may reveal new ideas, share knowledge and encouragements. Besides, roommates can help to explore the proposition of courses and campus meetings (cf. Zimmerman 2003, p. 11).

Formal networks providing bridging social capital

Professionals (teacher/professor): An important function of social networks allow students to gain access to social capital in terms of institutional and support resources (cf. Stanton- Salazar/Dornbusch 1995, p. 120). Observing teacher support is assumed to be important for understanding the social context of the institutional environment on achievement. Professionals, such as teachers are a main component in the educational development for learning achievements. Then, building a model to comprise social capital formed through teacher collaboration with undergraduates is required when analysing learning achievements (cf. Davis 2009, p. 133).

Mentors: A mentor is an experienced individual from a higher institution, who supports a less-experienced person. Thereby the mentor gives offer knowledge, backing and guidance for the less-experienced individuals (cf. Campbell/Campbell 1997, p. 727).

After defining the network compositions students might be confronted with, the next subchapter displays the several components of social capital and their influences on students’ learning achievements on the basis of the selected studies.

4.2 Components of social capital

As seen in chapter 2, there are numerous definitions of social capital. So far it has been stated, that social capital is connected to the value of networks and is basically about how people act reciprocally (cf. Dekker/Uslaner 2001, p. 3). To study the influence of social capital on students’ learning achievements, it is essential to examine the components social capital is made of more in detail. The conceptualisation of social capital can be segregated into three components, or for this thesis declared as dimensions: structural, relational and resource- based dimension (cf. Fliaster 2007, p. 132; cf. Fliaster 2014, p. 126). To sum it up, social capital can be measured by its closure, size, density, bridges or access to the bridges or the strength of ties (cf. Hennig 2010, p. 183; cf. Patzelt/Lechner/Klaukien 2011, p. 804).

4.2.1 Structural dimension of social capital

The structural dimension of social capital discusses relations among actors in network. It is constructed on the suggestion that ties within a network offer access to resources. Indeed, the network configuration considers ties, that deliver the paths for information communication. Actually, the complete configuration of these ties forms an essential component of social capital, implying that they have an impact on the development of intellectual capital (cf. Nahapiet/Ghoshal 1998, p. 252). This view of social networks on learning claims that learning is influenced by social access. This access is different from actor to actor due to infrastructure of ties and the application of these connections through contact between the actors (cf. de Jong 2010, p. 25).

The structural dimension comprises the following subcategories: i) Structural closure, ii)structural holes, iii) network size and iv) network position (cf. Fliaster 2014, p. 126).

i) Structural closure: People, i.e. students, gain advantages if their networks include closure. This means their acquaintances are closely related (cf. Gargiulo/Ertug/Galunic 2009, p. 300). Particularly, closure represents a dense network with homogeny people and multifaceted relations. Due to the actors’ homogeneity, it is suggested that they have similar values and norms. Therefore, their activities can be coordinated more easily and their behaviours can be predicted. Considering social relations’ multiplicity, actors are connected in more than one context (cf. Fliaster 2007, p. 111). Closure is expected to facilitate students’ chances of graduating (cf. Greeley 1997, p. 589).

ii) Structural holes: Structural holes in a network imply that actors, namely students, who are nearby those holes create useful ideas more likely (cf. Burt 2004, p. 349). As a matter of fact, structural holes give a student the possibility to broker the exchange and movement of knowledge among actors. For this reason, students in a broker position could regulate meetings that bring students together from alternate sides of the hole. Moreover, it is stated that students within a social network that crosses holes, are expected to share their knowledge with other students (cf. Burt 2001, p. 35).

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