This systematic review and PRISMA-based analysis examines the effects of vocabulary development strategies on the speaking skills of senior high school learners in English as a Foreign Language (EFL) and English as a Second Language (ESL) contexts between 2020 and 2025. Speaking proficiency is widely recognized as a multidimensional construct that includes fluency, grammatical accuracy, pronunciation, and vocabulary use, with lexical competence serving as a fundamental component of effective oral communication (Utami et al., 2025). Despite learners demonstrating strong receptive vocabulary knowledge, several studies report persistent difficulties in transferring lexical knowledge into fluent and intelligible spoken communication (Enobio & Palma, 2025). This review therefore aims to synthesize empirical evidence regarding how vocabulary development strategies influence speaking performance, identify the most frequently applied instructional approaches, and examine contextual factors affecting their effectiveness.
Following the PRISMA 2020 framework for systematic reviews, data were collected from major academic databases, including Google Scholar, ERIC, Scopus, and ScienceDirect. An initial pool of approximately 600 studies was identified, and after duplicate removal, screening, and eligibility assessment, 30 empirical studies met the inclusion criteria. The selected studies employed experimental, quasi-experimental, survey, and mixed-method research designs to examine the relationship between vocabulary instruction and speaking development. The review categorized vocabulary development strategies into four major types: cognitive, metacognitive, memory-based, and technology-mediated approaches.
Table of Contents
1. INTRODUCTION
2. MATERIALS AND METHODS
2.1 Research Objectives
2.2 Research Design and Method
2.3 Data Collection Procedure
2.4 Data Analysis and Synthesis
3. RESULTS AND DISCUSSION
3.1 Cognitive Strategies
3.1.2 Metacognitive Strategies
3.1.3 Memory-Based Strategies
3.1.4 Activation Strategies
3.1.5 Integration of Technology in Vocabulary Strategies
3.2 Technology Integration in Vocabulary Learning
3.2.1 AI-Driven Tools
3.2.2 Gamified Learning Applications
3.2.3 Multimedia and Mobile Learning
3.2.4 Benefits of Technology Integration
3.2.5 Challenges and Considerations
3.2.6 Implications for Vocabulary and Speaking Development
3.3 Vocabulary–Speaking Performance Gap
3.3.1 Vocabulary Mastery and Fluency
3.3.2 Pronunciation Challenges
3.3.3 Passive vs. Active Vocabulary
3.4 Speaking Skill Outcomes
3.4.1 Vocabulary Use
3.6 Activation and Communicative Practice
3.6.1 Storytelling and Speaking Tasks
3.6.2 Video-Based Learning
3.6.3 Peer Interaction and Collaborative Tasks
3.7 Emerging Trends in Vocabulary Instruction (2020–2025)
3.7.1 Shift to Blended Learning
3.7.2 Constructivist and Socio-Cognitive Approaches
3.7.3 Digital and Interactive Pedagogy
4. Conclusion
Objectives and Research Themes
The primary objective of this review is to synthesize empirical evidence regarding how various vocabulary development strategies influence the speaking proficiency of senior high school learners in EFL/ESL contexts, specifically addressing the persistent gap between lexical knowledge and oral performance.
- Effects of cognitive, metacognitive, and memory-based vocabulary strategies on speaking performance.
- The role of technology-mediated approaches, including AI, gamification, and multimedia, in vocabulary instruction.
- Identification of contextual factors and pedagogical practices influencing speaking development outcomes.
- Analysis of the "vocabulary–speaking gap" and strategies to facilitate the transition to active oral communication.
- Evaluation of blended learning approaches in combining traditional and digital instruction.
Excerpt from the Book
3.2.1 AI-Driven Tools
AI-driven instructional tools—including intelligent tutoring systems, speech-recognition software, adaptive vocabulary applications, and automated pronunciation feedback systems—were consistently identified as effective in improving vocabulary acquisition and speaking performance among senior high school learners. Studies examining AI-assisted language learning environments reported improvements in pronunciation accuracy, contextual vocabulary usage, and oral fluency because learners received immediate corrective feedback during speaking activities (Yaasiin, 2025, pp. 31–35).
In particular, findings from the Ondo State study (2025, pp. 12–16) indicated that learners who used AI-supported vocabulary and speaking tools demonstrated stronger pronunciation accuracy and more effective oral vocabulary deployment than learners exposed only to traditional instructional approaches. The automated feedback mechanisms embedded in AI systems enabled learners to identify pronunciation errors, monitor lexical usage, and improve speaking accuracy through repeated guided practice.
Furthermore, AI-driven applications supported real-time language processing by helping learners retrieve and apply vocabulary more efficiently during oral communication tasks. These findings suggest that AI integration not only strengthens vocabulary retention but also facilitates the transition from vocabulary recognition to spontaneous spoken language production. However, the studies also emphasized that AI tools are most effective when integrated with teacher-guided communicative practice rather than used as isolated learning platforms.
Summary of Chapters
1. INTRODUCTION: Outlines the importance of speaking skills and the identified "vocabulary–speaking gap" among senior high school learners.
2. MATERIALS AND METHODS: Describes the PRISMA systematic review framework and the methodology used to select 30 empirical studies from 600 initial records.
3. RESULTS AND DISCUSSION: Synthesizes findings on various instructional strategies, technology integration, and factors influencing speaking proficiency.
4. Conclusion: Summarizes key evidence suggesting that blended learning and communicative practice are essential for bridging the gap between passive vocabulary knowledge and active oral production.
Keywords
vocabulary development strategies, speaking skills, senior high school learners, PRISMA systematic review, EFL/ESL learning, technology-mediated vocabulary instruction, communicative practice, AI-driven tools, gamified learning, blended learning, lexical competence, oral proficiency, vocabulary-speaking gap, pedagogical frameworks.
Frequently Asked Questions
What is the primary focus of this systematic review?
This review examines how different vocabulary development strategies affect the speaking proficiency of senior high school learners in EFL and ESL contexts, identifying effective instructional approaches and trends from 2020 to 2025.
What are the central themes of the research?
The research focuses on vocabulary instruction types, the integration of technology, the distinction between receptive and productive vocabulary, and the impact of communicative, activation-oriented tasks.
What is the main goal or research question?
The primary goal is to determine how vocabulary strategies influence speaking fluency, accuracy, and pronunciation, and to identify which instructional models best help learners transfer knowledge into spontaneous oral communication.
Which scientific methodology is used?
The study utilizes a systematic review design strictly guided by the PRISMA 2020 framework to identify, screen, evaluate, and synthesize empirical findings from academic databases.
What topics are covered in the main section?
The main section evaluates cognitive, metacognitive, and memory-based strategies, the impact of AI and gamified digital tools, and the role of activation strategies like storytelling and peer interaction.
Which keywords best characterize this work?
The work is characterized by terms such as vocabulary development strategies, PRISMA systematic review, technology-mediated instruction, senior high school learners, and the vocabulary–speaking gap.
How does AI specifically support speaking development?
AI tools provide immediate feedback on pronunciation and vocabulary use, allowing learners to identify errors in real-time and practice oral production repeatedly in a guided, non-judgmental environment.
Why is the "Vocabulary–Speaking Gap" significant?
It is significant because it highlights that strong receptive knowledge does not guarantee oral fluency, proving that traditional memorization-based vocabulary learning must be supplemented by communicative activation tasks.
- Quote paper
- Marwin Saplagio (Author), 2026, Vocabulary Development Strategies and their Effects on Speaking Skills of Senior High School Learners, Munich, GRIN Verlag, https://www.grin.com/document/1719397
