Microlearning in Language Education: A Systematic Review of Emerging Trends and Challenges (2014-2025).
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| Title: | Microlearning in Language Education: A Systematic Review of Emerging Trends and Challenges (2014-2025). |
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| Authors: | EKİZER, Feyza Nur1 fekizer@erbakan.edu.tr, ASMA, Burak2 burakasma@akdeniz.edu.tr |
| Source: | Hacettepe University Journal of Education. Jul2026, Vol. 41 Issue 3, p534-553. 20p. |
| Subject Terms: | *Microlearning, *Foreign language education, *Mobile learning, *Educational technology, *Digital divide, *Curriculum planning, *Cognitive load, Self-determination theory |
| Abstract: | The rapid evolution of technology and shifting learning preferences of digitally native generations have necessitated innovative pedagogical approaches in language education. This systematic review investigates the role of bite-sized learning, or microlearning, in addressing cognitive overload, enhancing engagement, and improving language acquisition outcomes. Through a systematic review of 65 studies [2014-2025 (July)], the study identifies dominant themes, methodological trends, outcomes, suggestions and implementation challenges. Findings reveal that microlearning significantly enhances retention, motivation, and skill acquisition by delivering content in concise, interactive formats aligned with Cognitive Load Theory and Self-Determination Theory. Experimental and quasi-experimental studies (32%) dominate the research landscape, demonstrating efficacy in vocabulary, grammar, and pronunciation training, while qualitative insights (29%) underscore its adaptability across educational contexts. Key platforms such as mobile apps (e.g., Duolingo) and social media (e.g., TikTok) leverage multimedia to foster engagement, particularly among Generation Y and Z learners. However, challenges persist, including content depth limitations, technological accessibility disparities, and a lack of structured pedagogical frameworks. The synthesis highlights microlearning's potential in curriculum redesign, teacher professional development, and post-pandemic educational transformation. Recommendations emphasize integrating interactive elements, balancing brevity with depth, and addressing digital divides. Despite its promise, gaps remain in long-term impact assessments, scalability, and higher-order skill development. This study advocates hybrid models that combine microlearning with traditional methods, AI-driven personalization, and equitable resource allocation to optimize its macro impact on language education. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
| Abstract: | The rapid evolution of technology and shifting learning preferences of digitally native generations have necessitated innovative pedagogical approaches in language education. This systematic review investigates the role of bite-sized learning, or microlearning, in addressing cognitive overload, enhancing engagement, and improving language acquisition outcomes. Through a systematic review of 65 studies [2014-2025 (July)], the study identifies dominant themes, methodological trends, outcomes, suggestions and implementation challenges. Findings reveal that microlearning significantly enhances retention, motivation, and skill acquisition by delivering content in concise, interactive formats aligned with Cognitive Load Theory and Self-Determination Theory. Experimental and quasi-experimental studies (32%) dominate the research landscape, demonstrating efficacy in vocabulary, grammar, and pronunciation training, while qualitative insights (29%) underscore its adaptability across educational contexts. Key platforms such as mobile apps (e.g., Duolingo) and social media (e.g., TikTok) leverage multimedia to foster engagement, particularly among Generation Y and Z learners. However, challenges persist, including content depth limitations, technological accessibility disparities, and a lack of structured pedagogical frameworks. The synthesis highlights microlearning's potential in curriculum redesign, teacher professional development, and post-pandemic educational transformation. Recommendations emphasize integrating interactive elements, balancing brevity with depth, and addressing digital divides. Despite its promise, gaps remain in long-term impact assessments, scalability, and higher-order skill development. This study advocates hybrid models that combine microlearning with traditional methods, AI-driven personalization, and equitable resource allocation to optimize its macro impact on language education. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 13005340 |
| DOI: | 10.16986/hunefd.1755298 |
