Journals / Hacettepe Üniversitesi Eğitim Fakültesi Dergisi / 2026 / Cilt: 41 Sayı: 3

Microlearning in Language Education: A Systematic Review of Emerging Trends and Challenges (2014-2025)

Dil Öğretiminde Mikro Öğrenme: Yeni Eğilimler ve Karşılaşılan Güçlükler Üzerine Sistematik Tematik Bir İnceleme

Feyza Nur Ekizer(NECMETTİN ERBAKAN ÜNİVERSİTESİ)0000-0003-0568-5355
Burak Asma(AKDENİZ ÜNİVERSİTESİ, EĞİTİM FAKÜLTESİ)0000-0002-3602-3867
Pages
534–553
Publication Date
2026-07-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The rapid evolution of technology and shifting learning preferences of digitally native generations have necessitated innovative pedagogical approaches in language education.
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Key Findings & Data:Through a systematic review of 65 studies [2014–2025 (July)], the study identifies dominant themes, methodological trends, outcomes, suggestions and implementation challenges.
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Conclusion & Impact: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.
🔬Design:Review & Systematic Survey
📍Scope:2014–2025 Verileri
⚙️Variables:Mikro öğrenme · dil öğretimi · tematik analiz

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.

Özet

Teknolojinin hızlı evrimi ve dijital yerliler olarak adlandırılan kuşakların değişen öğrenme tercihleri, dil eğitiminde yenilikçi pedagojik yaklaşımların benimsenmesini zorunlu kılmıştır. Bu sistematik tematik analiz, bilişsel yükü azaltma, öğrenen katılımını artırma ve dil edinimi sonuçlarını iyileştirme bağlamında mikro öğrenme yaklaşımının rolünü incelemektedir. 2014–2025 yılları arasında yayımlanmış 65 çalışmanın sistematik tematik analizi yoluyla öne çıkan temalar, yöntemsel eğilimler, elde edilen bulgular, öneriler ve uygulamaya yönelik zorluklar ortaya konmuştur. Bulgular, mikro öğrenmenin, Bilişsel Yük Kuramı ve Öz Belirleme Kuramı ile uyumlu biçimde yapılandırılmış kısa ve etkileşimli içerikler sunarak öğrenmenin kalıcılığı, motivasyonu ve beceri edinimini anlamlı ölçüde artırdığını göstermektedir. Araştırma alanında deneysel ve yarı-deneysel çalışmalar (%32) ön plana çıkmakta; bu çalışmalar mikro öğrenmenin kelime bilgisi, dil bilgisi ve telaffuz öğretimindeki etkinliğini ortaya koymaktadır. Nitel bulgular (%29) ise bu yaklaşımın farklı eğitim bağlamlarına uyarlanabilirliğini vurgulamaktadır. Duolingo gibi mobil uygulamalar ve TikTok gibi sosyal medya platformları, özellikle Y ve Z kuşağı öğrencileri arasında etkileşimi artırmak için çoklu ortam olanaklarından faydalanmaktadır. Bununla birlikte, içerik derinliği sınırlılıkları, teknolojik erişim eşitsizlikleri ve yapılandırılmış pedagojik çerçeve eksiklikleri gibi sorunlar devam etmektedir. Yapılan analiz, mikro öğrenmenin müfredat yeniden tasarımı, öğretmenlerin mesleki gelişimi ve pandemi sonrası eğitim dönüşümünde önemli bir potansiyel taşıdığını ortaya koymaktadır. Çalışmada, etkileşimli unsurların öğrenme süreçlerine entegre edilmesi, içerik sunumunda kısalık ile derinlik arasında denge sağlanması ve dijital erişim eşitsizliklerinin giderilmesi yönünde öneriler sunmaktadır. Mikro öğrenme umut verici bulgular ortaya koymakla birlikte, bu yaklaşımın uzun vadeli etkileri, geniş ölçekli uygulanabilirliği ve üst düzey bilişsel becerilerin geliştirilmesine katkısı konularında hâlâ önemli boşluklar bulunmaktadır. Bu doğrultuda çalışma, mikro öğrenmenin geleneksel öğretim yöntemleriyle harmanlandığı, yapay zekâ destekli kişiselleştirme olanaklarının sunulduğu ve eğitim kaynaklarının adil biçimde dağıtıldığı hibrit modellerin benimsenmesinin, dil eğitiminde daha kapsamlı ve sürdürülebilir etkiler yaratabileceğini ortaya koymaktadır.

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Cite This Article

Ekizer, F. N., Asma, B. (2026). Microlearning in Language Education: A Systematic Review of Emerging Trends and Challenges (2014-2025). Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, Cilt: 41 Sayı: 3, 534–553. https://doi.org/10.16986/hunefd.1755298

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References (74)

  1. Alfitri, B. (2025). The impact of short-form content TikTok on English language learning development among Generation Z: A case study of students at Institut Elkatarie. Majapahit Journal of English Studies, 1(2), 156–173. https://doi.org/10.69965/mjes.v1i2.103
  2. Alias, N. F., & Abdul Razak, R. (2023). Exploring the pedagogical aspects of microlearning in educational settings: A systematic literature review. Malaysian Journal of Learning and Instruction (MJLI), 20(2), 267-294. https://doi.org/10.32890/ Anmarkrud, Ø., Andresen, A., & Bråten, I. (2019). Cognitive load and working memory in multimedia learning: Conceptual and measurement issues. Educational psychologist, 54(2), 61-83. https://doi.org/10.1080/00461520.2018.1554484
  3. Baddeley, A. (2000). Short-term and working memory. In E. Tulving, & F. I. M. Craik (Eds.), The Oxford Handbook of Memory (pp. 77-92). Oxford University Press.
  4. Bruck, P. A., Motiwalla, L., & Foerster, F. (2012, June 17 to 20). Mobile learning with micro content: A framework and evaluation [Conference paper]. 25th Bled eConference eDependability: Reliable and Trustworthy eStructures, eProcesses, eOperations and eServices for the Future, Bled, Slovenia.
  5. Buchem, I., & Hamelmann, H. (2010). Microlearning: A Strategy for Ongoing Professional Development. eLearning Papers, (21), 1-15.
  6. Byrne, M. D. (2025). Nanolearning: Breaking materials into small but powerful moments of learning. Nursing Education Perspectives, 46(2), 137-137. https://doi.org/10.1097/01.nep.0000000000001387
  7. Castellano, G., Cimino, M. G., Fanelli, A. M., Lazzerini, B., Marcelloni, F., & Torsella, M. O. (2014). A multi-agent system for enabling collaborative situation awareness via position-based stigmergy and neuro-fuzzy learning. Neurocomputing, 135, 86-97. https://doi.org/10.1016/j.neucom.2013.03.066
  8. Cepeda, N. J., Pashler, H., Vul, E., Wixted, J.T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132, 354–380. https://doi.org/10.1037/0033-2909.132.3.354
  9. Chen, Y., & Sitthiworachart, J. (2024). Research on the problems and development of micro-learning in English vocabulary curriculum. Educational Administration: Theory and Practice, 30(3),284-300. https://doi.org/10.52152/kuey.v30i3.896
  10. Chikhi, H., & Guettaf, C. (2023). EFL teachers’ views and learners’ attitudes towards the use of TikTok as a microlearning tool in the department of English at Mouloud Mammeri University of Tizi-Ouzou: A survey study (Master’s thesis). Mouloud Mammeri University of Tizi-Ouzou.
  11. Cronin, J., & Durham, M. L. (2024). Microlearning: a concept analysis. CIN: Computers, Informatics, Nursing, 42(6), 413-420. https://doi.org/10.1097/cin.0000000000001122
  12. Cowan, N. (2010). The magical mystery four: How is working memory capacity limited, and why? Current Directions in Psychological Science, 19(1), 51–57. https://doi.org/10.1177/0963721409359277
  13. Çeken, B., & Taşkın, N. (2022). Multimedia learning principles in different learning environments: A systematic review. Smart Learning Environments, 9(19), 1-22. https://doi.org/10.1186/s40561-022-00200-2
  14. Dakhi, O., Jama, J., & Irfan, D. (2020). Blended learning: a 21st century learning model at college. International Journal of Multi Science, 1(08), 50-65. https://multisciencejournal.com/index.php/ijm/article/view/92
  15. Darby, F., & Lang, J. M. (2019). Small teaching online: Applying learning science in online classes. Jossey-Bass and Pfeiffer.
  16. Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227–268. https://doi.org/10.1207/S15327965PLI1104_01
  17. Deocampo, M. F. (2024). Microteaching reflective practices to enhance the teaching efficacy of English language pre-service teachers. IDA Journal of Language and Communication, 29(46), 1-22. https://so04.tci-thaijo.org/index.php/NJLC/article/view/280612
  18. Dwinggo Samala, A., Bojić, L., Bekiroğlu, D., Watrianthos, R., & Hendriyani, Y. (2023). Microlearning: Transforming education with bite-sized learning on the go—insights and applications. International Journal of Interactive Mobile Technologies (iJIM), 17(21),4-24. https://doi.org/10.3991/ijim.v17i21.42951
  19. Fidan, M. (2023). The effects of microlearning-supported flipped classroom on pre-service teachers’ learning performance, motivation and engagement. Education and Information Technologies, 28, 12687–12714. https://doi.org/10.1007/s10639-023-11639-2
  20. Ghanbari, S., Haghani, F., Barekatain, M., & Jamali, A. (2020). A systematized review of cognitive load theory in health sciences education and a perspective from cognitive neuroscience. Journal of Education and Health Promotion, 9(1), 176. https://doi.org/10.4103/jehp.jehp_643_19
  21. Gohar, R. (2023). A microlearning ESP program to develop university students’ vocabulary and reduce their cognitive load. CDELT Occasional Papers in the Development of English Education, 83(1), 453–476. https://doi.org/10.21608/opde.2023.325342
  22. Gorham, T., Majumdar, R., & Ogata, H. (2023). Analyzing learner profiles in a microlearning app for training language learning peer feedback skills. Journal of Computers in Education, 10, 549–574. https://doi.org/10.1007/s40692-023-00264-0
  23. Grovo. (2015). Bite size is the right size: how microlearning shrinks the skills gap in higher education. www.trainingindustry.com/content-development/articles/bite-size-isthe-right-size-how-microlearning-shrinks-the-skills-gap.aspx.
  24. Gusenbauer, M., & Haddaway, N. R. (2020). Which academic search systems are suitable for systematic reviews or meta‐analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Research Synthesis Methods, 11(2), 181–217. https://doi.org/10.1002/jrsm.1378
  25. Hallson, T. L., Drumheller, K., Mallard, J., McKee, C., & Schlegel, P. (2013). Cell phones, text messaging, and Facebook: Competing time demands of today's college students. College Teaching, 59(1), 23-30. http://dx.doi.org/10.1080/87567555.2010.489078
  26. Hanley, T., & Cutts, L. (2013). What is a systematic review? Counselling Psychology Review, 28(4), 3-6.
  27. Hug, T. (2007). Didactics of microlearning. Waxmann Verlag.
  28. Huo, C. Q., & Shen, B. G. (2015). Teaching reform of English listening and speaking in China based on mobile micro-learning. Creative Education, 6, 2221–2226. https://doi.org/10.4236/ce.2015.620228
  29. Job, M. A., & Ogalo, H. S. (2012). Micro learning as innovative process of knowledge strategy. International journal of scientific & technology research, 1(11), 92-96.
  30. Jomah, O., Masoud, A., Kishore, X. P., & Aurelia, S. (2016). Micro learning: A modernized education system: BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 7(1), 103-110. https://www.edusoft.ro/brain/index.php/brain/article/view/582
  31. Kamel, O.M. (2018). Academic overload, self-efficacy and perceived social support as predictors of academic adjustment among first year university students. International Journal of Psycho-Educational Sciences, 7(1), 86-93. https://files.eric.ed.gov/fulltext/ED585260.pdf
  32. Kang, S. H. K. (2016). Spaced repetition promotes efficient and effective learning: Policy implications for instruction. Policy Insights from the Behavioral and Brain Sciences, 3(1), 12-19. https://doi.org/10.1177/2372732215624708
  33. Kapp, K. M., & Defelice, R. A. (2015). Microlearning: Short and sweet. ATD Press.
  34. Klepsch, M., & Seufert, T. (2021). Making an effort versus experiencing load. Frontiers in Education (6), 645284.https://doi.org/10.3389/feduc.2021.645284
  35. Kloos, C. D., Pardo, A., Muñoz-Merino, P. J., Gutiérrez, I., & Leony, D. (2013). Learning Analytics. 2013 IEEE Global Engineering Education Conference (EDUCON). Berlin, Germany. https://doi.org/10.1109/educon.2013.6530264
  36. Koh, N. S., Gottipati, S., & Shankararaman, V. (2018). Effectiveness of bite-sized lecture on student learning outcomes. In 4th International Conference on Higher Education Advances (HEAd'18) (pp. 515-523). Universitat Politècnica de València. https://doi.org/10.4995/HEAd18.2018.8027
  37. Kohnke, L., Foung, D., & Zou, D. (2024). Microlearning: A new normal for flexible teacher professional development in online and blended learning. Education and Information Technologies, 29, 4457–4480. https://doi.org/10.1007/s10639-023-11964-6
  38. Kohnke, L., & Foung, D. (2023). Exploring microlearning for CALL teacher education and professional development: Voices from Hong Kong. In Tafazoli, D. & Picard, M. (Eds.), CALL Teacher Education and Professional Development: Voices from Under-Represented Context (pp. 279–312). Springer. https://doi.org/10.1007/978-981-99-0514-0_17.
  39. Kohnke, L., & Moorhouse, B. L. (2024). An exploration of microlearning as continuous professional development for English language teachers: Initial findings and insights. Open Learning: The Journal of Open, Distance and e-Learning, 1–17. https://doi.org/10.1080/02680513.2024.2362649 Kuleto, V., P, M. I., Stanescu, M., Ranković, M., Šević, N. P., Păun, D., & Teodorescu, S. (2021). Extended reality in higher education, a responsible innovation approach for generation Y and generation Z. Sustainability, 13(21), 11814. https://doi.org/10.3390/su132111814
  40. Landis, J. R., & Koch, G. G. (1977). An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics, 3(2), 363-374. https://doi.org/10.2307/2529786
  41. Lever-Duffy, J., McDonald, J., & Mizell, A. (2003). Teaching and learning with technology. Pearson Education.
  42. Li, L., & Chinokul, S. (2024). Effects of online vocabulary instruction using nano authentic videos on young Chinese EFL learners’ vocabulary knowledge. Kasetsart Journal of Social Sciences, 45(4), 1414–1424. https://so04.tci-thaijo.org/index.php/kjss/article/view/277023
  43. Lopez, S. (2024). The impact of cognitive load theory on the effectiveness of microlearning modules. European Journal of Education and Pedagogy, 5(2), 29-35. https://doi.org/10.24018/ejedu.2024.5.2.799
  44. Manning, K. D., Spicer, J. O., Akbashev, M., & Klein, R. (2021). The micro revolution: effect of Bite-Sized Teaching (BST) on learner engagement and learning in postgraduate medical education. BMC Medical Education, 21(69),1-11. https://doi.org/10.1186/s12909-021-02496-z
  45. Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press.
  46. Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. https://doi.org/10.1207/S15326985EP3801_6
  47. Mazlan, C. N., Abdullah, M. H., Sulong, M. A., Abas, A., Ramdan, M. R., Safian, A. R. Fuad, D. R. (2023). Exploring the integration of bite-sized learning: A scoping review of research in education and related disciplines. Contemporary Educational Technology, 15(4), ep468. https://doi.org/10.30935/cedtech/13622.
  48. Meirbekov, A., Nyshanova, S., Meiirbekov, A., Kazykhankyzy, L., Burayeva, Z., & Abzhekenova, B. (2024). Digitisation of English language education: Instagram and TikTok online educational blogs and courses vs. traditional academic education. How to increase student motivation?. Education and Information technologies, 29(11), 13635-13662. https://doi.org/10.1007/s10639-023-12396-y
  49. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97. https://doi.org/10.1037/h0043158
  50. Mirra, N., Morrell, E., & Filipiak, D. (2018). From digital consumption to digital invention: Toward a new critical theory and practice of multiliteracies. Theory Into Practice, 57(1), 12-19. https://doi.org/10.1080/00405841.2017.1390336
  51. Mostrady, A., Sanchez-Lopez, E., & Gonzalez-Sanchez, A. F. (2025). Microlearning and its effectiveness in modern education: A mini review. Acta Pedagogia Asiana, 4(1), 33-42. https://doi.org/10.53623/apga.v4i1.496
  52. Murtianto, Y., Herlambang, B., & Muhtarom, M. (2022). Cognitive load theory on virtual mathematics laboratory: Systematic literature review. KnE Social Sciences, 7(19), 42–55. https://doi.org/10.18502/kss.v7i19.12461
  53. Ojochegbe, A. T. (2025). Tiny steps, giant leaps: The place of micro-learning in language and literature. Journal of World Science, 4(1), 1772–1781. https://doi.org/10.58344/jws.v4i1.1277
  54. Omona, K., & O'dama, M. K. (Eds.). (2024). Global perspectives on micro-learning and micro-credentials in higher education. IGI Global.
  55. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D.,. & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, (71). https://doi.org/10.1136/bmj.n71
  56. Pham, A. T. V., & Le, L. T. T. (2023). Students' perceptions towards Duolingo app as a microlearning tool. In Proceedings of the 2023 5th World Symposium on Software Engineering (pp. 213–217). Association for Computing Machinery. https://doi.org/10.1145/3631991.3632026
  57. Plass, J.L., Kalyuga, S. (2019). Four ways of considering emotion in cognitive load theory. Educational Psychology Review, 31, 339–359. https://doi.org/10.1007/s10648-019-09473-5
  58. Seemiller, C., & Grace, M. (2017a). Generation Z goes to college. John Wiley & Sons. Seemiller, C., & Grace, M. (2017b). Generation Z: Educating and engaging the next generation of students. About campus, 22(3), 21-26. https://doi.org/10.1002/abc.21293
  59. Shatte, A. B. R., & Teague, S. (2020). Microlearning for improved student outcomes in higher education: A scoping review. Open Science Framework. https://doi.org/10.31219/osf.io/fhu8n
  60. Shay, J. E., & Pohan, C. (2021). Resilient instructional strategies: helping students cope and thrive in crisis. Journal of microbiology & biology education, 22(1), 1-8. https://doi.org/10.1128/jmbe.v22i1.2405
  61. Sharp, J. L. L. (2023). A quasi-experimental study on the effect of course modality on learning transfer of skydiving teachers-in-training: A solomon four-group design. National University.
  62. Skulmowski, A., & Xu, K. M. (2022). Understanding cognitive load in digital and online learning: A new perspective on extraneous cognitive load. Educational psychology review, 34(1), 171-196. https://doi.org/10.1007/s10648-021-09624-7
  63. Stillman, D., & Stillman, J. (2017). Gen Z @ work: How the next generation is transforming the workplace. Harper Business.
  64. Sugiarto, J., Widjanarko, W., & Rosidi, M. I. (2024). Innovations in technology-based learning to enhance 21st century competencies. Indonesian Journal of Education (INJOE), 4(3), 1002-1010. https://felifa.net/index.php/INJOE/article/view/253
  65. Sunley, R., Moloney, K., Parker, J., Arrowsmith, C., Brown, K., & Wilson, A. (2017). Mini Sim’ – innovative bite sized simulation teaching in a busy children’s emergency department. Emergency Medicine Journal, 34, A899-A900. https://doi.org/10.1136/emermed-2017-207308.55
  66. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
  67. Sweller, J., van Merriënboer, J. J. G., & Paas, F. (2019). Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, 31(2), 261–292. https://doi.org/10.1007/s10648-019-09465-5
  68. Wongsirisrisakul, S., & Anchunda, H. Y. (2023). A study of learning achievement using micro-learning grammar lessons through Facebook classroom for grade 8 students of Bansuankwan School, Uthai Thani. Journal of Graduate MCU KhonKaen Campus, 10(2), 128–139. https://so02.tci-thaijo.org/index.php/jg-mcukk/article/view/261567
  69. Yazıcıoğlu, T., & Dodur, H. M. S. (2023). The effect of bite-sized learning on teachers’ qualifications to prepare individualized educational program. Journal of Kırşehir Education Faculty, 24(2), 1500–1528. https://doi.org/10.29299/kefad.1268333
  70. Young, J. Q., Van Merrienboer, J., Durning, S., & Ten Cate, O. (2014). Cognitive load theory: implications for medical education: AMEE Guide No. 86. Medical teacher, 36(5), 371-384. https://doi.org/10.3109/0142159x.2014.889290
  71. Zhang, Y., Zhang, M., Wu, L., & Li, J. (2025). digital transition framework for higher education in AI-assisted engineering teaching: Challenge, strategy, and initiatives in China. Science & Education, 34(2), 933-954. https://doi.org/10.1007/s11191-024-00575-3?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle
  72. Zhu, B., Chau, K. T., & Mokmin, N. A. M. (2024). Optimizing cognitive load and learning adaptability with adaptive microlearning for in-service personnel. Scientific Reports, 14(1), 25960. https://doi.org/10.1038/s41598-024-77122-1
  73. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D.,. & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, (71). https://doi.org/10.1136/bmj.n71
  74. Shay, J. E., & Pohan, C. (2021). Resilient instructional strategies: helping students cope and thrive in crisis. Journal of microbiology & biology education, 22(1), 1-8. https://doi.org/10.1128/jmbe.v22i1.2405