Needs Analysis of Mobile-Based Biology Microlearning for Senior High School Students: Student and Teacher Perspectives
Main Article Content
Abstract
Learning biology, particularly cells and metabolism, requires students to understand structures, sequences, and dynamic processes that are difficult to observe directly. This study aimed to analyze students’ and teachers’ needs as a basis for developing mobile-based biology microlearning for senior high school students. A descriptive needs analysis involved 31 Grade 11 students in the Mathematics and Natural Sciences track and three biology teachers at SMA Negeri 23 Makassar. Closed-ended data were analyzed using frequencies, percentages, means, and standard deviations, while open-ended responses were coded descriptively. Smartphones were the primary student devices (77.4%), and videos of 3–5 minutes were the most preferred duration (51.6%). All students needed offline access, 93.5% needed subtitles, and 90.3% agreed that short, stepwise materials could support their focus. The most frequently identified difficult topics were enzyme and coenzyme inhibition (32.3%), light-dependent reactions of photosynthesis (29.0%), and the fluid mosaic model of cell membranes (22.6%). Teachers emphasized dynamic media, curriculum-aligned materials, editable resources, formative question banks, data-efficient materials, and technical support, while only one teacher reported confidence in creating simple digital materials. The findings indicate that the initial design should provide 3–5-minute single-concept segments, 360p–480p video options, offline access, subtitles and transcripts, stepwise visualizations, and short quizzes with explanatory feedback. The study provides context-sensitive initial specifications for mobile-based biology microlearning, which should be followed by content validation, prototype development, usability testing, and effectiveness evaluation.
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
Authors retain copyright and grant the journal the right of first publication. Articles are distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
Al-Zahrani, A. M. (2024). Enhancing postgraduate students’ learning outcomes through flipped mobile-based microlearning. Research in Learning Technology, 32, Article 3110. https://doi.org/10.25304/rlt.v32.3110
Alias, N. F., & Razak, R. A. (2023). Exploring the pedagogical aspects of microlearning in educational settings: A systematic literature review. Malaysian Journal of Learning and Instruction, 20(2), 267-294. https://doi.org/10.32890/mjli2023.20.2.3
Bai, S., Hew, K. F., & Huang, B. (2020). Does gamification improve student learning outcome? Evidence from a meta-analysis and synthesis of qualitative data in educational contexts. Educational Research Review, 30, Article 100322. https://doi.org/10.1016/j.edurev.2020.100322
Bernacki, M. L., Greene, J. A., & Crompton, H. (2020). Mobile technology, learning, and achievement: Advances in understanding and measuring the role of mobile technology in education. Contemporary Educational Psychology, 60, Article 101827. https://doi.org/10.1016/j.cedpsych.2019.101827
Carpenter, S. K., Pan, S. C., & Butler, A. C. (2022). The science of effective learning with spacing and retrieval practice. Nature Reviews Psychology, 1, 496-511. https://doi.org/10.1038/s44159-022-00089-1
Çeken, B., & Ta?k?n, N. (2022). Multimedia learning principles in different learning environments: A systematic review. Smart Learning Environments, 9, Article 19. https://doi.org/10.1186/s40561-022-00200-2
Crompton, H., & Burke, D. (2020). Mobile learning and pedagogical opportunities: A configurative systematic review of PreK-12 research using the SAMR framework. Computers & Education, 156, Article 103945. https://doi.org/10.1016/j.compedu.2020.103945
Cruz, E. P. F., Gomes, G. R. R., & Azevedo Filho, E. T. (2022). Microlearning como uma nova abordagem tecnopedagógica: Uma revisão. Research, Society and Development, 11(6), Article e47611629548. https://doi.org/10.33448/rsd-v11i6.29548
El Hammoumi, S., Zerhane, R., & Janati Idrissi, R. (2022). The impact of using interactive animation in biology education at Moroccan universities and students’ attitudes towards animation and ICT in general. Social Sciences & Humanities Open, 6(1), Article 100293. https://doi.org/10.1016/j.ssaho.2022.100293
Falloon, G. (2020). From digital literacy to digital competence: The teacher digital competency (TDC) framework. Educational Technology Research and Development, 68, 2449-2472. https://doi.org/10.1007/s11423-020-09767-4
Farrokhnia, M., Meulenbroeks, R. F. G., & van Joolingen, W. R. (2020). Student-generated stop-motion animation in science classes: A systematic literature review. Journal of Science Education and Technology, 29, 797-812. https://doi.org/10.1007/s10956-020-09857-1
Global Education Monitoring Report Team. (2023). Global education monitoring report 2023: Technology in education—A tool on whose terms? UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000385723
Haagsman, M. E., Scager, K., Boonstra, J., & Koster, M. C. (2020). Pop-up questions within educational videos: Effects on students’ learning. Journal of Science Education and Technology, 29, 713-724. https://doi.org/10.1007/s10956-020-09847-3
König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608-622. https://doi.org/10.1080/02619768.2020.1809650
Lee, Y.-M. (2023). Mobile microlearning: A systematic literature review and its implications. Interactive Learning Environments, 31(7), 4636-4651. https://doi.org/10.1080/10494820.2021.1977964
Mayer, R. E. (2020). Multimedia learning (3rd ed.). Cambridge University Press.
Monib, W. K., Qazi, A., & Apong, R. A. (2025). Microlearning beyond boundaries: A systematic review and a novel framework for improving learning outcomes. Heliyon, 11(2), Article e41413. https://doi.org/10.1016/j.heliyon.2024.e41413
Noetel, M., Griffith, S., Delaney, O., Sanders, T., Parker, P., del Pozo Cruz, B., & Lonsdale, C. (2021). Video improves learning in higher education: A systematic review. Review of Educational Research, 91(2), 204-236. https://doi.org/10.3102/0034654321990713
Nowak, G., Speed, O., & Vuk, J. (2023). Microlearning activities improve student comprehension of difficult concepts and performance in a biochemistry course. Currents in Pharmacy Teaching and Learning, 15(1), 69-78. https://doi.org/10.1016/j.cptl.2023.02.010
Patterson, K., Terrill, B., Dorfman, B.-S., Blonder, R., & Yarden, A. (2022). Molecular animations in genomics education: Designing for whom? Trends in Genetics, 38(6), 517-520. https://doi.org/10.1016/j.tig.2022.03.003
Ploetzner, R., Berney, S., & Bétrancourt, M. (2021). When learning from animations is more successful than learning from static pictures: Learning the specifics of change. Instructional Science, 49(4), 497-514. https://doi.org/10.1007/s11251-021-09541-w
Sailer, M., & Homner, L. (2020). The gamification of learning: A meta-analysis. Educational Psychology Review, 32(1), 77-112. https://doi.org/10.1007/s10648-019-09498-w
Sankaranarayanan, R., Leung, J., Abramenka-Lachheb, V., Seo, G., & Lachheb, A. (2023). Microlearning in diverse contexts: A bibliometric analysis. TechTrends, 67(2), 260-276. https://doi.org/10.1007/s11528-022-00794-x
Scherer, R., Howard, S. K., Tondeur, J., & Siddiq, F. (2021). Profiling teachers’ readiness for online teaching and learning in higher education: Who’s ready? Computers in Human Behavior, 118, Article 106675. https://doi.org/10.1016/j.chb.2020.106675
Smestad, B., Hatlevik, O. E., Johannesen, M., & Øgrim, L. (2023). Examining dimensions of teachers’ digital competence: A systematic review pre- and during COVID-19. Heliyon, 9(6), Article e16677. https://doi.org/10.1016/j.heliyon.2023.e16677
Strømme, T. A., & Mork, S. M. (2021). Students’ conceptual sense-making of animations and static visualizations of protein synthesis: A sociocultural hypothesis explaining why animations may be beneficial for student learning. Research in Science Education, 51(4), 1013-1038. https://doi.org/10.1007/s11165-020-09920-2
UNICEF, & International Telecommunication Union. (2020). How many children and young people have internet access at home? Estimating digital connectivity during the COVID-19 pandemic. UNICEF. https://www.unicef.org/reports/how-many-children-and-young-people-have-internet-access-home-2020
Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, Article 3087. https://doi.org/10.3389/fpsyg.2019.03087
Yang, C., Luo, L., Vadillo, M. A., Yu, R., & Shanks, D. R. (2021). Testing (quizzing) boosts classroom learning: A systematic and meta-analytic review. Psychological Bulletin, 147(4), 399-435. https://doi.org/10.1037/bul0000309
Yang, L., García-Holgado, A., & Martínez-Abad, F. (2023). Digital competence of K-12 pre-service and in-service teachers in China: A systematic literature review. Asia Pacific Education Review, 24, 679-693. https://doi.org/10.1007/s12564-023-09888-4.