Learning styles and academic performance in technology-mediated educational environments: a systematic review
Estilos de aprendizaje y rendimiento académico en entornos educativos mediados por tecnología: revisión sistemáticaMain Article Content
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Abouhashesh, M. R. I., Abdelrhman, S. A. A. M., & Kahouf, S. A. E. (2025). The effect of the interaction between learning style (surface/deep) and content presentation mode (conditional/flexible) in an adaptive learning environment on acquiring computer maintenance skills and developing analytical thinking among educational. Scientific Culture, 11(3.2), 1206–1235. https://doi.org/10.5281/zenodo.18422007
Ali, K., Haggag, S., & Nassereddiene, M. (2025). Learning style differences between mechanical and electrical engineering students. International Journal of Mechanical Engineering Education. https://doi.org/10.1177/03064190251376271
Alshammari, M. T. (2020). Design and evaluation of an adaptive framework for virtual learning environments. International Journal of Advanced and Applied Sciences, 7(5), 39–51. https://doi.org/10.21833/ijaas.2020.05.006
Al-Shdaifat, I. M., Obeidat, L. M., Mabdeh, S. N., Alzoubi, L., & Al-Khazaleh, S. H. (2023). Integrating video feedback into architectural design education to engage diverse learning styles. Cogent Engineering, 10(2). https://doi.org/10.1080/23311916.2023.2269651
Chikasha, S., Petegem, W. V., & Valcke, M. (2022). Impact of alternative designs of multimedia elaboration on learning outcomes: Towards personalized learning of Software Engineering. IEEE Global Engineering Education Conference, EDUCON, 2022-March, 2104–2113. https://doi.org/10.1109/educon52537.2022.9766676
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. Learning and Skills Research Centre. https://www.leerbeleving.nl/wp-content/uploads/2011/09/learning-styles.pdf
Faathima Fayaza, M. S., & Ahangama, S. (2024). Use of felder silverman learning style model in technology enhanced learning. Proceedings - International Research Conference on Smart Computing and Systems Engineering, SCSE 2024. https://doi.org/10.1109/SCSE61872.2024.10550775
Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in engineering education. Engineering Education, 78(7), 674–681. https://engr.ncsu.edu/wp-content/uploads/drive/1QP6kBI1iQmpQbTXL-08HSl0PwJ5BYnZW/1988-LS-plus-note.pdf
Fleming, N. D., & Mills, C. (1992). Not Another Inventory, rather a catalyst for reflection. To Improve the Academy, 11(1), 137–155. https://doi.org/10.1002/j.2334-4822.1992.tb00213.x
Galon, D. I. (2024). The impact of distance learning on tourism and hospitality education during the SARS-CoV-2 pandemic in Region VI, Western Visayas. International Journal of Advanced and Applied Sciences, 11(10), 1–6. https://doi.org/10.21833/ijaas.2024.10.001
Garcia-Suarez, D., Guzmán Guzmán, B. R., Hernández Alamillo, C. A., & Martínez Ludet- Muñoz De Cote, E. P. (2025). AI-Driven Personalized Learning Profiles to Enhance Student Performance in Basic Physics: A Pilot Study. IEEE Global Engineering Education Conference, EDUCON. https://doi.org/10.1109/educon62633.2025.11016294
Geng, Y., & Jin, M. (2026). AI-powered recommendation and task assignment mechanism for interactive vocational English teaching. International Journal of Information and Communication Technology, 27(11), 1–17. https://doi.org/10.1504/ijict.2026.151714
Gertner, Y., Alvarez, J., Cosman, B., & Amos, J. R. (2022). Work in progress: Understanding student learning profiles in second-year problem-solving engineering classes. ASEE Annual Conference and Exposition, Conference Proceedings. https://doi.org/10.18260/1-2--40598
Girón-García, C., & Gargallo-Camarillas, N. (2023). The effects of an online task on legal English students’ perceptual learning styles and academic achievement [Los efectos de una tarea online en los estilos de aprendizaje perceptivos y en el rendimiento académico de estudiantes de inglés jurídico]. Cultura, Lenguaje y Representación, 30, 107–130. https://doi.org/10.6035/clr.6537
Hakim, A. R., Degeng, I. N. S., Kamdi, W., & Soepriyanto, Y. (2025). Design Thinking-based Adaptive Web Learning System for Science Education with Visual and Verbal Learning Modes. Online Learning in Educational Research, 5(2), 425–439. https://doi.org/10.58524/oler.v5i2.895
Huamani, G. T., & Inga, P. M. T. (2021). WIP Adaptive evaluation for a systems theory course according to the learning context. EDUNINE 2021 - 5th IEEE World Engineering Education Conference: The Future of Engineering Education: Current Challenges and Opportunities, Proceedings. https://doi.org/10.1109/edunine51952.2021.9429166
Huang, T., Li, M., Qin, Y., Zhong, H., & Deng, Y. (2025). Research on Hybrid Learning Behavior Pattern Recognition Based on K-means Clustering and Random Forest. Proceedings of 2025 International Conference on Educational Technology and Artificial Intelligence, ETAIC 2025, 184–191. https://doi.org/10.1145/3766557.3766589
Idrizi, E., Filiposka, S., & Trajkovikj, V. (2023). Gender impact on STEM online learning- a correlational study of gender, personality traits and learning styles in relation to different online teaching modalities. Multimedia Tools and Applications, 82(19), 30201–30219. https://doi.org/10.1007/s11042-023-14908-x
Ifenthaler, D., & Yau, Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Imanian, N., Havas, S., & Moradi, P. (2022). Adaptive educational games based on recommendation strategy and learning style identification. 9th International and the 15th National Conference E-Learning and E-Teaching, ICELET 2022. https://doi.org/10.1109/icelet55619.2022.9765415
Isaza Domínguez, L. G., Robles-Gómez, A., & Pastor-Vargas, R. (2025). A data-driven approach to engineering instruction: Exploring learning styles, study habits, and machine learning. IEEE Access, 13, 10978–11002. https://doi.org/10.1109/access.2025.3528263
Jalinus, N., Ganefri, Zaus, M. A., Wulansari, R. E., Nabawi, R. A., & Hidayat, H. (2022). Hybrid and Collaborative Networks Approach: Online Learning Integrated Project and Kolb Learning Style in Mechanical Engineering Courses. International Journal of Online and Biomedical Engineering, 18(15), 4–16. https://doi.org/10.3991/ijoe.v18i15.34333
Kadam, P. R., Gaikwad, U. K., & Bhamre, P. D. (2021). Student centred learning using student’s learning style. Journal of Engineering Education Transformations, 34(Special Issue), 391–395. https://doi.org/10.16920/jeet/2021/v34i0/157185
Kapetanaki, A., Krouska, A., Troussas, C., & Sgouropoulou, C. (2021). A novel framework incorporating augmented reality and pedagogy for improving reading comprehension in special education. Frontiers in Artificial Intelligence and Applications, 338, V–VI. https://doi.org/10.3233/faia210081
Kaur, R., Saini, S. K., Saini, R., Aggarwal, V., Sandeep Vasekara, P., & Kaveyan, K. (2025). Harnessing Disruptive Technologies in Education: The Role of AI, VR/AR, Blockchain, IoT, and Adaptive Learning Platforms. 2025 International Conference on Artificial Intelligence and Data Engineering, AIDE 2025 - Proceedings, 353–358. https://doi.org/10.1109/aide64228.2025.10986860
Kendaganna Swamy, S., Subramanya, K. N., Rajasree, P. M., Veena Divya, K., & Uma, B. V. (2025). A Case Study on-Enriching Learning Ability among Students By Adapting Collaborative Experiential Learning Based on Kolb’s Model. Journal of Engineering Education Transformations, 38(Special Issue), 368–374. https://doi.org/10.16920/jeet/2025/v38is2/25044
Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice-Hall. https://www.fullerton.edu/cice/_resources/pdfs/sl_documents/Experiential%20Learning%20-%20Experience%20As%20The%20Source%20Of%20Learning%20and%20Development.pdf
Lin, H. C. (2026). A Generative AI-Supported Flipped Classroom Model for Personalized Skill Training in Engineering Woodworking Education. Lecture Notes in Computer Science, 15914 LNCS, 366–376. https://doi.org/10.1007/978-3-031-98197-5_39
Liu, L. (2025). Enhancing educational training and learning outcomes through a hybrid experience created by integrating augmented reality and virtual reality technologies. Journal of Computational Methods in Sciences and Engineering, 25(3), 2310–2321. https://doi.org/10.1177/14727978241312994
Maquiling, E. E., & Desabella, R. V. (2025). Unraveling the connections: Learning styles, critical thinking skills and mathematics performance among industrial technology students. Edelweiss Applied Science and Technology, 9(6), 821–834. https://doi.org/10.55214/25768484.v9i6.7954
Meeran, M. R. N., Khuthbuddin, S., Al-Hinai, A. A. S., Ahmed, N. N., & Prakash, V. M. (2025). Exploring learning mechanisms and influences on student engagement and academic performance. International Journal of Innovation and Learning, 37(4), 474–493. https://doi.org/10.1504/ijil.2025.146512
Mishra, S., Mohamed, A., & Mohamed, M. (2025). Towards Efficient Assessment: Personalized Quizzing Through Machine Learning. Canadian Conference on Electrical and Computer Engineering, 469–474. https://doi.org/10.1109/ccece64018.2025.11364481
Obeidat, S., Dakeev, U., & Ma, J. (2022). Teaching AutoCAD in E-learning and Face-to-Face Styles for Undergraduate Engineering Technology Students During and after COVID-19 Pandemic. ASEE Annual Conference and Exposition, Conference Proceedings. https://doi.org/10.18260/1-2--40746
Obeidat, S. M., & Hajjat, J. A. (2021). Face-to-Face and E-learning Styles for Undergraduate Engineering Technology Students During COVID-19 Pandemic. ASEE Annual Conference and Exposition, Conference Proceedings. https://doi.org/10.18260/1-2--37170
Oletti, B. L., & Maxwell, J. (2024). Board 79: Leveraging Learning Styles for Enhanced Student Outcomes: A Study at a New York University. ASEE Annual Conference and Exposition, Conference Proceedings. https://doi.org/10.18260/1-2--48378
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., et al. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372. https://doi.org/10.1136/bmj.n71
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles concepts and evidence. Psychological Science in the Public Interest, Supplement, 9(3), 105–119. https://doi.org/10.1111/j.1539-6053.2009.01038.x
Patil, P. B., Vijayalakshmi, M., Basawaraj, & Humbi, N. (2022). Learning Styles of First-Year Undergraduate Engineering Majors at an Indian Technological University. 2022 IEEE IFEES World Engineering Education Forum - Global Engineering Deans Council, WEEF-GEDC 2022 - Conference Proceedings. https://doi.org/10.1109/WEEF-GEDC54384.2022.9996222
Pedram, S., Howard, S., Kencevski, K., & Perez, P. (2020). Investigating the relationship between students’ preferred learning style on their learning experience in virtual reality (VR) learning environment. Advances in Intelligent Systems and Computing, 1018, 275–281. https://doi.org/10.1007/978-3-030-25629-6_43
Rahman, S., Thankachan, B., Samposalo, H. M., Pade, C. S., Tandon, C., Kinnula, M., Monga, C., & Turunen, M. (2025). Technology-Assisted Sign Language Learning for Elementary Schoolchildren - A Cross-Country Study. ACM International Conference Proceeding Series, 222–232. https://doi.org/10.1145/3696593.3696602
Sampurno, M. B. T., Safian, A. R., Kusumandyoko, T. C., Islam, M. A., Wiratmoko, C., & Djahwasi, H. R. (2025). Integrating tactile and digital learning through hybrid popup cards (HiPOP) to enhance engagement and learning outcomes in distance elementary education. Edutec, 2025(94), 161-180. https://doi.org/10.21556/edutec.2025.94.3889
Selvi, K. T., Suhas, S., Shetty, V. H., Kumar, S. K., & Shenoy, S. (2025). Edutrack: AI based Personalized Learning Through Secure Analytics. Proceedings of the 4th International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2025, 1126–1131. https://doi.org/10.1109/icimia67127.2025.11200902
Siregar, H. S., Rizza, M., & Nurhamzah. (2025). ISLAMIC EDUCATION IN THE DIGITAL AGE: Students’ Perspectives on the Vark Model in the Context of Education 4.0. Ulumuna, 29(1), 129–154. https://ulumuna.or.id/index.php/ujis/article/view/1319
Stănescu, A. B., Travadel, S., Rughiniș, R. V., & Bucea-Manea-Țoniș, R. (2025). Modeling Learning Outcomes in Virtual Reality Through Cognitive Factors: A Case Study on Underwater Engineering. Electronics (Switzerland), 14(17). https://doi.org/10.3390/electronics14173369
Suprapto, Y., Nuraela, L., Masitoh, S., Nurdyansyah, & Mandarani, V. (2020). The Influence Computer Based Training Utilization of Learning Outcomes of Solid-State Electronics Viewed from Different Learning Style. Journal of Physics: Conference Series, 1594(1). https://doi.org/10.1088/1742-6596/1594/1/012008
Teeraputon, D., & Nuankaew, P. (2020). Attitude and learning styles in different academic achievement of tertiary students. Universal Journal of Educational Research, 8(11B), 6178–6184. https://doi.org/10.13189/ujer.2020.082255
Tibyani, T., Supianto, A. A., Anam, S., Wardhani, N. W. S., & Hartono, P. (2025). Learning-Advisory System Based on Students’ Similarity. International Journal of Mathematics and Computer Science, 20(4), 1121–1139. https://doi.org/10.69793/ijmcs/04.2025/tibyani
Tuyboyov, O., Turdikulova, B., Davlatova, R., & Norov, S. (2025). The role of AI-driven intelligent tutoring systems in enhancing mechanical engineering education. AIP Conference Proceedings, 3268(1). https://doi.org/10.1063/5.0257379
Vázquez-Sánchez, A., & Delgado, F. (2023). Educative performance transitions in engineering students through the COVID-19 pandemic. Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1156724
Wang, L., & Jin, Y. (2025). Research on Differentiated Teaching Strategies and Educational Effect Evaluation in Online Teaching of Radio and Television Director Major Based on Deep Neural Network. 3rd International Conference on Business Analytics for Technology and Security, ICBATS 2025, 1–6. https://doi.org/10.1109/icbats66542.2025.11258106
Wang, X. (2024). A blended teaching model integrating cognitive science and educational technology: An empirical study to enhance students’ learning effectiveness. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3092
Weiling, C. T., Ling, L. S., & Yin, O. S. (2025). Personalised and Collaborative Learning Experience (PCLE) Framework for AI-Driven Learning Management System (LMS). 2025 IEEE International Conference on Computing, ICOCO 2025, 506–511. https://doi.org/10.1109/icoco67189.2025.11334107
Wu, W., Hsu, Y., Cao, X., & Chen, J. (2021). Cross-Cultural Education: The Effects of AR Technology and Learning Styles on Learning Achievements of Sculpture Course. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12772 LNCS, 241–250. https://doi.org/10.1007/978-3-030-77077-8_19
Yang, C., & Singh, S. S. B. (2024). User Experience in Information System Platforms: A Study on Learning Styles and Academic Challenges. Journal of Internet Services and Information Security, 14(4), 209–223. https://doi.org/10.58346/jisis.2024.i4.012
Yin, M., Cao, H., Yu, Z., & Pan, X. (2024). Manual Label and Machine Learning in Clustering and Predicting Student Performance: A Practice Based on Web-Interactive Teaching Systems. International Journal of Web-Based Learning and Teaching Technologies, 19(1). https://doi.org/10.4018/ijwltt.347661
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education: Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/S41239-019-0171-0