How e-learning programs can be more individualized with artificial intelligence – a theoretical approach from a pedagogical point of view
Abstract
Countless e-learning programs have been developed over the last few years. Learning opportunities supported by technology have become widespread in educational contexts, and many people rely on the Internet to continue their education in personal, professional, or school contexts. Findings indicate that recently developed e-learning programs are built on modern digital tools but need more purposeful content and a different focus than traditional learning scenarios. These observations raise whether online learning features are optimal extensions to traditional in-person, in-class teaching.This article focuses on how to optimize an e-learning program with the development of a query builder based on Artificial Intelligence (AI) that leverages the know-how of pedagogical experts to incorporate pedagogical learning methods effectively. For this reason, different definitions of e-learning and traditional learning theories, e.g., behaviorism, cognitivism, constructivism, and connectivism, will be analyzed to help derive theory ideas for an EU-funded project called “Young Refugees AI Student Empowerment Program.” Finally, the article will show some first technical results of implementation integrated into the project. Because of the project's target group, the needs, motives, and requirements of migrants and refugees will also be analyzed, and into the ideas for implementation included.
Keywords:
Artificial Intelligence, e-learning, learning theories, integration, migrants, refugees
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References
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Bahri, S., & Lestari, E. M. (2021). Implementation of human-machine friendship learning in the new normal era. Journal of Education and Learning (Edu Learn), 15(2), pp. 291-296. doi:10.11591/edulearn.v15i2.18404
Flindt, N., Magarian, M., & Hohl, G. (2021). The creation of brain-stimulating online learning content for a young migrant and refugee project. Muallim Jorunal of Social Sciences and Humanities, 5(2), pp. 1-11. doi:10.33306/mjssh/116
TeachSurfing. (2022). About us. Retrieved from https://teachsurfing.org/about-us
Garbauskaite, J. (2022). Educational quality assessment e-VELP. pp. 1-12. Retrieved from https://s3.eu-central-1.amazonaws.com/info.teachsurfing.org/evelp/eVELP-Educational-Quality-Assessment.pdf
Erasmus+. (2021). Application. Young Refugees´ AI Student Empowerment Program. pp. 1-122.
Marr, B. (2021). How Is AI Used In Education - Real World Examples Of Today And A Peek Into The Future. Retrieved from https://bernardmarr.com/how-is-ai-used-in-education-real-world-examples-of-today-and-a-peek-into-the-future/
Kumar Basak, S. K., Wotto, M., & Bélanger, P. (2018). E-learning, M-learning and D-learning: Conceptual definition and comparative analysis. E-Learning and Digital Media, 15(4), pp. 191-216. doi:10.1177/2042753018785180
Dichanz, H., & Ernst, A. (2001). E-Learning: Begriffliche, psychologische und didaktische Überlegungen zum "electronic learning" [E-Learning: Conceptual, psychological and didactical considerations on "electronic learning"]. MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung, 2(Virtualität und E-Learning), pp. 1-30. doi:10.21240/mpaed/02/2001.06.27.X
Flindt, N. (2005). E-learning - Theoriekonzepte und Praxiswirklichkeit (Doctoral dissertation). doi:10.11588/heidok.00006907
Sangrà, A., Vlachopoulus, D., & Cabrera, N. (2012). Building an inclusive definition of e-learning: An approach to the conceptual framework. The international review of research in open and distributed learning, 13(2), pp. 145-159. doi:10.19173/irrodl.v13i2.1161
Gleason, B., & Greenhow, C. (2017). Hybrid education: The potential of teaching and learning with robot-mediated communication. Online learning journal, 21(4), pp. 159-176. doi:10.24059/olj.v21i4.1276
Bencheva, N. (2010). Learning Styles and E-Learninh Face-to-Face to the Traditional Learning. Научни Трудове На Русенския Университеt, 49(3.2), pp. 63-67. Retrieved from https://conf.uni-ruse.bg/bg/docs/cp10/3.2/3.2-11.pdf
García Carreño, I. (2014). Theory of Connectivity as an Emergent Solution to Innovative Learning Strategies. American Journal of Educational Research, 2(2), pp. 107-116. doi:10.12691/education-2-2-7
Chandrappa, P. K. (2018). Connectivism as a Learning Theory For The Digital Age. ADHYAYAN: A JOURNAL OF MANAGEMENT SCIENCES, 8(1), pp. 37-47. Retrieved from https://smsjournals.com/index.php/Adhyayan/article/view/2092
García Carreño, I. (2014). Theory of Connectivity as an Emergent Solution to Innovative Learning Strategies. American Journal of Educational Research, 2(2), pp. 107-116. doi:10.12691/education-2-2-7
Siemens, G. (2005). Connectivism: A Learning Theory for the Digital Age. International Journal of Instructional Technology and Distance Learning, 2(1), pp. 3-10.
Downes, S. (2022). Connectivism. Asian Journal of Distance Education, 17(1), pp. 58-87. Retrieved from https://www.asianjde.com/ojs/index.php/AsianJDE/article/view/623
Utrecht, J., & Keller, D. (2019). Becoming Relevant Again: Applying Connectivism Learning Theory to Today´s Classrooms. Academy for Educational Studies, pp. 107-119. Retrieved from https://eric.ed.gov/?id=EJ1219672
Janelli, M. (2018). E-Learning in Theory, Practice, and Research. Voprosy obrazovaniya / Educational Studies Moscow, 4, pp. 81-98. doi:10.17323/1814-9545-2018-4-81-98
Skinner, B. F. (1958). Teaching Machines. From the experimental study of learning come devices which arrange optimal conditions for self-instruction. 128(3330), pp. 969-977. Retrieved from SCIENCE (1958)
Mödritscher, F. (2006). e-Learning Theories in Practice: A Comparison of three methods. Journal of Universal Science and Technology of Learning, 28(1), pp. 3-18.
Ertmer, P. A., & Newby, T. J. (2013). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 26(2), pp. 43-71. doi:10.1002/piq.21143
Schulmeister, R. (2007). Grundlagen hypermedialer Lernsysteme. Theorie - Didaktik – Design [Basics of hypermedia learning systems]. Oldenbourg Wissenschaftsverlag, 4. doi:10.1524/9783486594096
Heckmann, F. (2015). Integration von Migranten. Einwanderung und neue Nationenbildung [Integration of migants. Immigration and new nation building]. Wiesbaden: Springer VS.
Kosyakova, Y., & Kogan, I. (2022). Labor market situation of refugees in Europe: The role of individual and contextual factors. Frontiers in Political Science. doi:10.3389/fpos.2022.977764
Worbs, S., & Bund, E. (2016). Asylberechtigte und anerkannte Flüchtlinge in Deutschland: Qualifikationsstruktur, Arbeitsmarktbeteiligung und Zukunftsorientierungen [Refugees entitled to asylum and recognized refugees in Germany: Qualifications, labor market and future orientations]. Retrieved from https://nbn-resolving.org/urn:nbn:de:0168-ssoar-67441-2
Xie, P., Cao, Q., Li, X., Yang, Y., & Yu, L. (2022). The effects of social participation on social integration. Frontiers in Psychology. doi:10.3389/fpsyg.2022.919592
Niemi, M., Manhica, H., Gunnarsson, D., Stahle, G., & Larsson, S. S. (2019). A Scoping Review and Conceptual Model of Socal Participation and Mental Health amog Refugees and Asylum Seekers. International journal of environmental research and public health, 16(20) 4027, pp. 1-27. doi:10.3390/ijerph16204027
Becker, R. (2011). Integration von Migranten durch Bildung und Ausbildung - theoretische Erklärungen und empirische Befunde [Integration through education. Educational acquisition of young migrants]. In R. Becker, Integration durch Bildung. Bildungserwerb von jungen Migranten in Deutschland (pp. 11-36). Wiesbaden: Springer VS.
Cormoș, V. C. (2022). The Processes of Adaption, Assimilation and Integration in the Country of Migration: A Psychosocial Perspective on Place Identity Chnges. Department of Humanities and Social-Political Sciences, Stefan cel Mare University Romania, 14(16) 10296, pp. 1-20. doi:10.3390/su141610296
Ivanov, B. (2020). The Role of Artificial Intelligence in E-learning. Retrieved from https://becominghuman.ai/the-role-of-artificial-intelligence-in-e-learning-41ac88ee3e8d
Neelakandan, N. (2019). Artificial Intelligence-Based eLearning Platform: Is Impact On The Future of eLearning. Retrieved from https://elearningindustry.com/artificial-intelligence-based-platform-impact-future-elearning
Alzain, H. A. (2018). The role of social networks in supporting collaborative e-learning based on connectivism theory among students of PNU. Turkish Online Journal of Distance Education, 20(2), pp. 46-63. doi:10.17718/tojde.557736
e-VELP. (2021). Online Course. Retrieved from https://evelp.teachsurfing.org/
Bender, J. (2023). Machine Learning or Automation: What´s the Difference? Retrieved from https://www.businessnewsdaily.com/10352-machine-learning-vs-automation.html
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Rohde, N., Flindt, N., Rietz, C., & K. Kassymova, G. (2023). How e-learning programs can be more individualized with artificial intelligence – a theoretical approach from a pedagogical point of view. Muallim Journal of Social Sciences and Humanities, 7(3), 1-17. https://doi.org/10.33306/mjssh/240
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