ARTIFICIAL INTELLIGENCE CREATES FAIRY TALES FOR PHYSICS TEACHING IN PRIMARY EDUCATION

Forfattere

  • Konstantinos T. Kotsis Department of Primary Education, University of Ioannina, Greece

DOI:

https://doi.org/10.46827/ejoe.v9i1.5250

Nøgleord:

artificial intelligence, fairy tales, physics teaching, primary education

Resumé

This study explores the potential of Artificial Intelligence (AI) in creating fairy tales to enhance physics teaching in primary education. Traditional methods of teaching physics often fail to captivate young learners and instil a deep understanding of scientific concepts. Integrating storytelling and AI technology can create a stimulating learning environment, fostering curiosity and engagement among students. This paper discusses the theoretical framework behind storytelling and its impact on learning, outlines the development and implementation of AI-generated fairy tales in physics education, and evaluates this approach's effectiveness. The results demonstrate that AI-created fairy tales can significantly enhance students' interest, comprehension, and retention of physics concepts, leading to improved learning outcomes.

Forfatterbiografi

  • Konstantinos T. Kotsis, Department of Primary Education, University of Ioannina, Greece

    Konstantinos T. Kotsis, from 1981 to 2000, served as a Faculty Member specialising in solid-state physics and x-ray diffraction at the University of Ioannina's Physics Department. Since 2000, he has been a Faculty Member at the Department of Primary Education at the University of Ioannina, and in 2012, he was a Full Professor specialising in Physics Education. He has experience teaching in many University Departments, such as Physics, Chemistry, Informatics, Biological Applications & Technology, and Primary Education at the University of Ioannina and Aristotle University of Thessaloniki, Greece. His team designed the new Greek curriculum for science teaching in primary education. He participated in many conferences in Greece and abroad. His articles have been published in scientific International and Greek journals.

Referencer

AbuKhousa E., El-Tahawy M. S., Atif Y. (2023). Envisioning Architecture of Metaverse Intensive Learning Experience (MiLEx): Career Readiness in the 21st Century and Collective Intelligence Development Scenario. Future Internet.; 15(2):53. https://doi.org/10.3390/fi15020053

Ainscow, M. (2020). Promoting inclusion and equity in education: lessons from international experiences. Nordic Journal of Studies in Educational Policy, 6(1), 7–16. https://doi.org/10.1080/20020317.2020.1729587

Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7

Alshumaimeri, Y., & Alshememry, A. K. (2024). The Extent of AI Applications in EFL Learning and Teaching. IEEE Transactions on Learning Technologies, 17, 653-663. https://doi.org/10.1109/TLT.2023.3322128

Anjum, A., & Lieberum, N. (2023). Automatic Simplification of Scientific Texts using Pre-trained Language Models: A Comparative Study at CLEF Symposium 2023, 3497, p. 2899-2907. https://ceur-ws.org/Vol-3497/paper-242.pdf

Behnamnia, N., Kamsin, A., Ismail, M. A. B., & Hayati, A. (2020). The effective components of creativity in digital game-based learning among young children: A case study. Children and Youth Services Review, 116, 105227. https://doi.org/10.1016/j.childyouth.2020.105227

Bjorklund, D. F. (2022). Children′ s thinking: Cognitive development and individual differences. Sage publications.

Callo, E., & Yazon, A. (2020). Exploring the factors influencing the readiness of faculty and students on online teaching and learning as an alternative delivery mode for the new normal. Universal Journal of Educational Research, 8(8), 3509-3318. https://doi.org/10.13189/ujer.2020.080826

Cate, F. H., & Dockery, R. (2021). Data Privacy and Security Law, in Paul Cornish (ed.) The Oxford Handbook of Cyber Security. https://doi.org/10.1093/oxfordhb/9780198800682.013.20

Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00408-3

Council, T. A., & National Academies of Sciences, Engineering, and Medicine. (2016). Science teachers' learning: Enhancing opportunities, creating supportive contexts. National Academies Press.

Daryanes, F., Darmadi, D., Fikri, K., Sayuti, I., Rusandi, M.A., & Situmorang, D., (2023). The development of articulate storyline interactive learning media based on case methods to train students' problem-solving ability. Heliyon, 9 4, e15082. https://doi.org/10.1016/j.heliyon.2023.e15082

Das, D. K. (2023). Exploring the impact of feedback on student performance in undergraduate civil engineering. European Journal of Engineering Education, 48(6), 1148–1164. https://doi.org/10.1080/03043797.2023.2238188

Druga, S., Christoph, F. L., & Ko, A. J. (2022, April). Family as a Third Space for AI Literacies: How do children and parents learn about AI together? In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-17). https://doi.org/10.1145/3491102.3502031

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Vigneswara Ilavarasan. P., Janssen, M., Jones, P., Kumar Kar, A., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., Medaglia, R... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Gottschalk, F., & Weise C., (2023). Digital equity and inclusion in education: An overview of practice and policy in OECD countries, OECD Education Working Papers, No. 299, OECD Publishing, Paris, https://doi.org/10.1787/7cb15030-en.

Jortveit, M., & Kovač, V. B. (2022). Co-teaching that works: special and general educators’ perspectives on collaboration. Teaching Education, 33(3), 286-300. https://doi.org/10.1080/10476210.2021.1895105

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Keeling, A.B., Piitz, M., Semrau, J.A., Hill, M.D., Scott, S.H. & Dukelow, S.P., (2021). Robot enhanced stroke therapy optimizes rehabilitation (RESTORE): a pilot study. Journal Neuro Engineering Rehabil 18, 10 https://doi.org/10.1186/s12984-021-00804-8

Koropec, T. (2021). Storytelling as a Teaching Tool: The Importance and Benefits for Business English Students. International Journal of Humanities, Social Sciences and Education. 8(2), 105–109. https://doi.org/10.20431/2349-0381.0802009

Kotsis, K. T., & Tsiouri, E. (2023). Once Upon a Time-Integrating Fairy Tales into Physics Education: The Case of Mechanics. European Journal of Education and Pedagogy, 4(4), 31–39. https://doi.org/10.24018/ejedu.2023.4.4.712

Kuntjara, H., & Almanfaluthi, B. (2017). Character design in games analysis of character design theory. Journal of Games, Game Art, and Gamification, 2(2), 42-47. https://doi.org/10.21512/jggag.v2i2.7197

Lembani, R., Gunter, A., Breines, M., & Dalu, M. T. B. (2020). The same course, different access: the digital divide between urban and rural distance education students in South Africa. Journal of Geography in Higher Education, 44(1), 70-84. https://doi.org/10.1080/03098265.2019.1694876

Lin, C. C., Huang, A. Y., & Lu, O. H. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments, 10(1), 41. https://doi.org/10.1186/s40561-023-00260-y

Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., Baltes, J., Guerra, R., Li, P., & Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in Psychology, 11, 580820. https://doi.org/10.3389/fpsyg.2020.580820

Marginson, S., & Dang, T. K. A. (2017). Vygotsky’s sociocultural theory in the context of globalization. Asia Pacific Journal of Education, 37(1), 116-129. https://doi.org/10.1080/02188791.2016.1216827

Marian, A. (2023). Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery. Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 434–443. https://doi.org/10.1145/3593013.3594009

McMahon, A., & Cunningham, D.E. (2024). GP training in affluent practices in Scotland: the experiences of GP trainees and implications for their future practice. Education for Primary Care, 1–8. https://doi.org/10.1080/14739879.2024.2310316

Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2). https://doi.org/10.1177/2053951716679679

Papa, A., Dezi, L., Gregori, G.L., Mueller, J. and Miglietta, N. (2020). Improving innovation performance through knowledge acquisition: the moderating role of employee retention and human resource management practices, Journal of Knowledge Management, Vol. 24 No. 3, pp. 589-605. https://doi.org/10.1108/JKM-09-2017-0391

Piaget, J. (1954). The Construction of Reality in the Child. Basic Books.

Putz, L. M., Hofbauer, F., & Treiblmaier, H. (2020). Can gamification help to improve education? Findings from a longitudinal study. Computers in Human Behavior, 110, 106392. https://doi.org/10.1016/j.chb.2020.106392

Shank, M. K. (2023). Novice teachers’ training and support needs in evidence-based classroom management, Preventing School Failure: Alternative Education for Children and Youth, 67:4, 197–208, https://doi.org/10.1080/1045988X.2023.2195361

Shewbridge, C., Fuster, M., & Rouw, R., (2019). Constructive accountability, transparency and trust between government and highly autonomous schools in Flanders, OECD Education Working Papers, No. 199, OECD Publishing, Paris, https://doi.org/10.1787/c891abbf-en.

Susanto, P. C., Syailendra, S., & Suryawan, R. F. (2023). Determination of Motivation and Performance: Analysis of Job Satisfaction, Employee Engagement and Leadership. International Journal of Business and Applied Economics, 2(2), 59-68. https://doi.org/10.55927/ijbae.v2i2.2135

Szymkowiak, A., Melović, B., Dabić, M., Jeganathan, K., & Kundi, G. S. (2021). Information technology and Gen Z: The role of teachers, the internet, and technology in the education of young people. Technology in Society, 65, 101565. https://doi.org/10.1016/j.techsoc.2021.101565

Tonape, V., Salunkhe, S., & Lakade, S. (2023). Introduction of Case Based Learning and Comparison with Traditional Teaching Methods: An Observational Study. International Journal of Scientific Research 12(10), 67-69. https://doi.org/10.36106/ijsr/0809759

Viennot, L. (2003). Teaching physics. Springer Science & Business Media.

Vincent-Lancrin, S. & van der Vlies, R., (2020). Trustworthy artificial intelligence (AI) in education: Promises and challenges, OECD Education Working Papers, No. 218, OECD Publishing, Paris, https://doi.org/10.1787/a6c90fa9-en

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Publiceret

2024-03-03

Nummer

Årg. 9 Nr. 1 (2024)

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Articles

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