Adoption of AI-Based Educational Tools in Elementary Schools: Teachers’ Readiness, Pedagogical Shifts, and Learning Effectiveness
DOI:
https://doi.org/10.29284/pcr4qk46Keywords:
Artificial Intelligence in Education, Elementary Schools, Teachers’ Readiness, Pedagogical Shifts, Learning Effectiveness.Abstract
Artificial intelligence (AI) is increasingly being introduced in the elementary classroom, with promises of changing instruction, individualizing learning, and improving student performance. But the success of AI-driven educational tools largely comes down to how prepared teachers are and what pedagogical shifts these tools result in. This is a conceptual paper that focuses on teachers’ readiness, pedagogical change and the effectiveness of learning in primary schools. Based on studies cited in reputable journals, the study theorizes teachers' readiness as a multidimensional construct with technical, pedagogical/psychological and ethical dimensions. Theoretical and practical implications are also discussed on how pedagogical changes serve as a critical mediating factor in the relationships between AI use and learning effectiveness (cognitive-, behavioral- and affective-wise). An overarching conceptual framework is introduced and illustrated in secondary syntheses tables formatted for Excel based figure construction. The study ends with an implications for policy, school leadership, and teacher education and a further research agenda on AI-assisted elementary education.
References
1. Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1), 5–31.https://doi.org/10.1007/s11092-008-9068-5
2. Cuban, L. (2018). The flight of a butterfly or the path of a bullet? Using technology to transform teaching and learning. Harvard Education Press.
3. Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284.
https://doi.org/10.1080/15391523.2010.10782551
4. Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109.
https://doi.org/10.3102/00346543074001059
5. Fullan, M. (2016). The new meaning of educational change (5th ed.). Teachers College Press.
6. Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge.
7. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
8. Koehler, M. J., & Mishra, P. (2009). What is technological pedagogical content knowledge (TPACK)? Contemporary Issues in Technology and Teacher Education, 9(1), 60–70.
9. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
10. OECD. (2021). Artificial intelligence in education: Challenges and opportunities for sustainable development. OECD Publishing.
11. Pane, J. F., Steiner, E. D., Baird, M. D., & Hamilton, L. S. (2017). Informing progress: Insights on personalized learning implementation and effects. Educational Policy, 31(6), 713–750.
https://doi.org/10.1177/0895904816661016
12. Selwyn, N. (2016). Education and technology: Key issues and debates (2nd ed.). Bloomsbury Academic.
13. Tondeur, J., van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education. Educational Technology Research and Development, 65(3), 555–575.https://doi.org/10.1007/s11423-016-9481-2
14. Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in artificial intelligence in education. Learning, Media and Technology, 45(3), 223–235.
https://doi.org/10.1080/17439884.2020.1798995
15. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in education. International Journal of Educational Technology in Higher Education, 16(1), 39.https://doi.org/10.1186/s41239-019-0171-0
16. UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO Publishing.
17. B.R. Kukreti, Tanuja Bhatt, Co-relational study of teaching efficiency and intelligence: In relation to type of organisation and teaching experience, Materials Today: Proceedings, Volume 80, Part 3, 2023, Pages 2777-2780, ISSN 2214-7853.
https://doi.org/10.1016/j.matpr.2021.07.037.
18. Understanding The Factors Influencing Academic Procrastination: A Comprehensive Review. (2023). Journal of Namibian Studies : History Politics Culture, 35, 4396-4414.
https://doi.org/10.59670/jns.v35i.4465
19. Nep 2020 Curriculum Reform And Pedagogical Innovations In Higher Education. (2023). Journal of Namibian Studies : History Politics Culture, 39, 789-809. https://doi.org/10.59670/8zv04759
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This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
