AI-Driven Learning Analytics in STEM Education
DOI:
https://doi.org/10.33830/ijrse.v5i2.1596Keywords:
Education, Disciplines, AI in education, STEM educationAbstract
In recent years, the integration approach of Artificial Intelligence (AI) is called for many disciplines, it also STEM education has paved the way for transformative advancements. This paper provides an example of AI-driven learning analytics within the context of STEM education. It provides a thorough analysis of the AI-driven STEM curriculum and its associated paradigm. Additionally, it highlights the obstacles and possible threats that educators and institutions face when implementing technological innovations in the classroom. The serves as a valuable resource for educators, researchers, and policymakers seeking to harness the power of AI-driven learning analytics to enhance STEM education. The transformative potential of AI is now shaping the future of STEM learning environments while advocating for a responsible and ethical approach to data-driven education. Ethical concerns and moral considerations should be discussed in school AI and STEM education.
References
Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligence,4, 100131. https://doi.org/10.1016/j.caeai.2023.100131.
Alam, A. (2022). A digital game-based learning approach for effective curriculum transactions for teaching-learning of artificial intelligence and machine learning. In2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS)(pp. 69-74). IEEE. https://doi.org/10.1109/icscds53736.2022.9760932.
Berendt, B., Littlejohn, A., & Blakemore, M. (2020). AI in education: Learner choice and fundamental rights. Learning, Media and Technology,45(3), 312-324. https://doi.org/10.1080/17439884.2020.1786399.
Borenstein, J., & Howard, A. (2021). Emerging challenges in AI and the need for AI ethics education. AI and Ethics,1(1), 61-65. https://doi.org/10.1007/s43681-020-00002-7.
Bryan, L. A., Moore, T. J., Johnson, C. C., & Roehrig, G. H. (2015). Integrated STEM education. STEM road map: A framework for integrated STEM education, 23-37. https://doi.org/10.4324/9781315753157-3.
Buiten, M. C. (2019). Towards intelligent regulation of artificial intelligence. European Journal of Risk Regulation, 10(1), 41-59. https://doi.org/10.1017/err.2019.8.
Casal-Otero, L., Catala, A., Fernandez-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: a systematic literature review. International Journal of STEM Education,10(1), 29. https://doi.org/10.1186/s40594-023-00418-7.
Changtong, N., Maneejak, N., & Yasri, P. (2020). Approaches for implementing STEM (Science, Technology, Engineering & Mathematics) activities among middle school students in Thailand. International journal of educational methodology, 6(1), 185-198. https://doi.org/10.12973/ijem.6.1.185.
Fortes, P. R. B., Baquero, P. M., & Amariles, D. R. (2022). Artificial intelligence risks and algorithmic regulation. European Journal of Risk Regulation, 13(3), 357-372. https://doi.org/10.1017/err.2022.14.
Furey, H., & Martin, F. (2019). AI education matters a modular approach to AI ethics education. AI Matters,4(4), 13-15. https://doi.org/10.1145/3299758.3299764.
Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education,3, 1-11. https://doi.org/10.1186/s40594-016-0046-z.
Kennedy, T. J., & Sundberg, C. W. (2020). 21st century skills. Science Education in Theory and Practice: An Introductory Guide to Learning Theory, 479-496. https://doi.org/10.1007/978-3-030-43620-9_32.
Kricorian, K., Seu, M., Lopez, D., Ureta, E., & Equils, O. (2020). Factors influencing participation of underrepresented students in STEM fields: matched mentors and mindsets. International Journal of STEM Education, 7(1), 1-9. https://doi.org/10.1186/s40594-020-00219-2.
Kusmawan, U. (2018). Online Microteaching: a Multifaceted Approach to Teacher Professional Development. Journal of Interactive Online Learning. https://www.ncolr.org/jiol/issues/pdf/15.1.3.pdf
Kusmawan, U. (2022). A Virtual Lab As A Vehicle For Active Learning Through Distance Education. International Journal of Research in STEM Education (IJRSE), 4(2), 18-38. https://dx.doi.org/10.31098/ijrse.v4i2.1188
Kusmawan, U. (2023). Redefining Teacher Training: The Promise of AI-Supported Teaching Practices. 2665, 332–335. https://doi.org/10.36348/jaep.2023.v07i09.001.
Lafifa, F., Rosana, D., Suyanta, S., Nurohman, S., & Astuti, S. R. D. (2023). Integrated STEM approach to improve 21st Century skills in Indonesia: A systematic review. International Journal of STEM Education for Sustainability,3(2), 252-267. http://dx.doi.org/10.53889/ijses.v3i2.219.
McCurdy, R. P., Nickels, M. L., & Bush, S. B. (2020). Problem-based design thinking tasks: Engaging student empathy in STEM. The Electronic Journal for Research in Science & Mathematics Education, 24(2), 22-55.
National Research Council. (2011). Successful K-12 STEM education: Identifying effective approaches in science, technology, engineering, and mathematics. National Academies Press.
Nawaz, S., Alghamdi, E. A., Srivastava, N., Lodge, J., & Corrin, L. (2022). Understanding the role of AI and learning analytics techniques in addressing task difficulties in STEM education. Artificial Intelligence in STEM Education: The Paradigmatic Shifts in Research, Education, and Technology, 241-258. https://doi.org/10.1201/9781003181187-20.
Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221-4241. https://doi.org/10.1007/s10639-022-11316-w.
Nuangchalerm, P., Prachagool, V., El Islami, R. A. Z., & Abdurrahman, A. (2020). Contribution of integrated learning through STEM education in ASEAN Countries. Journal of Progressive Education, 10(1), 11-21. https://doi.org/10.23960/jpp.v10.i1.202002.
Pham, S. T., & Sampson, P. M. (2022). The development of artificial intelligence in education: A review in context. Journal of Computer Assisted Learning,38(5), 1408-1421. https://doi.org/10.1111/jcal.12687.
Prachagool, V., & Nuangchalerm, P. (2021). Perspectives of Thai educators toward 21st Century instruction. Journal of Education and Learning (EduLearn),15(3), 432-437. https://doi.org/10.11591/edulearn.v15i3.20281.
Rus-Casas, C., La Rubia, M. D., Eliche-Quesada, D., Jimenez-Castillo, G., & Aguilar-Peña, J. D. (2021). Online tools for the creation of personal learning environments in engineering studies for sustainable learning. Sustainability,13(3), 1179. https://doi.org/10.3390/su13031179.
Tang, J., Zhou, X., Wan, X., & Ouyang, F. (2022). A Systematic review of AI applications in computer-supported collaborative learning in STEM education. Artificial Intelligence in STEM Education: The Paradigmatic Shifts in Research, Education, and Technology, 333-358. https://doi.org/10.1201/9781003181187-27.
Taylor, D. L., Yeung, M., & Bashet, A. Z. (2021). Personalized and adaptive learning. Innovative Learning Environments in STEM Higher Education: Opportunities, Challenges, and Looking Forward, 17-34. https://doi.org/10.1007/978-3-030-58948-6_2.
Triplett, W. J. (2023). Addressing cybersecurity challenges in education. International Journal of STEM Education for Sustainability, 3(1), 47-67. http://dx.doi.org/10.53889/ijses.v3i1.132.
Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology,45(3), 223-235. https://doi.org/10.1080/17439884.2020.1798995.
Xu, W., & Ouyang, F. (2022). The application of AI technologies in STEM education: a systematic review from 2011 to 2021. International Journal of STEM Education, 9(1), 1-20. https://doi.org/10.1186/s40594-022-00377-5.
Yang, W. (2022). Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence,3, 100061. https://doi.org/10.1016/j.caeai.2022.100061.
Zafari, M., Bazargani, J. S., Sadeghi-Niaraki, A., & Choi, S. M. (2022). Artificial intelligence applications in K-12 education: A systematic literature review. IEEE Access,10, 61905-61921. https://doi.org/10.1109/access.2022.3179356.
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