Analyzing the Dimensions and Components of Experimental Science Curricula Based on the Application of Artificial Intelligence
Subject Areas : curriculummohammadreza bidel 1 , Hossein Momenimahmouei 2 * , aliakbar ajam 3
1 -
2 - Department of Educational Sciences, Torbat Heydarieh Branch, Islamic Azad University, Torbat Heydarieh, Iran
3 - Associate Professor, Department of Educational Sciences, Payam Noor University, Tehran, Iran
Keywords: Experimental Science Education, Artificial Intelligence, Curriculum,
Abstract :
The present study aimed to investigate the dimensions and components of experimental science curricula based on the application of artificial intelligence, in order to provide a comprehensive picture and perspective of this field. For this purpose, a qualitative meta-synthesis method was used. Research data were searched and collected using Roberts' six-stage model in the range considered (internal 1400-1404 and external 2020-2024). The scope of the research was all article that were presented on the research topic and related fields in specialized and scientific databases. The research sample was 30 articles, which were selected purposefully and based on thematic, content, and theoretical saturation monitoring of the data. The research data were analyzed at this stage using thematic content analysis. In order to examine the reliability and trustworthiness of the findings, the criteria of the researcher's self-review and the peer review method (rater agreement coefficient) were also used. By analyzing the data, the dimensions and components of the experimental science curricula based on the application of artificial intelligence were organized into six dimensions, 17 axes, and 78 categories, including environment and context (effective sectoral and cross-sectoral culture, professional development of human resources, technical infrastructure); goals (appropriateness and integration, alignment and interaction, formulation process); content (personalization, needs-based, empowering); teaching-learning strategies (based on a constructivist approach, situational and contingency strategies),resources and facilities (suitability with goals, processes and organizational procedures, system characteristics); and evaluation (providing smart assignments, reducing unproductive competition in evaluation, continuous supervision and monitoring).
Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101.
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431-440.
Alam, A. (2021, November). Possibilities and apprehensions in the landscape of artificial intelligence in education. In 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) (pp. 1-8). IEEE.
Almasri, F. (2024). Exploring the Impact of Artificial Intelligence in Teaching and Learning of Science: A Systematic Review of Empirical Research. Research in Science Education, 1-21.
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023). Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), 12983.
Bécue, A., Praça, I., & Gama, J. (2021). Artificial intelligence, cyber-threats and Industry 4.0: Challenges and opportunities. Artificial Intelligence Review, 54(5), 3849-3886.
Catacutan, A., Kilag, O. K., Diano Jr, F., Tiongzon, B., Malbas, M., & Abendan, C. F. (2023). Competence-Based Curriculum Development in a Globalized Education Landscape. Excellencia: International Multi-disciplinary Journal of Education (2994-9521), 1(4), 270-282.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. Ieee Access, 8, 75264-75278.
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002.
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002.
Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education. Educational Technology & Society, 25(1), 28-47.
Chiu, T. K., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118.
Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452.
Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452.
Dempster, H., & Hargrave, K. (2017). Understanding public attitudes towards refugees and migrants. London: Overseas Development Institute & Chatham House.
Dempster, H., & Hargrave, K. (2017). Understanding public attitudes towards refugees and migrants. London: Overseas Development Institute & Chatham House.
Dinçer, S. (2018). Content analysis in scientific research: Meta-analysis, meta-synthesis, and descriptive content analysis. Bartın University Journal of Faculty of Education, 7(1), 176-190.
Doroudi, S. (2023). The intertwined histories of artificial intelligence and education. International Journal of Artificial Intelligence in Education, 33(4), 885-928.
Erduran, S., & Levrini, O. (2024). The impact of artificial intelligence on scientific practices: an emergent area of research for science education. International Journal of Science Education, 1-8.
Fiok, K., Farahani, F. V., Karwowski, W., & Ahram, T. (2022). Explainable artificial intelligence for education and training. The Journal of Defense Modeling and Simulation, 19(2), 133-144.
Foltynek, T., Bjelobaba, S., Glendinning, I., Khan, Z. R., Santos, R., Pavletic, P., & Kravjar, J. (2023). ENAI Recommendations on the ethical use of Artificial Intelligence in Education. International Journal for Educational Integrity, 19(1), 1-4.
González-Calatayud, V., Prendes-Espinosa, P., & Roig-Vila, R. (2021). Artificial intelligence for student assessment: A systematic review. Applied sciences, 11(12), 5467.
Grassini, S. (2023). Shaping the future of education: exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), 692.
Herrera Comoglio, R. (2020). Undergraduate and postgraduate pharmacovigilance education: A proposal for appropriate curriculum content. British journal of clinical pharmacology, 86(4), 779-790.
Holmes, W., Persson, J., Chounta, I. A., Wasson, B., & Dimitrova, V. (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe.
Huang, J., Saleh, S., & Liu, Y. (2021). A review on artificial intelligence in education. Academic Journal of Interdisciplinary Studies, 10(3).
Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100001.
Jia, F., Sun, D., & Looi, C. K. (2024). Artificial intelligence in science education (2013–2023): Research trends in ten years. Journal of Science Education and Technology, 33(1), 94-117.
Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), 12451.
Kaplan, S. N. (2023). The grid: A model to construct differentiated curriculum for the gifted. In Systems and models for developing programs for the gifted and talented (pp. 235-251). Routledge.
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y. S., Kay, J., ... & Gašević, D. (2022). Explainable artificial intelligence in education. Computers and Education: Artificial Intelligence, 3, 100074.
Knox, J. (2020). Artificial intelligence and education in China. Learning, Media and Technology, 45(3), 298-311.
Lee, J., & Cho, J. (2024). Artificial Intelligence Curriculum Development for Intelligent System Experts in University. International Journal on Advanced Science, Engineering & Information Technology, 14(2).
Limna, P., Jakwatanatham, S., Siripipattanakul, S., Kaewpuang, P., & Sriboonruang, P. (2022). A review of artificial intelligence (AI) in education during the digital era. Advance Knowledge for Executives, 1(1), 1-9.
Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., ... & Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in psychology, 11, 580820.
Lubicz-Nawrocka, T., & Bovill, C. (2023). Do students experience transformation through co-creating curriculum in higher education?. Teaching in Higher Education, 28(7), 1744-1760.
Namasivayam, S., Al-Obaidi, A. S. M., & Fouladi, M. H. (2023). A conceptual curriculum design approach for educating engineers of and for the future. Indonesian Journal of Science and Technology, 8(3), 381-396.
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.
Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104.
Null, W. (2023). Curriculum: From theory to practice. Rowman & Littlefield.
Olatunde-Aiyedun, T. G. (2024). Artificial Intelligence (AI) in Education: Integration of AI Into Science Education Curriculum in Nigerian Universities. International Journal of Artificial Intelligence for Digital, 1(1).
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020.
Park, J., Teo, T. W., Teo, A., Chang, J., Huang, J. S., & Koo, S. (2023). Integrating artificial intelligence into science lessons: Teachers’ experiences and views. International Journal of STEM Education, 10(1), 61.
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development.
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.
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.
Pinar, W. F. (2019). What is curriculum theory?. Routledge.
Rossouw, N., & Frick, L. (2023). A conceptual framework for uncovering the hidden curriculum in private higher education. Cogent Education, 10(1), 2191409.
Sánchez, J. M., Rodríguez, J. P., & Espitia, H. E. (2020). Review of artificial intelligence applied in decision-making processes in agricultural public policy. Processes, 8(11), 1374.
Sanusi, I. T., Olaleye, S. A., Agbo, F. J., & Chiu, T. K. (2022). The role of learners’ competencies in artificial intelligence education. Computers and Education: Artificial Intelligence, 3, 100098.
Shahjahan, R. A., Estera, A. L., Surla, K. L., & Edwards, K. T. (2022). “Decolonizing” curriculum and pedagogy: A comparative review across disciplines and global higher education contexts. Review of Educational Research, 92(1), 73-113.
Suttrisno, S., & Yulia, N. M. (2024). Artificial Intelligence In Science Learning In Primary Schools. International Journal Of Humanities Education and Social Sciences, 3(6).
Tatar, C., Jiang, S., Rosé, C. P., & Chao, J. (2024). Exploring Teachers’ Views and Confidence in the Integration of an Artificial Intelligence Curriculum into Their Classrooms: a Case Study of Curricular Co-Design Program. International Journal of Artificial Intelligence in Education, 1-34.
Tomlinson, C. A. (2023). The parallel curriculum model: A design to develop potential & challenge high-ability learners. In Systems and models for developing programs for the gifted and talented (pp. 571-598). Routledge.
Tomlinson, C. A., & Jarvis, J. M. (2023). Differentiation: Making curriculum work for all students through responsive planning & instruction. In Systems and models for developing programs for the gifted and talented (pp. 599-628). Routledge.
Valle-Cruz, D., Alejandro Ruvalcaba-Gomez, E., Sandoval-Almazan, R., & Ignacio Criado, J. (2019, June). A review of artificial intelligence in government and its potential from a public policy perspective. In Proceedings of the 20th annual international conference on digital government research (pp. 91-99).
Valle-Cruz, D., Criado, J. I., Sandoval-Almazán, R., & Ruvalcaba-Gomez, E. A. (2020). Assessing the public policy-cycle framework in the age of artificial intelligence: From agenda-setting to policy evaluation. Government Information Quarterly, 37(4), 101509.
Wong, G. K., Ma, X., Dillenbourg, P., & Huan, J. (2020). Broadening artificial intelligence education in K-12: Where to start?. ACM inroads, 11(1), 20-29.
Yu, H., & Guo, Y. (2023, June). Generative artificial intelligence empowers educational reform: current status, issues, and prospects. In Frontiers in Education (Vol. 8, p. 1183162). Frontiers Media SA.
Zhang, J., & Tao, D. (2020). Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things. IEEE Internet of Things Journal, 8(10), 7789-7817.