نوآوری‌های آموزشی

نوآوری‌های آموزشی

شناسایی انواع دانش محتوایی ضروری آموزگاران در درس علوم تجربی مبتنی برتحولات هوش مصنوعی

مقالات آماده انتشار

نوع مقاله : مقاله پژوهشی

نویسندگان
حسین بهاری بیگ باغلو 1
علیرضا عصاره 2
مصطفی قادری 3
محمد رضا امام جمعه 4
سید رسول عمادی 5
1 دانشجوی دکتری مطالعات برنامه درسی، دانشگاه تربیت دبیر شهید رجایی، تهران، ایران
2 استاد مطالعات برنامه درسی، دانشکده روانشناسی و علوم تربیتی، دانشگاه تربیت دبیر شهید رجایی، تهران، ا یران
3 دانشیار مطالعات برنامه درسی، دانشکده روانشناسی و علوم تربیتی دانشگاه علامه طباطبایی، تهران، ایران
4 دانشیار مطالعات برنامه درسی، دانشکده روانشناسی و علوم تربیتی دانشگاه تربیت دبیر شهید رجایی، تهران، ایران
5 دانشیار تکنولوژی آموزشی، دانشکده روانشناسی و علوم تربیتی، دانشگاه تربیت دبیر شهید رجایی، تهران، ایران
10.22034/jei.2025.532188.3237
چکیده
پژوهش حاضر با استفاده از روش کیفی و نوع سنتزپژوهی، به شناسایی انواع دانش محتوایی ضروری معلمان علوم در عصر هوش مصنوعی پرداخته است. داده‌های این تحقیق شامل 48 مقاله علمی پژوهشی داخلی و خارجی در شش سال اخیر بوده که از طریق جستجوی نظام‌مند گردآوری شده و با استفاده از الگوی شش‌مرحله‌ای سنتزپژوهی روبرتس، در سه مرحله کدگذاری باز، محوری و گزینشی تحلیل گردیدند. یافته‌ها نشان داد که دانش محتوایی ضروری معلمان در سه بعد دانش محتوایی، دانش محتوایی-آموزشی و دانش فناوری-آموزشی-محتوایی قابل تبیین است. این مؤلفه‌ها با بهره‌گیری از هوش مصنوعی تقویت شده و امکان یادگیری فعال، شخصی‌سازی‌شده و میان‌رشته‌ای را فراهم می‌کنند. تلفیق این ابعاد در چارچوب مدل AI-TPACK می‌تواند مبنای ارتقای شایستگی‌های معلمان علوم باشد. از نظر نظری، این مدل بر رویکردهای سازنده‌گرایی و ارتباط‌گرایی به‌عنوان رویکردهای اصلی و بر رویکردهای شناختی و رفتارگرایی به‌عنوان رویکردهای پشتیبان استوار است و به اثربخشی آموزش علوم تجربی در دوره ابتدایی کمک می‌کند.
کلیدواژه‌ها
دانش محتوایی
دانش ضروری
آموزگاران علوم
هوش مصنوعی
موضوعات

عنوان مقاله English

Identifying the Dimensions and Components of Essential Content Knowledge for Science Teachers Based on Artificial Intelligence Developments

نویسندگان English

Hossein Bahari Big Baghlou 1
Alireza Assare 2
Mostafa Ghaderi 3
Mohammadreza Imamjome 4
Seyed Rasoul Emadi 5
1 PhD Student in Curriculum, Shahid Rajaee Teacher Training University, Faculty of Humanities, Tehran, Iran
2 Professor of Curriculum Studies, Faculty of Psychology and Educational Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
3 Associate Professor of Curriculum Studies, Faculty of Psychology and Educational Sciences, Allameh Tabatabaei University, Tehran, Iran
4 Associate Professor of Curriculum Studies, Faculty of Psychology and Educational Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
5 Associate Professor of Curriculum Studies, Faculty of Psychology and Educational Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran
چکیده English

The present study aims to identify the dimensions and components of the essential content knowledge required for science teachers based on Artificial Intelligence (AI) advancements. This qualitative research was conducted using the meta-synthesis method, following the seven-step approach established by Sandelowski and Barroso. The statistical population comprised all Persian and English books and articles published between 2015 and 2025 in the field of science education utilizing AI tools. Through purposive sampling and applying specific inclusion criteria, a final sample of 50 articles was selected. The selected articles were analyzed using open, axial, and selective coding techniques facilitated by the MAXQDA software. The findings indicate that constructivist, socio-cultural, cognitive, and behaviorist theories underpin the foundations and applications of AI in science education. Furthermore, the essential content knowledge dimensions and components for elementary school science teachers, based on AI developments, encompass 3 main dimensions (Content Knowledge, Pedagogical Content Knowledge, and Technological Knowledge), 12 organizing components, 8 AI-based teaching techniques, and 129 identified codes. According to the conceptual model derived from the research findings (AI-TPACK), the essential knowledge components for elementary science teachers with an AI approach involve the integration of content knowledge, pedagogical content knowledge, and technological knowledge. These include: AI technical knowledge, AI content/technological knowledge, AI pedagogical /technological knowledge, AI pedagogical/content/technological knowledge, and contextual technology knowledge. Additionally, eight components were identified as AI-based science teaching techniques.

کلیدواژه‌ها English

Content Knowledge
Essential Knowledge
Science Teachers
Artificial Intelligence
اکرمی، فاطمه، و قادری، مصطفی. (۱۴۰۳). تحول در دانش حرفه‌ای معلمان با ظهور هوش مصنوعی. پژوهش در مطالعات برنامه‌درسی تربیت معلم، ۴(۱)، ۹۵-۱۲۳. https://doi.org/10.48310/JCDR.2024.16814.1109
شعبانی، حمیرا. (۱۴۰۳). اثرات هوش مصنوعی در فرایند یادگیری دانش‌آموزان در درس علوم تجربی. رویکرد پژوهشی نوین در مدیریت و حسابداری، ۸(۹۲)، ۳۱-۴۵. https://majournal.ir/index.php/ma/article/view/2399
فتحی، فرهاد، فتحی واجارگاه، کوروش، جعفری، اسماعیل، و وحیدی‌اصل، مجتبی. (۱۴۰۴). بازاندیشی برنامه درسی در عصر هوش مصنوعی، از ابزار آموزشی تا بستر تمدنی: رهیافتی نو در جنبش چندبسترسازی. مطالعات برنامه‌درسی، ۱۹(۷۵)، ۳۱-۵۲. https://doi.org/10.22034/jcs.2025.429395.2198
قادری، مصطفی، نصرتی، نسرین، و خسروی، محبوبه. (۱۳۹۷). سرگذشت گفتمان عملی در مطالعات برنامه‌درسی. انتشارات آوای نور.
کامیابی، شریف، و سمیعی‌دوست، محمد. (۱۴۰۱). شناسایی مؤلفه‌های دانش فناوری مورد نیاز نو معلمان جهت کاربست آن در فرایند تدریس. نظریه و عمل در تربیت معلم، ۸(۱۴)، ۲۱-۴۲. https://itt.cfu.ac.ir/article_2591.html
مارش، کالین جِی. (1387). پژوهش تلفیقی: سنتز پژوهی. روش‌شناسی مطالعات برنامة درسی (ترجمة محمود مهرمحمدی و همکاران). سمت. (اثر اصلی در سال 1991 چاپ شده است).
مطلبی‌نژاد، علیرضا، فاضلی، فرزانه، و نوائی، الهام. (۱۴۰۲). بررسی نظام‌مند نویدها و چالش‌های هوش مصنوعی برای معلمان. فناوری و دانش‌پژوهی در تعلیم و تربیت، ۳(۱)، ۲۳-۴۴. https://doi.org/10.30473/t-edu.2023.68819.1101
Abualrob, M. M. (2025). Innovative teaching: How pre-service teachers use artificial intelligence to teach science to fourth graders. Contemporary Educational Technology, 17(1), Article ep547. https://doi.org/10.30935/cedtech/15686
Adli, M., Suriani, A. B., Ibrahim, M. M., Azzam, A. B., Kusuma, H. H., Dwandaru, W. S. B., & Dhanil, M. (2024). Comprehensive review on technology-based learning using artificial intelligence for science subjects and its implications in teaching and learning. Educatum Journal of Science, Mathematics and Technology, 11(2), 100-113. https://doi.org/10.37134/ejsmt.vol11.2.11
Al-Zyoud, H. M. (2020). The role of artificial intelligence in teacher professional development. Universal Journal of Educational Research, 8(11B), 6263-6272. https://www.hrpub.org
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, 54, 977-997. https://doi.org/10.1007/s11165-024-10176-3
Ambele, R., Kaijage, S., Dida, M., Trojer, L., & Kyando, N. (2022). A review of the development trend of personalized learning technologies and its applications. International Journal of Advances in Scientific Research and Engineering, 8(11), 75-91. https://www.ijasre.net/index.php/ijasre
Bagir, M., Karakoyun, G., & Asilturk, E. (2022). Views of science teachers on the use of artificial intelligence in education. International Online Journal of Educational Sciences, 14(5), 1223-1234. https://doi.org/10.15345/iojes
Bismack, A. S. (2019). Content knowledge for teaching science: A longitudinal study of novice elementary teachers’ knowledge development in a practice-based teacher education program and school contexts [Doctoral dissertation, University of Michigan]. https://deepblue.lib.umich.edu/items/fbf30ead-3944-41ef-ab1c-0f9fcec22f73
Blonder, R., Maggor, Y., & Rap, S. (2024). Are they ready to teach? Generative AI as a means to uncover pre-service science teachers’ PCK and enhance their preparation program. Journal of Science Education and Technology. https://doi.org/10.1007/s10956-024-10180-2
Bogdanova, A. N., Fedorova, G. A., & Ragulina, M. I. (2021). Forming teachers’ awareness of knowledge in the field of artificial intelligence. In E. Bakshutova, V. Dobrova, & Y. Lopukhova (Eds.), Humanity in the Era of Uncertainty (Vol. 119, pp. 281–287). European Proceedings of Social and Behavioural Sciences. https://doi.org/10.15405/epsbs.2021.12.02.35
Celik, I. (2022). Towards intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, Article 107468. https://doi.org/10.1016/j.chb.2022.107468
Chiu, T. K., Ahmad, Z., & Çoban, M. (2024). Development and validation of teacher artificial intelligence (AI) competence self-efficacy (TAICS) scale. Education and Information Technologies, 30(5), 6667-6685. https://doi.org/10.1007/s10639-024-13094-z
Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32, 444-452. https://doi.org/10.1007/s10956-023-10039-y
Dai, Y. (2023). Negotiation of epistemological understandings and teaching practices between primary teachers and scientists about artificial intelligence in professional development. Research in Science Education, 53(3), 577-591. https://doi.org/10.1007/s11165-022-10072-8
Darayseh, A. (2023). Acceptance of artificial intelligence in teaching science: Science teachers’ perspective. Computers and Education: Artificial Intelligence, Article 100132. https://doi.org/10.1016/j.caeai.2023.100132
Falloon, G. (2020). From digital literacy to digital competence: The teacher digital competency (TDC) framework. Educational Technology Research and Development, 68(5), 2449-2472. https://doi.org/10.1007/s11423-020-09767-4
Gunawan, K. D. H., Liliasari, Kaniawati, I., & Setiawan, W. (2021). The responses to artificial intelligence in teacher integrated science learning training program. Proceedings of the International Conference on Mathematics and Science Education, Article 012034. https://doi.org/10.1088/1742-6596/2098/1/012034
Harmon, J., Pitt, V., Summons, P., & Inder, K. J. (2020). Use of artificial intelligence and virtual reality within clinical simulation for nursing pain education: A scoping review. Nurse Education Today, 97, Article 104700. https://doi.org/10.1016/j.nedt.2020.104700
Ishmuradova, I. I., Zhdanov, S. P., Kondrashev, S. V., Erokhova, N. S., Grishnova, E. E., & Volosova, N. Y. (2025). Pre-service science teachers’ perception on using generative artificial intelligence in science education. Contemporary Educational Technology, 17(3), Article ep579. https://doi.org/10.30935/cedtech/16207
Isma'il, A., Aliu, A., & Ibrahim, M. (2024). Preparing teachers of the future in the era of artificial intelligence. Journal of Artificial Intelligence, Machine Learning and Neural Network, Article. https://doi.org/10.55529/jaimlnn.44.31.41
Kapici, H. O., Akcay, H., & Cakir, H. (2022). Investigating the effects of different levels of guidance in inquiry-based hands-on and virtual science laboratories. International Journal of Science Education, 44(2), 324-345. https://doi.org/10.1080/09500693.2022.2028926
Karsenti, T. (2019). Artificial intelligence in education: The urgent need to prepare teachers for tomorrow’s schools. Formation et Profession, 27(1), 105-111. https://doi.org/10.18162/fp.2019.a166
Kim, K., & Kwon, K. (2023). Exploring the AI competencies of elementary school teachers in South Korea. Computers and Education: Artificial Intelligence, Article 100137. https://doi.org/10.1016/j.caeai.2023.100137
Kim, S. (2024). Development of a TPACK educational program to enhance pre-service teachers' teaching expertise in artificial intelligence convergence education. International Journal on Advanced Science Engineering and Information Technology, 14(1), 1-9. https://doi.org/10.18517/ijaseit.14.1.19552
Köprülü, F., Oyebimpe, A. O., Başarı, Ş., & Ayhan, S. B. (2023). Innovative effects of artificial intelligence on teacher education. Conhecimento & Diversidade, 15(40), 449–465. https://doi.org/10.18316/rcd.v15i40.11240
Kotsis, K. T. (2024). Artificial intelligence creates fairy tales for physics teaching in primary education. European Journal of Open Education and E-learning Studies, 9(1). https://doi.org/10.46827/ejoe.v9i1.5250
Li, T., Reigh, E., He, P., & Adah Miller, E. (2023). Can we and should we use artificial intelligence for formative assessment in science? Journal of Research in Science Teaching, 60(6), 1385-1389. https://doi.org/10.1002/tea.21867
Lin, C.-C., Huang, A. Y. Q., & Lu, O. H. T. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: A systematic review. Smart Learning Environments, 10, Article 41. https://doi.org/10.1186/s40561-023-00260-y
Long, T., Zhao, G., Li, X., Zhao, R., Xie, K., & Duan, Y. (2020). Exploring Chinese in-service primary teachers’ technological pedagogical content knowledge (TPACK) for the use of thinking tools. Asia Pacific Journal of Education, 42(2), 350-370. https://doi.org/10.1080/02188791.2020.1812514
Lindner, A., & Romeike, R. (2019). Teachers' perspectives on artificial intelligence. https://www.researchgate.net/publication/337716601
Marsh, C. J. (2009). Key concepts for understanding curriculum. Routledge
Mollick, E. R., & Mollick, L. (2023, March 17). Using AI to implement effective teaching strategies in classrooms: Five strategies, including prompts (The Wharton School Research Paper). SSRN. https://doi.org/10.2139/ssrn.4391243
Mondal, H., Marndi, G., Behera, K., & Mondal, S. (2023). ChatGPT for teachers: Practical examples for utilizing artificial intelligence for educational purposes. Indian Journal of Vascular and Endovascular Surgery, 10, 200-205. https://doi.org/10.4103/ijves.ijves_37_23
Murphy, R. F. (2019, January). Artificial Intelligence Applications to Support K–12 Teachers and Teaching: A Review of Promising Applications, Opportunities, and Challenges (Research report 19907). RAND Corporation. https://www.jstor.org/stable/resrep19907?seq=1
Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers’ trust in AI-powered educational technology and a professional development program to improve it. British Journal of Educational Technology, 53(4), 914-931. https://doi.org/10.1111/bjet.13232
Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first-century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137-161. https://doi.org/10.1007/s11423-023-10203-6
Ning, Y., Zhang, C., Xu, B., Zhou, Y., & Wijaya, T. T. (2024). Teachers’ AI-TPACK: Exploring the relationship between knowledge elements. Sustainability, 16(3), Article 30978. https://doi.org/10.3390/su16030978
Nja, C. O., Idiege, K. J., Uwe, U. E., Meremikwu, A. N., Ekon, E. E., Erim, C. M., & Cornelius-Ukpepi, B. U. (2023). Adoption of artificial intelligence in science teaching: From the vantage point of the African science teachers. Smart Learning Environments, 10(1), Article 42. https://doi.org/10.1186/s40561-023-00261-x
Obe, W. H. (2018). The teaching of science in primary schools. David Fulton Publishers. https://doi.org/10.4324/9781315398907
Park, J., Teo, T., Teo, A., Chang, J., Huang, J., & Koo, S. (2023). Integrating artificial intelligence into science lessons: Teachers’ experiences and views. International Journal of STEM Education, 10, Article 16. https://doi.org/10.1186/s40594-023-00454-3
Polak, S., Schiavo, G., & Zancanaro, M. (2022). Teachers’ perspective on artificial intelligence education: An initial investigation. CHI Conference on Human Factors in Computing Systems Extended Abstracts, Article 431. https://doi.org/10.1145/3491101.3519866
Pope, D. (2017). Conceptions of subject knowledge in primary initial teacher training: The perspectives of student teachers and teacher educators [Doctoral thesis, Liverpool John Moores University]. https://doi.org/10.24377/LJMU.t.00005762
Pratschke, B. M. (2024). Generative AI and education: Digital pedagogies, teaching innovation and learning design. SpringerBriefs in Education. https://doi.org/10.1007/978-3-031-67991-9
Pu, S., Ahmad, A., Khambari, N., Yap, K., & Ahrari, S. (2021). Improvement of pre-service teachers' practical knowledge and motivation about artificial intelligence through a service-learning-based module in Guizhou, China: A quasi-experimental study. Asian Journal of University Education, 17(3). https://doi.org/10.24191/ajue.v17i3.14499
Okebukola, P. A. (Ed.). (2025). AI and curriculum development for the future (In honour of Abubakar Adamu Rasheed). Sterling Publishers. https://eprints.gouni.edu.ng/4428/1/Volume%202-AI%20and%20Quality%20Higher%20Education%20Handbook-January%202025.pdf
Saharuddin, M., Nasir, M., & Mahmud, M. (2024). Exploring teachers’ technological pedagogical content knowledge in utilizing artificial intelligence (AI) for teaching. International Journal of Learning, Teaching and Educational Research, 24(1), 136-151. https://doi.org/10.26803/ijlter.24.1.7
Shah, P. (2023). AI and the future of education: Teaching in the age of artificial intelligence. John Wiley & Sons
Simuț, R., Simuț, C., Badulescu, D., & Bădulescu, A. (2024). Artificial intelligence and the modelling of teachers' competencies. Amfiteatru Economic Journal, 26(65), 181-200. https://doi.org/10.24818/EA/2024/65/181
Topal, A. D., Eren, C. D., & Gecer, A. K. (2021). Chatbot application in a 5th grade science course. Education and Information Technologies, 26, 6241-6265. https://doi.org/10.1007/s10639-021-10627-8
United Nations Educational, Scientific and Cultural Organization. (2024). AI competency framework for teachers [Framework]. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000391104
Verma, G., Campbell, T., Melville, W., & Park, B. (2023). Navigating opportunities and challenges of artificial intelligence: ChatGPT and generative models in science teacher education. Journal of Science Teacher Education, 34(8), 793-798. https://doi.org/10.1080/1046560X.2023.2263251
Yue, M., Jong, M., & Ng, D. (2024). Understanding K-12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12621-2
Zhai, X. (2021). Practices and theories: How can machine learning assist in innovative assessment practices in science education? Journal of Science Education and Technology, 30, 454–468. https://doi.org/10.1007/s10956-021-09901-8
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مقالات آماده انتشار، پذیرفته شده
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