Exploratory Factor Analysis of Generative Artificial Intelligent Literacy for Teachers Under the Pathum Thani Secondary Educational Service Area Office
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Abstract
The purpose of this research is to analyze the exploratory factors of Generative Artificial Intelligence (GAI) literacy for Teachers Under the Secondary Educational Service Area Office Pathum Thani. The sample consisted of 350 teachers employed by basic education institutions under the Secondary Educational Service Area Office, Pathum Thani, for the 2024 academic year. The sample was selected using multi-stage sampling from 22 schools. The research instrument was a questionnaire, with content validity checked using the Index of Item-Objective Congruence (IOC), which ranged from 0.60 to 1.00. The overall reliability, measured by Cronbach's alpha, was 0.962. The data were analyzed using Exploratory Factor Analysis (EFA). Factors were extracted through common factor analysis (CFA) using the principal axis factoring (PAF) method, followed by orthogonal rotation with the Varimax method. The research findings revealed three components of Generative Artificial Intelligence (GAI) literacy for basic education teachers, organized in line with the knowledge management process as follows: 1) understanding the use of GAI with quality and ethics, which encompasses foundational knowledge and the ability to use GAI appropriately; 2) appropriate and effective use of GAI, which emphasizes the ability to give effective commands to GAI without violating ethical standards or rights; and 3) the application of GAI in various contexts, highlighting the skill of utilizing GAI to support tasks or solve problems beyond teaching and learning management. Together, these components explained 82.56% of the variance in GAI literacy for basic education teachers. These findings can be utilized by educational institutions to develop action plans for enhancing the capabilities of educators or teaching personnel, promoting the use of GAI to improve the quality of education in ways that align with the context of their organizations.
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References
กระทรวงการอุดมศึกษาฯ. (2565). แผนปฏิบัติการด้านปัญญาประดิษฐ์แห่งชาติเพื่อการพัฒนาประเทศไทย พ.ศ. 2565 – 2570. กระทรวงการอุดมศึกษา วิทยาศาสตร์ วิจัย และนวัตกรรม.
นฤภัค สันป่าแก้ว. (2566). แนวทางการส่งเสริมครูในการจัดการเรียนรู้ยุค AI. วารสารวิจัยนวัตกรรมการศึกษาและเทคโนโลยี, 1(2), 44-50.
ยุทธ ไกยวรรณ์. (2556). การวิเคราะห์สถิติหลายตัวแปรสำหรับงานวิจัย. กรุงเทพฯ: สำนักพิมพ์จุฬาลงกรณ์มหาวิทยาลัย.
สุภมาส อังศุโชติ, สมถวิล วิจิตวรรณา, & รัชนีกูล ภิญโญภานุวัฒน์. (2552). สถิติวิเคราะห์สำหรับการวิจัยทางสังคมศาสตร์และพฤติกรรมศาสตร์ เทคนิคการใช้โปรแกรม Lisrel (พิมพ์ครั้งที่ 3). กรุงเทพฯ: เจริญดีมั่นคงการพิมพ์.
สุวิมล ว่องวาณิช. (2558). การวิจัยประเมินความต้องการจําเป็น (พิมพ์ครั้งที่ 3 ฉบับปรับปรุง). กรุงเทพมหานคร: สำนักพิมพ์แห่งจุฬาลงกรณ์มหาวิทยาลัย.
Ayanwale, M. A., Adelana, O. P., Molefi, R. R., Adeeko, O., & Ishola, A. M. (2024). Examining artificial intelligence literacy among pre-service teachers for future classrooms. Computers and Education Open, 6, Article 100179. https://doi.org/10.1016/j.caeo.2024.100179
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.
Bastani, H., Bastani, O., Sungu, A., Ge, H., Kabakcı, O., & Mariman, R. (2024). Generative AI can harm learning. SSRN. https://doi.org/10.2139/ssrn.4895486
Bower, M., Torrington, J., Lai, J. W., Petocz, P., & Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative artificial intelligence? Outcomes of the ChatGPT teacher survey. Education and Information Technologies, 1–37.
Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: A systematic literature review. International Journal of STEM Education, 10(29). https://doi.org/10.1186/s40594-023-00418-7
Chhatwal, M., Garg, V., & Rajput, N. (2023). Role of AI in the education sector. Lloyd Business Review, 1(7).
Comrey, A. L., & Lee, H. B. (1992). A first course in factor analysis (2nd ed.). Lawrence Erlbaum Associates.
Cornell University. (2023). Ethical AI for teaching and learning. Center for Teaching Innovation. Retrieved from https://teaching.cornell.edu/generative-artificial-intelligence/ethical-ai-teaching-and-learning
de Winter, J. C., Dodou, D., & Stienen, A. H. (2023). ChatGPT in education: Empowering educators through methods for recognition and assessment. Informatics, 10(4), Article 87. https://doi.org/10.3390/informatics10040087
Ding, L., Kim, S., & Allday, R. A. (2024). Development of an AI literacy assessment for non-technical individuals: What do teachers know? Contemporary Educational Technology, 16(3), ep512. https://doi.org/10.30935/cedtech/14619
Farrelly, T., & Baker, N. (2023). Generative artificial intelligence: Implications and considerations for higher education practice. Education Sciences, 13(11), 1109–1122.Giannini, S. (2023). Generative AI and the future of education. UNESCO.
Google DeepMind. (2024). Gemini: Integrating perception and reasoning in AI. https://www.deepmind.com/research/publications/gemini-integrating-perception-and-reasoning-in-ai
Google, & MIT RAISE. (2024). Google and MIT RAISE collaborate on a free generative AI course for educators. MIT Open Learning. https://openlearning.mit.edu/news/google-and-mit-raise-collaborate-free-generative-ai-course-educators
Han, A., Zhou, X., Cai, Z., Han, S., Ko, R., Corrigan, S., & Peppler, K. (2024). Teachers, parents, and students’ perspectives on integrating generative AI into elementary literacy education. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '24), 1–17. https://doi.org/10.1145/3613904.3642438
Jauhiainen, J. S., & Guerra, A. G. (2023). Generative AI and ChatGPT in school children’s education: Evidence from a school lesson. Sustainability, 15(18), Article 14025.
Kaldaras, L., Akaeze, H. O., & Reckase, M. D. (2024). Developing valid assessments in the era of generative artificial intelligence. Frontiers in Education, 9, Article 1399377. https://doi.org/10.3389/feduc.2024.1399377
Laupichler, M. C., Aster, A., Haverkamp, N., & Raupach, T. (2023). Development of the “Scale for the assessment of non-experts’ AI literacy” – An exploratory factor analysis. Computers in Human Behavior Reports, 12, Article 100338. https://doi.org/10.1016/j.chbr.2023.100338
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20), 1–12. https://doi.org/10.1145/3313831.3376727
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041
OpenAI. (2024). GPT-4 technical report. https://openai.com/research/gpt-4
Relmasira, S. C., Lai, Y. C., & Donaldson, J. P. (2023). Fostering AI literacy in elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) education in the age of generative AI. Sustainability, 15, Article 13595. https://doi.org/10.3390/su151813595
Rice, S., Crouse, S. R., Winter, S. R., & Rice, C. (2024). The advantages and limitations of using ChatGPT to enhance technological research. Technology in Society, 76, Article 102426.
Tenberga, I., & Daniela, L. (2024). Artificial intelligence literacy competencies for teachers through self-assessment tools. Sustainability, 16(10386), Article 10386. https://doi.org/10.3390/su162310386
Wang, B., Rau, P.-L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929X.2022.2072768
Yu, H. (2024). The application and challenges of ChatGPT in educational transformation: New demands for teachers' roles. Heliyon.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27.