Adaptation of Artificial Intelligence Literacy Scale into Turkish: A Sample of Pre-Service Teachers
Year 2024,
Volume: 11 Issue: 4, 688 - 701
Hilal Uğraş
,
Merve Doğan
,
Mustafa Uğraş
Abstract
This study aims to adapt the Al-LS translated by Wang et al. (2022) into Turkish and create a scale suitable for assessing the AI-L of pre-service teachers. The study used the survey method within the scope of the quantitative method. The sample of the study consisted of 440 pre-service teachers (pre-school and primary pre-service teachers) from a state university in the Eastern Anatolia Region of Turkey. The original scale consists of 12 items, 4 factors, and a 5-point Likert-type structure. In the first stage, we conducted translation studies to assess the language validity of the adapted scale. Then, the data collected from the part of the sample determined for EFA (Exploratory Factor Analysis) were analyzed. The results show that the adapted scale preserves the original scale structure. The data collected from the part of the sample designated for CFA (Confirmatory Factor Analysis) was also analyzed. The results of the analysis show that the scale has acceptable and good-fit indices. In terms of reliability, Cronbach’s Alpha reliability coefficients show that the scale has a reliable structure. The results of the analysis indicate that the scale adapted to Turkish has a valid and reliable structure.
Ethical Statement
The necessary permissions were obtained from Fırat University Socıal And Bıberal Scıences Research Ethıcs Board on 29.01.2024 with the number 21730.
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Year 2024,
Volume: 11 Issue: 4, 688 - 701
Hilal Uğraş
,
Merve Doğan
,
Mustafa Uğraş
References
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- Ahmad, S. F., Rahmat, M. K., Mubarik, M. S., Alam, M. M., & Hyder, S. I. (2021). Artificial intelligence and its role in education. Sustainability, 13(22), 12902. https://doi.org/10.3390/su132212902
- Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
- Alemdar, M. Y., & Köker, N. E. (2013). Öğrencilerin Okul Kültürü Algisi Üzerine Amprik Bir Araştirma: Ege Üniversitesi İletişim Fakültesi Örneği. Global Media Journal: Turkish Edition, 3(6).
- Almazroa, H., & Alotaibi, W. (2023). Teaching 21st century skills: Understanding the depth and width of the challenges to shape proactive teacher education programmes. Sustainability, 15(9), 7365. https://doi.org/10.3390/su15097365
- Aravantinos, S., Lavidas, K., Voulgari, I., Papadakis, S., Karalis, T., & Komis, V. (2024). Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus. Education Sciences, 14(7), 744. https://doi.org/10.3390/educsci14070744
- Asparouhov, T., & Muthén, B. (2009). Exploratory structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 16(3), 397–438. https://doi.org/10.1080/10705510903008204
- 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, 100179.
https://doi.org/10.1016/j.caeo.2024.100179
- Brown, T. A., & Moore, M. T. (2012). Confirmatory factor analysis. Handbook of Structural Equation Modeling, 361, 379.
Bryman, A., & Cramer, D. (2002). Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Routledge. https://doi.org/10.4324/9780203471548
- Burgsteiner, H., Kandlhofer, M., & Steinbauer, G. (2016). Irobot: Teaching the basics of artificial intelligence in high schools. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1).
https://doi.org/10.1609/aaai.v30i1.9864
- Büyüköztürk, Ş. (2018). Sosyal bilimler için veri analizi el kitabı. Pegem Atıf İndeksi, 001–214. https://doi.org/10.14527/9789756802748
- Can, A. (2017). Quantitative data analysis with SPSS. Ankara: Pegem Akademi.
- Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245–276. https://doi.org/10.1207/s15327906mbr0102_10
- Çelebi, C., Yılmaz, F., Demir, U., & Karakuş, F. (2023). Artificial intelligence literacy: An adaptation study. Instructional Technology and Lifelong Learning, 4(2), 291–306. https://doi.org/10.52911/itall.1401740
- Chenqi, L., Guoqing, L., & Xiangchun, H. (2023). Measuring Artificial Intelligence Literacy of Pre-service Teachers at a University in Northwest China. 2023 Twelfth International Conference of Educational Innovation through Technology (EITT), 100–105. https://doi.org/10.1109/EITT61659.2023.00027
- Costello, A. B., & Osborne, J. (2019). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10(1), 7.
- Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
- Erdoğan, T. E., & Ekşioğlu, S. (2024). Yapay Zekâ Okuryazarlığı Ölçeği’nin Türkçeye Uyarlanması. Türk Eğitim Bilimleri Dergisi, 22(2), 1196–1211. https://doi.org/10.37217/tebd.1496716
- Faruqe, F., Watkins, R., & Medsker, L. (2021). Competency model approach to AI literacy: Research-based path from initial framework to model. arXiv Preprint arXiv:2108.05809. https://doi.org/10.54364/AAIML.2022.1140
Field, A. (2013). Discovering statistics using IBM SPSS statistics. sage.
- González-Pérez, L. I., & Ramírez-Montoya, M. S. (2022). Components of Education 4.0 in 21st century skills frameworks: Systematic review. Sustainability, 14(3), 1493. https://doi.org/10.3390/su14031493
- Heckler, C. E. (1996). A step-by-step approach to using the SASTM system for factor analysis and structural equation modeling. Taylor & Francis. https://doi.org/10.2307/1270628
- Holmes, W., & Porayska-Pomsta, K. (2023). The ethics of artificial intelligence in education. Routledge Taylor. https://doi.org/10.4324/9780429329067
- İpek, Z. H., Gözüm, A. İ. C., Papadakis, S., & Kallogiannakis, M. (2023). Educational Applications of the ChatGPT AI System: A Systematic Review Research. Educational Process :International Journal, 12(3), 26–55. https://doi.org/10.22521/edupij.2023.123.2
- Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/j.bushor.2018.03.007
- Jiang, J., Yang, Z., Ferreira, A., & Zhang, L. (2022). Control and autonomy of microrobots: Recent progress and perspective. Advanced Intelligent Systems, 4(5), 2100279. https://doi.org/10.1002/aisy.202100279
- Johnson, R. B., & Christensen, L. (2019). Educational research: Quantitative, qualitative, and mixed approaches. Sage publications.
- Kandlhofer, M., Steinbauer, G., Hirschmugl-Gaisch, S., & Huber, P. (2016). Artificial intelligence and computer science in education: From kindergarten to university. 2016 IEEE Frontiers in Education Conference (FIE), 1–9. https://doi.org/10.1109/FIE.2016.7757570
- 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
- Kim, J. (2024). Leading teachers’ perspective on teacher-AI collaboration in education. Education and Information Technologies, 29(7), 8693–8724. https://doi.org/10.1007/s10639-023-12109-5
- Kirschner, P., & Selinger, M. (2003). The state of affairs of teacher education with respect to information and communications technology. Technology, Pedagogy and Education, 12(1), 5–17. https://doi.org/10.1080/14759390300200143
- Kong, S.-C., Cheung, M.-Y. W., & Tsang, O. (2024). Developing an artificial intelligence literacy framework: Evaluation of a literacy course for senior secondary students using a project-based learning approach. Computers and Education: Artificial Intelligence, 6, 100214. https://doi.org/10.1016/j.caeai.2024.100214
- Lameras, P., & Arnab, S. (2021). Power to the Teachers: An Exploratory Review on Artificial Intelligence in Education. Information, 13(1), 14. https://doi.org/10.1016/j.caeai.2024.100214
- Lanning, S., & Gerrity, C. (2022). Concise guide to information literacy. Bloomsbury Publishing USA. https://doi.org/10.5040/9798400630101
- Lavidas, K., Apostolou, Z., & Papadakis, S. (2022). Challenges and opportunities of mathematics in digital times: Preschool teachers’ views. Education Sciences, 12(7), 459. https://doi.org/10.3390/educsci12070459
- 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, 1–16. https://doi.org/10.1145/3313831.3376727
- Lubin, I. A. (2021). ICT and International Learning Ecologies: Representation and Sustainability Across Contexts. Routledge. https://doi.org/10.4324/9780429345463
- Markauskaite, L., Marrone, R., Poquet, O., Knight, S., Martinez-Maldonado, R., Howard, S., Tondeur, J., De Laat, M., Shum, S. B., & Gašević, D. (2022). Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI? Computers and Education: Artificial Intelligence, 3, 100056. https://doi.org/10.1016/j.caeai.2022.100056
- Marsh, H. W., Hau, K.-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling, 11(3), 320–341. https://doi.org/10.1207/s15328007sem1103_2
- Menard, S. (2002). Applied logistic regression analysis (Issue 106). Sage. https://doi.org/10.4135/9781412983433
- Muthmainnah, Ibna Seraj, P. M., & Oteir, I. (2022). Playing with AI to Investigate Human‐Computer Interaction Technology and Improving Critical Thinking Skills to Pursue 21st Century Age. Education Research International, 2022(1), 6468995. https://doi.org/10.1155/2022/6468995
- 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
- Ng, W. (2012). Can we teach digital natives digital literacy? Computers & Education, 59(3), 1065–1078. https://doi.org/10.1016/j.compedu.2012.04.016
- Nzomo, P., McKenzie, P., Ajiferuke, I., & Vaughan, L. (2021). Towards a definition of multilingual information literacy (MLIL): An essential skill for the 21st century. Journal of Library Administration, 61(7), 897–920. https://doi.org/10.1080/01930826.2021.1972737
- Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS. McGraw-hill education (UK). https://doi.org/10.4324/9781003117445
- Robinson, O. C. (2014). Sampling in interview-based qualitative research: A theoretical and practical guide. Qualitative Research in Psychology, 11(1), 25–41. https://doi.org/10.1080/14780887.2013.801543
- Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23–74.
- Searle, J. (2020). Developing literacy. In Developing vocational expertise (pp. 51–80). Routledge. https://doi.org/10.4324/9781003115342-5
- Seifi, L., Habibi, M., & Ayati, M. (2020). The effect of information literacy instruction on lifelong learning readiness. IFLA Journal, 46(3), 259–270. https://doi.org/10.1177/0340035220931879
- Shah, P. (2023). AI and the Future of Education: Teaching in the Age of Artificial Intelligence. John Wiley & Sons.
- Stembert, N., & Harbers, M. (2019). Accounting for the human when designing with AI: challenges identified. CHI’19-Extended Abstracts, Glasgow, Scotland Uk—May 04-09, 2019.
- Su, G. (2018). Unemployment in the AI Age. AI Matters, 3(4), 35–43. https://doi.org/10.1145/3175502.3175511
- Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2013). Using multivariate statistics (Vol. 6). pearson Boston, MA.
- Tarafdar, M., Beath, C. M., & Ross, J. W. (2019). Using AI to enhance business operations. MIT Sloan Management Review, 60(4). https://doi.org/10.7551/mitpress/12588.003.0015
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