IJMECS Vol. 17, No. 5, 8 Oct. 2025
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Primary School Students, Artificial Intelligence, Attitude, Scale Development, Exploratory Sequential Design
Based on this gap in the literature, the problem situation identified was deemed worth investigating in terms of contributing to the accumulation of knowledge on the subject area. In addition, it is thought that this study will contribute to future studies on artificial intelligence in primary school education. The aim of this study is to create a Likert-type attitude scale that can be used to determine primary school students’ attitudes towards artificial intelligence. In this study, exploratory sequential design, one of the mixed research method types, was used. A 32-item draft scale form was prepared in the light of the literature review, student opinions collected through a structured interview form and data obtained from field experts. In order to examine the validity of the scale, exploratory and confirmatory factor analyses, item-factor total correlations and item discriminations were evaluated. The goodness of fit values obtained in confirmatory factor analysis were [CMIN=245,020, df=159 (CMIN/df= 1.541), RMSEA= 0.45, RMR= 0.035, GFI= 0.916, AGFI= 0.889, CFI= 0.903, NFI= 0.773, IFI= 0.906]. To evaluate the reliability of the scale, internal consistency coefficient was calculated, and test-retest analysis was performed. Cronbach’s Alpha reliability coefficient for the overall scale was 0.807 and McDonald’s Omega coefficient was 0.816. As a result, it was determined that the Artificial Intelligence Attitude Scale, which consists of 4 factors and 20 items, is an appropriate, valid and reliable tool for evaluating primary school students’ attitudes towards artificial intelligence.
Taha Oruç, Özgen Korkmaz, Murat Kurt, "Artificial Intelligence Attitude Scale for Primary School Students", International Journal of Modern Education and Computer Science(IJMECS), Vol.17, No.5, pp. 29-40, 2025. DOI:10.5815/ijmecs.2025.05.02
[1]C. Elmas. Yapay zeka uygulamaları [Artificial intelligence applications]. Ankara: Seckin Publishing.
[2]N. J. Nilsson. Yapay zekâ geçmişi ve geleceği [Artificial Intelligence Past and Future]. Boğaziçi University Publishing House, İstanbul, pages 386–387, 2019.
[3]S. J. Russell and P. Norvig. Artificial intelligence: A modern approach. Pearson, 2016.
[4]E. B. Adas and B. Erbay. An evaluation on the sociology of artificial intelligence. Gaziantep University Journal of Social Sciences, 21(1):326–337, 2022.
[5]G. Tasci and M. Celebi. A new paradigm in education: Artificial intelligence in higher education. OPUS International Journal of Society Researches, 16(29):2346–2370, 2020.
[6]B. G. Tabachnick and L. S. Fidell. Using multivariate statistics. Pearson, 7th edition, 2019.
[7]G. Arık and S. S. Seferoglu. Artificial intelligence studies in education: Research trends, challenges and solutions. In V. Nabiyev and A. K. Erümit, editors, Artificial Intelligence in Education from Theory to Practice, 3rd edition, pages 259–282. Pegem Akademy, 2022.
[8]G. Meco and F. Costu. Using artificial intelligence in education: A descriptive content analysis study. Karadeniz Technical University Institute of Social Sciences Journal of Social Sciences, 12(23):171–193, 2022.
[9]N. Tekin. Artificial intelligence in education: A content analysis on the trends of Turkish research. Necmettin Erbakan University Ereğli Education Faculty Journal, 5(Special Issue):387–411, 2023.
[10]S. G. A. Ali. Using an artificial intelligence application for developing primary school pupils’ oral language skills. Journal of Education, 75:68–110, 2020.
[11]N. E. E. A. Fattah. Effectiveness of using the artificial intelligence in behavioral disorders management among the third-grade primary students. Eurasian Journal of Educational Research, 101(101):33–48, 2022.
[12]C. Guzey, O. Cakır, M. H. Athar, and E. Yurdaoz. Examining the trends in research on artificial intelligence in education. Journal of Information and Communication Technologies, 5(1):67–78, 2023.
[13]M. Akdeniz and F. Ozdinc. Analyzing Turkish studies on artificial intelligence in education. Van Yüzüncü Yıl University Journal of Faculty of Education, 18(1):912–932, 2021.
[14]E. Arugaslan and H. Civril. Data mining and artificial intelligence studies in the field of education in Türkiye. International Journal of Technological Sciences, 13(2):81–89, 2021.
[15]F. Asık, A. Yildiz, S. Kilinc, N. Aytekin, R. Adali, and K. Kurnaz. Impact of artificial intelligence on education. International Journal of Social and Humanities Sciences Research (JSHSR), 10(98):2100–2107, 2023.
[16]E. Bayindir. Analyzing artificial intelligence studies in the field of education with social network analysis. Master’s thesis, Bahçeşehir University, İstanbul, 2023.
[17]L. Chen, P. Chen, and Z. Lin. Artificial intelligence in education: A review. IEEE Access, 8:75264–75278, 2020.
[18]F. O. Gul. Artificial intelligence in education: Opportunities and risks for education academics. In 6th International Higher Education Studies Conference (IHEC), page 7, 2023.
[19]S. Kayahan. Artificial intelligence in educational applications: A review. In 6th International Instructional Technologies and Teacher Education Symposium, Trakya University, Edirne, 2018.
[20]A. Salido, A. K. Kenedi, and D. A. A. Putri. The use of artificial intelligence for primary school mathematics: A bibliometric analysis. In International Conference on Teaching and Learning, volume 1(1), 2023.
[21]W. Yang. Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence, 3:100061, 2022.
[22]X. Zhao. Education challenges and coping mechanisms for artificial intelligence in primary and secondary schools. Science Insights, 41(5):675–679, 2022.
[23]A. Aktas. Yönetici ve öğretmen görüşlerine göre yapay zekâ: bir metafor çalışması [Artificial intelligence according to the views of administrators and teachers: a metaphor study]. In 1st National Congress on Artificial Intelligence Applications in Education Full Text Proceedings, pages 4–36, Şanlıurfa, Türkiye, 2021.
[24]E. Demirtas and U. E. Turksoy. Primary school education stakeholders’ metaphorical perceptions of artificial intelligence. In Ufuk University 2nd International Congress on Social Sciences, pages 194–207, 2023.
[25]S. Sacan, K. T. Yaralı, and S. Z. Kavruk. Investigation of children’s metaphorical perceptions of the concept of artificial intelligence. Mehmet Akif Ersoy University Journal of Faculty of Education, 64:274–296, 2022.
[26]V. Kuprenko. Artificial intelligence in education: Benefits, challenges, and use cases. Accessed at https://medium.com/towards-artificial-intelligence/artificial-intelligence-in-education-benefits-challenges-and-use-cases-db52d8921f7a, 2020.
[27]K. Tozduman Yarali. Dikkat, bellek ve öğrenmede medyanın etkisi [The effect of media on attention, memory and learning]. (S. Kılıc, Ed.) Çocuk ve Medya içinde [In Children and Media] (pp. 66-93). Pegem Akademy, 2021.
[28]M. Inceoglu. Tutum-algı iletişim [Attitude-perception communication (6th Edition)]. Siyasal Kitabevi, 6th edition, 2011.
[29]M. I. Dibek and M. S. Kursad. Tutum ve tutum ölçekleme teknikleri. [Attitude and attitude scaling techniques]. (H. D. Gulleroglu & O. C. Bokeoglu, Eds.) Kuramdan Uygulamaya Tutum Ölçeği Geliştirme Kılavuzu içinde [In Attitude Scale Development Guide from Theory to Practice] (pp. 49-78). Pegem Akademy., 2023.
[30]E. D. Dulger and M. Koklu. A scale development study to determine the views of school administrators and teachers on the use of artificial intelligence in education. ISPEC International Journal of Social Sciences & Humanities, 7(1):154–174, 2023.
[31]D. Ferikoglu. Artificial intelligence awareness level scale for teachers: Reliability and validity study. Master’s thesis, Bahçeşehir University, İstanbul, 2021.
[32]A. Schepman and P. Rodway. Initial validation of the general attitudes towards artificial intelligence scale. Computers in Human Behavior Reports, 1:100014, 2020.
[33]B. Wang, P. L. P. Rau, and T. Yuan. Measuring user competence in using artificial intelligence: Validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9):1324–1337, 2023.
[34]Y. Y. Wang and Y. W. Chuang. Artificial intelligence self-efficacy: Scale development and validation. Education and Information Technologies, pages 1–24, 2024.
[35]F. G. K. Yilmaz, R. Yilmaz, and M. Ceylan. Generative artificial intelligence acceptance scale: A validity and reliability study. International Journal of Human–Computer Interaction, pages 1–13, 2023.
[36]B. Akkaya, A. Ozkan, and H. Ozkan. Artificial intelligence anxiety scale: Turkish adaptation, validity and reliability study. Alanya Academic Overview, 5(2):1125–1146, 2021.
[37]F. Kaya, F. Aydin, A. Schepman, P. Rodway, O. Yetisensoy, and M. Demir Kaya. The roles of personality traits, AI anxiety, and demographic factors in attitudes toward artificial intelligence. International Journal of Human–Computer Interaction, 40(2):497–514, 2024.
[38]M. Polatgil and A. Guler. Adaptation of artificial intelligence literacy scale into Turkish. Journal of Quantitative Research in Social Sciences, 3(2):99–114, 2023.
[39]F. G. K. Yilmaz and R. Yilmaz. Adaptation of artificial intelligence literacy scale into Turkish. Journal of Information and Communication Technologies, 5(2):172–190, 2023.
[40]J. W. Creswell. Research design: Qualitative, quantitative and mixed method approaches. Eğiten Publications, Ankara, 2017.
[41]B. Karakoc. Olgubilim (Fenomenoloji) araştırması [Phenomenology research] (S. Sen & I. Yildirim, Eds.). Eğitimde araştırma yöntemleri içinde [In Research methods in education] (pp. 263-282). Nobel Academic Publishing, 2019.
[42]M. Q. Patton. Nitel araştırma ve değerlendirme yöntemleri (3. Baskıdan Çeviri) [Qualitative research and evaluation methods (Translation from 3rd Edition)] (M. Butun & S.B. Demir, Trans. Eds.). Ankara: Pegem Akademy, 2014.
[43]S. Canbazoglu Bilici. Örnekleme yöntemleri [Sampling methods] (H. Özmen & O. Karamustafaoğlu, Eds.). Eğitimde Araştırma Yöntemleri (2. Baskı) içinde [In Research Methods in Education (2nd Edition)] (pp. 56-82). Pegem Akademy.
[44]Kaiser, H.F. (1970). A second generation little jiffy. Psychometrika, 35, 401–415, 2019.
[45]S. Buyukozturk. Sosyal bilimler için veri analizi el kitabı (28. Baskı) [Handbook of data analysis for social sciences (28th Edition)]. Ankara: Pegem Akademy, 2020.
[46]R. A. Peterson. A meta-analysis of variance accounted for and factor loadings in exploratory factor analysis. Marketing Letters, 11(3):261–276, 2000.
[47]K. Schermelleh-Engel, H. Moosbrugger, and H. Müler. Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research, 8(2):23–74, 2003.
[48]E. Tavsancil. Tutumların ölçülmesi ve spss ile veri analizi [Measurement of attitudes and data analysis with spss]. Yargı Publishing House, Ankara, 2005.
[49]G. Y. Peters. The alpha and the omega of scale reliability and validity: Why and how to abandon Cronbach’s alpha and the route towards more comprehensive assessment of scale quality. European Health Psychologist, 16(2):56–69, 2014.
[50]V. Osetskyi, A. Vitrenko, I. Tatomyr, S. Bilan, and Y. Hirnyk. Artificial intelligence application in education: Financial implications and prospects. Financial and Credit Activity: Problems of Theory and Practice, 2(33):574–584, 2020.
[51]R. B. Kline. Principles and practice of structural equation modeling. Guilford Publications, 2023.
[52]P. M. Bentler and C. P. Chou. Practical issues in structural modeling. Sociological Methods & Research, 16(1):78–117, 1987.
[53]D. M. McNeish. On using Bayesian methods to address problems of estimation and model comparison in psychometrics. Psychological Methods, 23(4):551–573, 2018.