Investigating the factors affecting the intention to use AI chatbots in STEM education app: A hybrid structural equation modelling and artificial neural network

Morshada khanam  Mim; Mst. Tahmina Jerin Arju; Mahady Hasan; Farzana Sadia; Shipra Banik

Research Article

2026, 11(1), Article No: 32

Investigating the factors affecting the intention to use AI chatbots in STEM education app: A hybrid structural equation modelling and artificial neural network

Morshada khanam Mim ¹ ^* , Mst. Tahmina Jerin Arju ¹, Mahady Hasan ¹, Farzana Sadia ¹, Shipra Banik ¹

¹ Independent University Bangladesh, BANGLADESH
^* Corresponding Author

Published in Volume 11 Issue 1: 02 Jun 2026

Download: 3

OPEN ACCESS FULL TEXT (PDF)

Abstract

This study explores the impact of Artificial Intelligence (AI)-powered applications in Science, Technology, Engineering, and Mathematics (STEM) education, emphasizing their role in improving students’ problem-solving skills and self-efficacy. It examines how personal factors such as ICT self-efficacy and self-directed learning (SDL), along with technological aspects like perceived ease of use (PEU) and perceived convenience (PC), shape students’ engagement with AI-driven tools. Using a quantitative method, survey data were collected from 117 students during February–March 2025. The research employed the Structured Predictive Latent Semantic System (SPLSS) model and Artificial Neural Network (ANN), validated through Structural Equation Modeling (SEM), to ensure reliability and predictive accuracy. Results show that AI tools significantly enhance problem-solving and self-efficacy. PC and intention to use were strong predictors of chatbot utilization, while ICT self-efficacy and PEU influenced attitudes and behavioral intentions. Importance-Performance Map Analysis (IPMA) revealed convenience as most impactful, and self-efficacy as least. All hypotheses were supported, confirming the model’s robustness. The study concludes that AI-driven applications create personalized, engaging, and confidence-boosting STEM learning experiences, highlighting the need for user-friendly, contextually adaptive AI tools and suggesting future research on long-term impacts and scalability for inclusive STEM education

Figure 1. Research model

Al-Areeshi, Z. M. (2025). Artificial intelligence in education: A future vision. مجلة العلوم التربوية و النفسية، 9(1), 142–156. https://doi.org/10.26389/AJSRP.M181224
Ayanwale, M. A., & Ndlovu, M. (2024). Investigating factors of students' behavioral intentions to adopt chatbot technologies in higher education: Perspective from expanded diffusion theory of innovation. Computers in Human Behavior Reports, 14, 100396. https://doi.org/10.1016/j.chbr.2024.100396
Bayanova, A. R., Orekhovskaya, N. A., Sokolova, N. L., Shaleeva, E. F., Knyazeva, S. A., & Budkevich, R. L. (2023). Exploring the role of motivation in STEM education: A systematic review. EURASIA Journal of Mathematics, Science and Technology Education, 19(4), em2250. https://doi.org/10.29333/ejmste/13086
Bergdahl, N., & Sjöberg, J. (2025). Attitudes, perceptions and AI self-efficacy in K-12 education. Computers and Education: Artificial Intelligence, 8, 100358. https://doi.org/10.1016/j.caeai.2024.100358
Dogutas, A. (2025). A comparative analysis of immigrant children's educational policies: Türkiye and the United States. European Journal of Education & Language Review, 1(1), 2. https://doi.org/10.20897/ejelr/17313
Esiyok, E., Sahin, G., & Kemal, G. K. (2025). Acceptance of educational use of AI chatbots in the context of self-directed learning with technology and ICT self-efficacy of undergraduate students. International Journal of Human–Computer Interaction, 41(1), 641–650. https://doi.org/10.1080/10447318.2024.2303557
Hwang, Y., & Yi, W. (2025). The influence of generative artificial intelligence on creative cognition of design students: A chain mediation model of self-efficacy and anxiety. Frontiers in Psychology, 15, 1455015. https://doi.org/10.3389/fpsyg.2024.1455015
Işıklı, Ş., & Fazlıoğlu, E. F. (2026). Technological effects on gender studies: An intersectional perspective. Feminist Encounters: A Journal of Critical Studies in Culture and Politics, 10(1). https://doi.org/10.20897/femenc/17998
Islam, M., Das, H. K., Akter, S., & Hossain, M. D. (2026). Investigating the challenges of secondary students in reading comprehension skills in Bangladesh. Asia Pacific Journal of Education and Society, 14(1), 5. https://doi.org/10.20897/apjes/17957
Kong, S. C., Zhu, J., & Yang, Y. N. (2025). Developing and validating a scale of empowerment in using artificial intelligence for problem-solving for senior secondary and university students. Computers and Education: Artificial Intelligence, 8, 100359. https://doi.org/10.1016/j.caeai.2024.100359
Lai, R. P. (2023). Harnessing pedagogical innovation and educational technology to revolutionize STEM beyond the classroom: Future directions. STEM Education Review, 1. https://doi.org/10.54844/stemer.2023.0460
Lee, Y. F., Hwang, G. J., & Chen, P. Y. (2022). Impacts of an AI-based chatbot on college students' after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational Technology Research and Development, 70(5), 1843–1865. https://doi.org/10.1007/s11423-022-10142-8
Mokmin, N. A. M., Ariffin, U. H., & Hamizi, M. A. A. M. (2022). Educators' perspective on the use of augmented reality to create STEM learning material. Journal of ICT in Education, 9(2), 191–200. https://doi.org/10.37134/jictie.vol9.2.14.2022
Montejo, D. C. O., Diocares, K. A. B., Adol, K. H. S., & Mendoza, S. G. (2025). Evaluating the impact of AI-powered tools on programming skills development among IT students at Davao Oriental State University (DOrSU). Ho Chi Minh City Open University Journal of Science – Social Sciences, 16(2). https://doi.org/10.46223/HCMCOUJS.soci.en.16.2.3519.2026
Obiwuru, O. M. (2024). Impacts of AI-chatbots usage on the knowledge construction and critical reasoning of university students: A mixed methods approach in a Nigerian university [Unpublished manuscript].
Parsakia, K. (2023). The effect of chatbots and AI on the self-efficacy, self-esteem, problem-solving and critical thinking of students. Health Nexus, 1(1), 71–76. https://doi.org/10.61838/hn.1.1.14
Pellas, N. (2025). The impact of AI-generated instructional videos on problem-based learning in science teacher education. Education Sciences, 15(1), 102. https://doi.org/10.3390/educsci15010102
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(18), 13595. https://doi.org/10.3390/su151813595
Roca, M. D. L., Chan, M. M., Garcia-Cabot, A., Garcia-Lopez, E., & Amado-Salvatierra, H. (2024). The impact of a chatbot working as an assistant in a course for supporting student learning and engagement. Computer Applications in Engineering Education, 32(5), e22750. https://doi.org/10.1002/cae.22750
Rönkkö, M., & Cho, E. (2022). An updated guideline for assessing discriminant validity. Organizational Research Methods, 25(1), 6–14. https://doi.org/10.1177/1094428120968614
Sultan, Y., Dautova, G., & Dalle, J. (2025). Examining the relationship among artificial intelligence literacy, cultural literacy, and intercultural communication proficiency of philology students. Journal of Ethnic and Cultural Studies, 12(5), 345–362. https://doi.org/10.29333/ejecs/2839
Sun, D., Zhan, Y., Wan, Z. H., Yang, Y., & Looi, C. K. (2025). Identifying the roles of technology: A systematic review of STEM education in primary and secondary schools from 2015 to 2023. Research in Science & Technological Education, 43(1), 145–169. https://doi.org/10.1080/02635143.2023.2251902
Tam, H. L., Chan, A. Y. F., & Lai, O. L. H. (2020). Gender stereotyping and STEM education: Girls' empowerment through effective ICT training in Hong Kong. Children and Youth Services Review, 119, 105624. https://doi.org/10.1016/j.childyouth.2020.105624
Tashtoush, M. A., Al-Qasimi, A. B., Shirawia, N. A., & Rasheed, N. M. (2024). The impact of STEM approach to developing mathematical thinking for calculus students among Sohar University. European Journal of STEM Education, 9(1), 13. https://doi.org/10.20897/ejstem/15205
Tuanpusa, S., Sritragarn, T., Kaewthongyai, Y., & Tuenpusa, P. (2026). From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education. Journal of Interdisciplinary Research in Artificial Intelligence and Society, 2(1), Article 3. https://doi.org/10.20897/jirais/18573
Yu, W., Zheng, Z., & He, J. (2025). Integrating entrepreneurial education into STEM education: A systematic review. Research in Science Education, 55(1), 159–185. https://doi.org/10.1007/s11165-024-10193-2

APA 7th edition

In-text citation: (Mim et al., 2026)
Reference: Mim, M. K., Arju, M. T. J., Hasan, M., Sadia, F., & Banik, S. (2026). Investigating the factors affecting the intention to use AI chatbots in STEM education app: A hybrid structural equation modelling and artificial neural network. European Journal of STEM Education, 11(1), Article 32.

AMA 10th edition

In-text citation: (1), (2), (3), etc.
Reference: Mim MK, Arju MTJ, Hasan M, Sadia F, Banik S. Investigating the factors affecting the intention to use AI chatbots in STEM education app: A hybrid structural equation modelling and artificial neural network. European Journal of STEM Education. 2026;11(1), 32.

Chicago

In-text citation: (Mim et al., 2026)
Reference: Mim, Morshada khanam, Mst. Tahmina Jerin Arju, Mahady Hasan, Farzana Sadia, and Shipra Banik. "Investigating the factors affecting the intention to use AI chatbots in STEM education app: A hybrid structural equation modelling and artificial neural network". European Journal of STEM Education 2026 11 no. 1 (2026): 32.

Harvard

In-text citation: (Mim et al., 2026)
Reference: Mim, M. K., Arju, M. T. J., Hasan, M., Sadia, F., and Banik, S. (2026). Investigating the factors affecting the intention to use AI chatbots in STEM education app: A hybrid structural equation modelling and artificial neural network. European Journal of STEM Education, 11(1), 32.

MLA

In-text citation: (Mim et al., 2026)
Reference: Mim, Morshada khanam et al. "Investigating the factors affecting the intention to use AI chatbots in STEM education app: A hybrid structural equation modelling and artificial neural network". European Journal of STEM Education, vol. 11, no. 1, 2026, 32.

Vancouver

Keywords

SPLSS model, problem-solving skills, ICT self-efficacy, AI-powered STEM education, ANN model

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Submit My Manuscript