IDEAS home Printed from https://ideas.repec.org/a/gam/jscscx/v14y2025i6p355-d1671151.html
   My bibliography  Save this article

Artificial Intelligence Adoption Amongst Digitally Proficient Trainee Teachers: A Structural Equation Modelling Approach

Author

Listed:
  • María Belén Morales-Cevallos

    (Faculty of Marketing and Communication, Universidad Ecotec, Via Principal Campus Ecotec Km 13.5, Samborondón 092302, Ecuador)

  • Santiago Alonso-García

    (Departament of Didactics and School Organization, Universidad de Granada, 18011 Granada, Spain)

  • Alejandro Martínez-Menéndez

    (Departament of Didactics and School Organization, Universidad de Granada, 18011 Granada, Spain)

  • Juan José Victoria-Maldonado

    (Departament of Didactics and School Organization, Universidad de Granada, 18011 Granada, Spain)

Abstract

The present study examines how pre-service teachers’ digital competence influences their acceptance and use of Artificial Intelligence (AI) in educational settings. Employing a quantitative approach via Structural Equation Modelling (SEM), the authors analyzed self-reported data from Early Childhood and Elementary Education students in Andalusian (Spain) universities. The findings indicate that professional engagement is associated with a critical assessment of AI, focusing on pedagogical and ethical considerations, whereas digital content creation skills promote a more positive and proactive attitude toward AI adoption. These results underscore the importance of teacher education programs that combine technical skills with critical thinking to foster responsible AI integration. This study acknowledges limitations, including its regional scope and cross-sectional design and recommends future longitudinal and comparative research to validate and expand these insights. By addressing these gaps, future studies could enhance our understanding of AI adoption in diverse educational contexts.

Suggested Citation

  • María Belén Morales-Cevallos & Santiago Alonso-García & Alejandro Martínez-Menéndez & Juan José Victoria-Maldonado, 2025. "Artificial Intelligence Adoption Amongst Digitally Proficient Trainee Teachers: A Structural Equation Modelling Approach," Social Sciences, MDPI, vol. 14(6), pages 1-23, June.
    • Handle: RePEc:gam:jscscx:v:14:y:2025:i:6:p:355-:d:1671151
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2076-0760/14/6/355/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2076-0760/14/6/355/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Marko Sarstedt & Christian M. Ringle & Joseph F. Hair, 2022. "Partial Least Squares Structural Equation Modeling," Springer Books, in: Christian Homburg & Martin Klarmann & Arnd Vomberg (ed.), Handbook of Market Research, pages 587-632, Springer.
    2. Hanan Khalil & Said Alsenaidi, 2024. "Teachers’ digital competencies for effective AI integration in higher education in Oman," Journal of Education and e-Learning Research, Asian Online Journal Publishing Group, vol. 11(4), pages 698-707.
    3. Gerbing, David W & Anderson, James C, 1984. "On the Meaning of Within-Factor Correlated Measurement Errors," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(1), pages 572-580, June.
    4. William Black & Barry J. Babin, 2019. "Multivariate Data Analysis: Its Approach, Evolution, and Impact," Springer Books, in: Barry J. Babin & Marko Sarstedt (ed.), The Great Facilitator, pages 121-130, Springer.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Luo, Xi & Cheah, Jun-Hwa & Hollebeek, Linda D. & Lim, Xin-Jean, 2024. "Boosting customers’ impulsive buying tendency in live-streaming commerce: The role of customer engagement and deal proneness," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    2. Chien, Yu-Shyun & Lu, Chung-Cheng, 2025. "Investigating users’ intention to re-use shared electric scooters through a combined behavioral model," Transport Policy, Elsevier, vol. 162(C), pages 533-544.
    3. Al-Shaer, Habiba & Uyar, Ali & Kuzey, Cemil & Karaman, Abdullah S., 2023. "Do shareholders punish or reward excessive CSR engagement? Moderating effect of cash flow and firm growth," International Review of Financial Analysis, Elsevier, vol. 88(C).
    4. Dafna Kariv & Carlo Giglio & Vincenzo Corvello, 2025. "Fostering Entrepreneurial intentions: exploring the interplay of education and endogenous factors," International Entrepreneurship and Management Journal, Springer, vol. 21(1), pages 1-27, December.
    5. Khalil Nimer & Muath Abdelqader & Cemil Kuzey & Ali Uyar, 2024. "Emission targeting and carbon emissions: The moderating effect of female directors," Business Strategy and the Environment, Wiley Blackwell, vol. 33(4), pages 3480-3504, May.
    6. Anna Jasinenko & Josephina Steuber, 2023. "Perceived Organizational Purpose: Systematic Literature Review, Construct Definition, Measurement and Potential Employee Outcomes," Journal of Management Studies, Wiley Blackwell, vol. 60(6), pages 1415-1447, September.
    7. Jinjing Yang & Cong Cao & Chensang Ye & Yangyan Shi, 2022. "Effects of Interface Design and Live Atmosphere on Consumers’ Impulse-Buying Behaviour from the Perspective of Human–Computer Interaction," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    8. Justina GineikienÄ—, 2013. "Consumer Nostalgia Literature Review And An Alternative Measurement Perspective," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 4(2).
    9. Nascimento, Lígia & Correia, Manuela Faia & Califf, Christopher B., 2024. "Towards a bright side of technostress in higher education teachers: Identifying several antecedents and outcomes of techno-eustress," Technology in Society, Elsevier, vol. 76(C).
    10. Chaeyoung Lim & Jongchang Ahn, 2021. "Social Overload and Discontinuance Intention on Facebook: A Comparative Study," Sustainability, MDPI, vol. 13(22), pages 1-17, November.
    11. Oliva M. D. Martins & Rocsana Bucea-Manea-Țoniș & Ana Sofia Coelho & Violeta-Elena Simion, 2022. "Sensory Perception Nudge: Insect-Based Food Consumer Behavior," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    12. Qiu, Lili & Olaru, Doina & Purchase, Sharon, 2024. "Fostering strategic synergy: Empirical insights on aligning innovation activities with competitive strategies," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    13. Golossenko, Artyom & Pillai, Kishore Gopalakrishna & Aroean, Lukman, 2020. "Seeing brands as humans: Development and validation of a brand anthropomorphism scale," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 737-755.
    14. Keerthi Police & Vikas Gautam & Sagar Chandakavate & Rishi Dwesar, 2024. "Modeling determinants of farmers’ purchase behavior: A case of chemical pesticides," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(4), pages 9217-9245, April.
    15. Cobelli, Nicola & Cassia, Fabio & Donvito, Raffaele, 2023. "Pharmacists' attitudes and intention to adopt telemedicine: Integrating the market-orientation paradigm and the UTAUT," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    16. Jurlin, Kresimir & Malekovic, Sanja & Puljiz, Jaksa & Cziraky, Dario & Polic, Mario, 2002. "Covariance structure analysis of regional development data: an application to municipality development assessment," ERSA conference papers ersa02p469, European Regional Science Association.
    17. Pham Quang Huy & Vu Kien Phuc, 2023. "Big data in relation with business intelligence capabilities and e-commerce during COVID-19 pandemic in accountant’s perspective," Future Business Journal, Springer, vol. 9(1), pages 1-21, December.
    18. Soyoung An & Weolho Kim & Bongkoo Lee & Jungho Suh, 2022. "A Study on the Tourism-Related Information Consumption Process of Tourists on Social Networking Sites," Sustainability, MDPI, vol. 14(7), pages 1-16, March.
    19. Meike Rombach & David Dean & Frank Vriesekoop & Bin Jiang & Zeyuan Zhou & Wendy Hao & Wim Koning, 2025. "Understanding factors determining Chinese consumer’s willingness to eat cultured meat, insect, and plant-based proteins," International Review on Public and Nonprofit Marketing, Springer;International Association of Public and Non-Profit Marketing, vol. 22(1), pages 77-109, March.
    20. Michael Hennessy & Amy Bleakley & Martin Fishbein, 2012. "Measurement Models for Reasoned Action Theory," The ANNALS of the American Academy of Political and Social Science, , vol. 640(1), pages 42-57, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jscscx:v:14:y:2025:i:6:p:355-:d:1671151. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.