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Students’ Intention toward Artificial Intelligence in the Context of Digital Transformation

Author

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  • Nikola Milicevic

    (Department for Trade, Marketing and Logistics, Faculty of Economics in Subotica, University of Novi Sad, Segedinski put 9-11, 24000 Subotica, Serbia)

  • Branimir Kalas

    (Department for Financial and Banking Management, Faculty of Economics in Subotica, University of Novi Sad, Segedinski put 9-11, 24000 Subotica, Serbia)

  • Nenad Djokic

    (Department for Trade, Marketing and Logistics, Faculty of Economics in Subotica, University of Novi Sad, Segedinski put 9-11, 24000 Subotica, Serbia)

  • Borka Malcic

    (Department of Pedagogy, Faculty of Philosophy, University of Novi Sad, Zorana Djindjica 2, 21102 Novi Sad, Serbia)

  • Ines Djokic

    (Department for Trade, Marketing and Logistics, Faculty of Economics in Subotica, University of Novi Sad, Segedinski put 9-11, 24000 Subotica, Serbia)

Abstract

The analysis of students’ attitudes and perceptions represents a basis for enhancing different types of activities, including teaching, learning, assessment, etc. Emphasis might be placed on the implementation of modern procedures and technologies, which play an important role in the process of digital transformation. Among them is artificial intelligence—a technology that has already been found to be applicable in various sectors. When it comes to education, several AI-based tools and platforms can be used by students and teachers. Besides offering customized learning experiences, AI may play a significant part in establishing the concept of sustainability, especially when concerning the achievement of sustainable development goal 4. This paper investigates students’ intention to use artificial intelligence in education, taking three predictors from the UTAUT model and AI awareness as the moderator. The analysis included students from the Autonomous Province of Vojvodina, Republic of Serbia. For the purpose of the research, the partial least squares structural equation modeling (PLS-SEM) method was applied. Hereby, two models (without and with a moderator) were tested to examine the main and moderating effects, respectively. Regarding the results, while interaction terms were non-significant, the impacts of performance expectancy, effort expectancy, and social influence on behavioral intention were significant and positive.

Suggested Citation

  • Nikola Milicevic & Branimir Kalas & Nenad Djokic & Borka Malcic & Ines Djokic, 2024. "Students’ Intention toward Artificial Intelligence in the Context of Digital Transformation," Sustainability, MDPI, vol. 16(9), pages 1-15, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3554-:d:1381762
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    References listed on IDEAS

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    1. Sara Mehrab Daniali & Sergey Evgenievich Barykin & Marzieh Zendehdel & Olga Vladimirovna Kalinina & Valeriia Vadimovna Kulibanova & Tatiana Robertovna Teor & Irina Anatolyevna Ilyina & Natalia Sergeev, 2022. "Exploring UTAUT Model in Mobile 4.5G Service: Moderating Social–Economic Effects of Gender and Awareness," Social Sciences, MDPI, vol. 11(5), pages 1-13, April.
    2. Vu Khanh Quy & Bui Trung Thanh & Abdellah Chehri & Dao Manh Linh & Do Anh Tuan, 2023. "AI and Digital Transformation in Higher Education: Vision and Approach of a Specific University in Vietnam," Sustainability, MDPI, vol. 15(14), pages 1-16, July.
    3. Rocsana Bucea-Manea-Țoniş & Valentin Kuleto & Simona Corina Dobre Gudei & Costin Lianu & Cosmin Lianu & Milena P. Ilić & Dan Păun, 2022. "Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
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