The Impact of Advanced Teaching Tools on Uni-versity Teachers' Adoptive Intention in Sichuan in the Age of Artifi-cial Intelligence
DOI:
https://doi.org/10.56910/literacy.v4i2.2369Keywords:
Advanced Teaching Tools, Adoptive Intention, Age of Artificial IntelligenceAbstract
The Impact of Advanced Teaching Tools on University Teachers' Adoptive Intention in Sichuan in the Age of Artificial Intelligence" explores the significant relationship between innovative teaching tools and university educators' willingness to integrate artificial intelligence technologies into their practices. The study highlights that educators’ positive experiences with advanced teaching tools enhance their perceptions of usability and effectiveness, leading to a greater intention to adopt these technologies. It also examines the role of supportive artificial intelligence policies, which promote ethical usage and provide necessary training, as crucial factors influencing adoption. The findings suggest that fostering an environment that encourages innovative practices and addresses concerns about AI tools can significantly improve educational outcomes. Overall, the research underscores the importance of strategic institutional support in facilitating the successful integration of AI technologies in higher education through a sample of 395 university teachers in Sichuan.
References
Bauwens, R., Muylaert, J., Clarysse, E., Audenaert, M., and Decramer, A., “Teachers’ acceptance and use of digital learning environments after hours: Implications for work-life balance and the role of integration preference,” Computers in Human Behavior, vol. 112, 2020.
Ding, A.-C. E., Shi, L., Yang, H., and Choi, I., “Enhancing teacher AI literacy and integration through different cases in teacher professional development,” Computers and Education Open, vol. 6, pp. 191–215, 2024.
Haleem, A., Javaid, M., Qadri, M. A., and Suman, R., “Understanding the role of digital technologies in education: A review,” Sustainable Operations and Computers, vol. 3, pp. 275–285, 2022.
Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., and Bassey, B. A., “Exploring the potential of artificial intelligence tools in educational measurement and assessment,” Eurasia Journal of Mathematics, Science and Technology Education, vol. 19, no. 8, pp. 23–41, 2023.
Venkatesh, V., Thong, J., and Xu, X., “Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology,” MIS Quarterly, vol. 36, no. 1, pp. 157–178, 2012.
Hermita, N., Wijaya, T.-W., Yusron, E., Abidin, Y., Alim, J.-A., and Putra, Z.-H., “Extending the unified theory of acceptance and use of technology to understand the acceptance of digital textbooks for elementary school in Indonesia,” Frontiers in Education, vol. 8, pp. 55–72, 2023.
Jang, M., and Lee, H.-W., “Pre-service teachers’ education needs for AI-based education competency,” Educational Technology International, vol. 24, no. 2, pp. 143–168, 2023.
Runge, I., Hebibi, F., and Lazarides, R., “Acceptance of pre-service teachers towards artificial intelligence (AI): The role of AI-related teacher training courses and AI-TPACK within the technology acceptance model,” Education Sciences, vol. 5, no. 2, pp. 167–182, 2025.
Celik, I., Dindar, M., Muukkonen, H., and Järvelä, S., “The promises and challenges of artificial intelligence for teachers: A systematic review of research,” TechTrends, vol. 66, pp. 616–630, 2022.
Lebo, C., and Brown, N., “Integrating artificial intelligence (AI) simulations into undergraduate nursing education,” Nursing Education Perspectives, vol. 45, pp. 55–56, 2024.
Gamage, K.-A., Dehideniya, S.-P., Xu, Z., and Tang, X., “ChatGPT and higher education assessments: More opportunities than concerns?,” Journal of Applied Learning and Teaching, vol. 6, pp. 358–369, 2023.
Fischer, J., Bearman, M., Boud, D., and Tai, J., “How does assessment drive learning? A focus on students’ development of evaluative judgement,” Assessment & Evaluation in Higher Education, vol. 49, pp. 233–245, 2023.
Fan, P., and Jiang, Q., “Exploring the factors influencing continuance intention to use AI drawing tools: Insights from designers,” Systems, vol. 12, no. 3, pp. 68–83, 2024.
De la Vall, R.-R., and Araya, F.-G., “Exploring the benefits and challenges of AI-language learning tools,” International Journal of Social Sciences and Humanities Invention, vol. 10, pp. 7569–7576, 2023.
Mirra, G., and Pugnale, A., “Expertise, playfulness, and analogical reasoning: Three strategies to train artificial intelligence for design applications,” Architectural Structures and Construction, vol. 2, pp. 111–127, 2022.
Al Shamsi, J. H., Al-Emran, M., and Shaalan, K., “Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants,” Education and Information Technologies, vol. 27, pp. 8071–8091, 2022.
Gupta, S., and Tomar, R., “What drives the user’s continuous usage intention of OTT video platforms? Identifying the role of cognitive absorption and perceived usefulness with the impact of OTT content on it,” International Journal of Professional Business Review, vol. 8, pp. 33–45, 2023.
Abdul Rahim, N. F., Abbasi, G. A., Iranmanesh, M., Christopher, N., and Amran, A., “Determinants of continuous intention to use e-government services: An extension of technology continuance theory,” Journal of Systems and Information Technology, vol. 25, pp. 245–267, 2023.
Kadam, P., and Bhalerao, S., “Sample size calculation,” International Journal of Ayurveda Research, vol. 1, no. 1, pp. 55–57, 2010.
Essa, S.-G., Celik, T., and Human-Hendricks, N.-E., “Personalized adaptive learning technologies based on machine learning techniques to identify learning styles: A systematic literature review,” Journal Title, Year. (Lengkapi jika tersedia)
Hwang, G.-J., and Chang, C.-Y., “A review of opportunities and challenges of chatbots in education,” Interactive Learning Environments, vol. 31, no. 7, pp. 4099–4112, 2023.
Järvelä, S., Nguyen, A., and Hadwin, A., “Human and artificial intelligence collaboration for socially shared regulation in learning,” British Journal of Educational Technology, vol. 54, no. 5, pp. 1057–1076, 2023.
Kamalov, F., Calonge, D.-S., and Gurrib, I., “New era of artificial intelligence in education: Towards a sustainable multifaceted revolution,” Sustainability, vol. 15, no. 16, pp. 124–151, 2023.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 LITERACY : International Scientific Journals of Social, Education, Humanities
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
