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Proceedings of the 2022 International Conference on Research in Management & Technovation

Annals of Computer Science and Information Systems, Volume 34

Factors influence students' attitudes toward AI-based innovative solutions

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DOI: http://dx.doi.org/10.15439/2022M9228

Citation: Proceedings of the 2022 International Conference on Research in Management & Technovation, Viet Ha Hoang, Vijender Kumar Solanki, Nguyen Thi Hong Nga, Shivani Agarwal (eds). ACSIS, Vol. 34, pages 21–26 ()

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Abstract. As technology improves, it appears that academic machine instructors will be used in many jobs in future of education. Despite the fact that the existing research does not clearly define the idea of machine lecturers. Nonetheless, given the current era of education, it appears to be critical to begin thinking about this concept. Machine units are technologies with a specific level of agency, suggesting that they will play a specific function in communication. Lecturers are frequently thought of as those who encourage and help others to improve their emotional and learning behavior via data collecting, advancement, and moral shaping. The machine teacher model may be broadly characterized as a technological design that helps and interacts with a person in boosting affective and learning behavior through numerous techniques, as supported by these two notions. In this paper, different factors will be examined to determine whether these will have certain effects on college students attiudes toward AI teaching assistants.

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