User attitudes toward Artificial Intelligence in educational learning


Amit Sarkar, University of Regina

Artificial intelligence (AI) is swiftly becoming a cornerstone of modern education, especially in learning practices. AI-driven personalized learning platforms can accelerate learning by 25-60% according to research undertaken at Stanford University. This advancement is especially helpful for adult learners who must manage schooling with other responsibilities (Domingos 2015). The World Economic Forum report provides AI-driven educational tools that may boost adult students learning efficiency by 40% (the future of jobs report 2020). As noted by the Educause Centre for Analysis and Research, universities that use AI applications have seen course completion rates increase by 10-20%. This demonstrates AIs ability to significantly improve student achievement and participation in higher education (Brown et al. 2020). AI in education is growing due to adoption and investment. Markets and Markets (2019) predicted this market will rise to $3.68 billion by 2023. Researchers found that AI systems have the potential to provide students more control over their own learning and the interaction between them and their teachers in online classes. In the classroom, AI makes teachers more attuned to their students individual requirements, which in turn encourages students to ask more questions and creates more individualized learning plans (Tung et. al 2021). Studies also found that Future AI technology could reduce instructors tasks, allowing them to focus on creative lesson planning, professional development, and personalized student coaching and mentoring. All these exercises improve pupils learning performance for future abilities and problems. The use of artificial intelligence technology, such as Chat GPT, can facilitate the translation of instructional content and the development of dynamic, personalized learning spaces. Another context where the AI proves quite significant is in the field of personalized tutoring. Because every student learns in their own way, the AI systems might modify the lesson plan accordingly (Grassini 2023). From theoretical perspective, the theory of planned behavior students provides that intentions to employ artificial intelligence in learning are influenced by their attitudes toward technology, subjective norms, and perceived behavioral control. Students are more inclined to accept AI if they believe it improves their learning experience, if their classmates or educators support it, and if they are confident in their abilities to use it effectively (Ajzen, 1991). Students accept AI based on perceived utility and simplicity of usage, according to the Technology Acceptance Model (TAM). Students are more inclined to accept AI tools if they find them beneficial and easy to use (Davis, 1989). Self-efficacy as defined by Bandura (1977) plays a significant role in students attitudes towards technology for success in life. Students with more technological self-efficacy view AI in learning more positively. Delves in the feminist theory, in the realm of education, artificial intelligence has the potential to play a role in defying established gender norms. This is especially true when it comes to encouraging more young women and girls to participate in STEM (Science, Technology, Engineering, and Mathematics) topics, promoting gender equality in these professions (Chen et al., 2021). From the conflict theory perspective, AI facilitates bridging educational gaps, and artificial intelligence has the ability to decrease educational inequalities despite the fact that it is frequently associated with increasing inequality. As an example, artificial intelligence has the potential to give disadvantaged or remote places access to high-quality educational materials, so minimizing the existing discrepancies in academic quality. AI also contributes to preparing the future workforce as it enables students to concentrate on developing intellectual abilities by automating routine tasks. This prepares students for a workforce increasingly characterized by automation and AI technology (Turner 2022). Using responses from a questionnaire survey of over 500 students from a variety of academic backgrounds in Saskatchewans capital city, this paper explores user attitudes towards artificial intelligence in educational learning.  The implications for academic integrity policy will also be discussed.

This paper will be presented at the following session: