Exploring AI-related attitudes, awareness, skills and usage and their impact on students’ learning experience: a necessary condition analysis

Abstract

Purpose In light of the widespread adoption and use of artificial intelligence (AI) tools, this study sought to address two timely objectives: ascertain possible AI-related dimensions and their impact on student’s learning experience, and gain insights as to the scale of AI adoption among grade students in a STEM program. This study aims to focus on the international student given that non-native English-speaking students may rely heavily on AI for assistance with translation, grammar and writing in their academic studies. Design/methodology/approach This study utilized necessary condition analysis to establish necessity conditions among several AI-related dimensions – awareness and understanding (AU); perceptions and attitudes (PA); usage and experience (EU) and education, skills and training (ST) – as predictors of students’ positive learning experience. The hypotheses were tested in a sample of 157 international Indian graduate students at a southeastern university’s STEM programs in the USA. Findings The results revealed a strong link between three AI-related categories and students’ positive learning experience. Specifically, the analysis of the data showed that ST, PA and EU emerged as statistically significant conditions necessary for a positive learning experience, whereas AU emerged as a weak predictor thus unnecessary for a positive learning experience. Overall, students’ utilization of this innovative technology has been widespread and growing. Practical implications The inherent practical implication suggests an opportunity for college administrators, faculty and organizational leaders to zoom in on critical AI dimensions and on their degree of necessity for the improvement and enhancement of learning experiences. In the sample of STEM program graduate students, capitalizing on students’ own AI experience, usage, skills and training and on their own perceptions and attitudes toward AI, may not be sufficient per se and hence must be complemented by program directors for further nurturing familiarity with AI technologies, tools and applications. These must be considered as priorities for “in-house” training and coaching. Indeed, mastery of AI technology by students, regardless of their academic field and constitutes a priority that educators and industry cannot ignore. Social implications The results indicate that AI skills and training, experience and usage and perceptions and attitudes can be considered as necessary for a positive student learning experience. The awareness and understanding of AI itself appear to be an unnecessary condition for a positive learning experience but may play a small role nonetheless. Originality/value These findings enrich the relevant extant literature and appear to align well with the theoretical framework. Results highlight the key role that self-experimentation and self-learning play in one’s proactive posture, actions and initiatives. Equally important, the findings emphasize the unique and urgent role college administrators can play in encouraging rather than suppressing students’ adoption and use of AI tools. This study further discusses these links along with implications for faculty and college administrators. Study limitations and directions for future research are also proposed.

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