Rulebook vs. Reality : The Influence of University AI Policies on Student AI Aversion, Attitudes, and Expected Learning Outcomes
Fidder, Daan (2024-08-21)
Rulebook vs. Reality : The Influence of University AI Policies on Student AI Aversion, Attitudes, and Expected Learning Outcomes
Fidder, Daan
(21.08.2024)
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2024083067480
https://urn.fi/URN:NBN:fi-fe2024083067480
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This study investigates students’ general attitudes toward AI and the impact of university
AI policies on their attitudes, algorithm aversion, and expected learning outcomes.
Utilizing a mixed-methods approach, we conducted document analyses of AI policies from
Dutch universities and a scenario-based survey experiment with students. The results of our
exploratory analysis revealed that students are highly familiar with AI tools and generally
hold positive views regarding the future of AI, although concerns about potential biases
persist. The findings from our empirical research indicate that while policies do not directly
influence students’ trust in AI, restrictive policies prohibiting AI usage lead to a slight change
in attitudes. Notably, policies significantly influence the use of AI, with students utilizing AI
most frequently in the absence of specific policies. These findings underscore the importance
of well-crafted AI policies that promote transparency, fairness, and ethical use to maximize
educational benefits. Future research should explore diverse factors and conduct longitudinal
studies to further elucidate the long-term effects of AI policy integration. This study
contributes to the ongoing discourse on AI in education by highlighting the critical role of
policy in shaping students’ engagement and learning outcomes with AI technologies.
AI policies on their attitudes, algorithm aversion, and expected learning outcomes.
Utilizing a mixed-methods approach, we conducted document analyses of AI policies from
Dutch universities and a scenario-based survey experiment with students. The results of our
exploratory analysis revealed that students are highly familiar with AI tools and generally
hold positive views regarding the future of AI, although concerns about potential biases
persist. The findings from our empirical research indicate that while policies do not directly
influence students’ trust in AI, restrictive policies prohibiting AI usage lead to a slight change
in attitudes. Notably, policies significantly influence the use of AI, with students utilizing AI
most frequently in the absence of specific policies. These findings underscore the importance
of well-crafted AI policies that promote transparency, fairness, and ethical use to maximize
educational benefits. Future research should explore diverse factors and conduct longitudinal
studies to further elucidate the long-term effects of AI policy integration. This study
contributes to the ongoing discourse on AI in education by highlighting the critical role of
policy in shaping students’ engagement and learning outcomes with AI technologies.