AI Effects on Student Well-being
Drozd, Dominika (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025101826162
https://urn.fi/URN:NBN:fi:amk-2025101826162
Tiivistelmä
This thesis studies Artificial Intelligence affects on student well-being, confidence, and career outlooks across fields in higher education. The working life partner of the thesis was Metropolia UAS and the theoretical framework builds on Self Determination Theory (SDT) and an adaptation of “Feelings of Being” (FoB). A multidisciplinary survey was conducted on 118 Metropolia students from: Social Services, IT, Digital Design (DD), Engineering, Business; covering usage patterns, fears regarding future job prospects, whether AI affected degree programme decisions, AI usefulness, confidence in working without AI etc. FoB measures included autonomy, creativity, ownership, effectiveness, motivation, presence, engagement, and immersion. Analysis was done in R-studio (data analysis programme) using field specific percentage visualizations, statistical analysis, correlation heatmap and regression models.
Results show that AI is academically helpful and relieves stress. Effectiveness and autonomy relate positively supporting SDT´s competence autonomy connection. DD students who use GenAI tools have the greatest autonomy concerns and the lowest pride in AI assisted work. Social Services students reported strong confidence in completing tasks without AI. Career anxiety was highest amongst IT, Business and DD students. IT Masters had the highest usage, highest education field change due to AI, highest reduction of academic stress due to AI, felt least confident in AI unaided work ability, had high temptation to use AI, and highest motivation to do programming as they view AI like a coworker. Ownership varied by modality (code/ text). Lower confidence without AI was a predictor of career anxiety, and frequent AI use predicted low unaided confidence. Immersion was related to higher career anxiety, helpfulness may cushion this.
Results point to autonomy supportive AI pedagogy, and the thesis includes recommendations for higher educational institutions based on the results; keep the competence and stress relief of AI but build unaided confidence with process graded tasks, field specific AI literacy and ethics courses.
Results show that AI is academically helpful and relieves stress. Effectiveness and autonomy relate positively supporting SDT´s competence autonomy connection. DD students who use GenAI tools have the greatest autonomy concerns and the lowest pride in AI assisted work. Social Services students reported strong confidence in completing tasks without AI. Career anxiety was highest amongst IT, Business and DD students. IT Masters had the highest usage, highest education field change due to AI, highest reduction of academic stress due to AI, felt least confident in AI unaided work ability, had high temptation to use AI, and highest motivation to do programming as they view AI like a coworker. Ownership varied by modality (code/ text). Lower confidence without AI was a predictor of career anxiety, and frequent AI use predicted low unaided confidence. Immersion was related to higher career anxiety, helpfulness may cushion this.
Results point to autonomy supportive AI pedagogy, and the thesis includes recommendations for higher educational institutions based on the results; keep the competence and stress relief of AI but build unaided confidence with process graded tasks, field specific AI literacy and ethics courses.