Author
Listed:
- Kai-Chao Yao
(Department of Electrical and Mechanical Technology, National Changhua University of Education, Changhua City 50007, Taiwan)
- Jung-Wei Liang
(Department of Electrical and Mechanical Technology, National Changhua University of Education, Changhua City 50007, Taiwan)
- Sumei Chiang
(Department of Electrical and Mechanical Technology, National Changhua University of Education, Changhua City 50007, Taiwan)
- Shao-Hsun Chang
(Department of Electrical and Mechanical Technology, National Changhua University of Education, Changhua City 50007, Taiwan)
Abstract
This study examines emotional dependency on generative artificial intelligence among vocational high school (VHS) students. Guided by Taiwan’s 108 Curriculum Guidelines, an interactive “Health and Nursing” course on AI reliance was implemented. The sample included 1000 students from five VHSs in central Taiwan (January–February 2026). Data were collected through questionnaires and classroom feedback to assess AI interaction frequency, emotional projection, and perceived effects on relationships and psychological needs. Research data were analyzed using SPSS 22.0 and SmartPLS 4. Findings show that some students displayed moderate to high emotional attachment to AI, particularly for support and stress relief, with blurred ethical boundaries. After the intervention, students reported greater awareness of risks and increased self-reflection. This study concludes that integrating AI literacy with emotional education into curricula is crucial for responsible technology use and healthy relational development. Overall, emotional reliance on AI among VHS students appears statistically significant but bounded, reflecting a balanced pattern of engagement that supports sustainable psychological well-being.
Suggested Citation
Kai-Chao Yao & Jung-Wei Liang & Sumei Chiang & Shao-Hsun Chang, 2026.
"Emotional Reliance on Generative AI Among Vocational High School Students: An AEDTAM-Based Analysis,"
Sustainability, MDPI, vol. 18(10), pages 1-21, May.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:10:p:5148-:d:1947181
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