Keywords
Vocational education
Professional-course learning
Cognitive engagement
Professional fit
Teacher perspectives
Institutional support
Abstract
GenAI is now part of ordinary study for many students, but frequent use does not automatically mean deeper learning. This mixed-methods study examined professional-course use of GenAI at a private vocational college in Jiangxi Province, China. The evidence came from 431 student questionnaires and written responses from 18 teachers. After response-quality screening, 184 cases were retained for the primary quantitative analyses; 203 moderately screened cases and the full 431 responses were used for sensitivity checks. Meaningful learning engagement (MLE) was measured with two items and is therefore treated as a brief indicator of cognitive engagement rather than a validated multidimensional scale.
Students reported using GenAI most often for knowledge clarification (82.6%) and coursework or exercises (74.5%); practical-training use was lower (20.7%). Perceived professional value (PPV) was associated with MLE (β = .550). When PPV and MLE were entered together, both remained associated with post-adoption learning experience (PAE; β = .339 and β = .364, respectively). The standardized indirect association from PPV to PAE through MLE was .200, with a 95% bootstrap CI of [.109, .307]. These cross-sectional results describe associations rather than causal effects.
Teacher accounts added important context. Teachers valued GenAI for quick explanations but also described answer-oriented use, inaccurate professional content, weak links with practical training, and uncertainty about institutional guidance. They wanted more discipline-specific examples, clearer expectations, and assessment that made student reasoning visible. Across both strands, three tensions stood out: efficiency versus engagement, general usefulness versus professional fit, and rapid student adoption versus slower institutional response. Because the evidence came from one college, the findings should be interpreted as context-specific.
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