Beyond unstructured use: scaffolded integration of generative AI in assessment for learning

This study examined how scaffolded integration of generative artificial intelligence (GenAI) within an assessment task influenced students’ experience, evaluative engagement, learning, confidence, and competence. A cross-sectional quantitative survey was completed by 164 first-year undergraduate students in a fully online health communication course. The assessment required students to generate, critically evaluate, and revise GenAI-assisted outputs, and reflect on their use. The questionnaire comprised Likert-scale and multiple-response items assessing students’ experiences, learning, confidence, competence, challenges, and perceived skill development. Composite scales were analysed descriptively and compared against neutral midpoints using non-parametric tests. Students reported positive technical experiences (64%) and learning benefits, particularly in critique writing (67%), critical thinking (83%), and responsible GenAI use (82%). Evaluative skills, including critical appraisal (71%) and source verification (69%), were frequently reported. Perceptions of reliability were cautious, and confidence and competence did not differ from neutral. Composite analyses indicated positive experience and learning without corresponding increases in confidence. Scaffolded integration of GenAI within assessment can support assessment for learning by promoting evaluative engagement and critical AI literacy without encouraging uncritical reliance. These findings position assessment design as a central mechanism for guiding responsible and effective GenAI use in higher education.