Academic integrity and artificial intelligence in initial teacher education: a documentary audit of teaching guides in Spanish universities
Maria Vallespir Adillón, Ruben Comas Forgas, Mercè Morey López, Eva Espiñeira BellónPurpose
Universities are increasingly adopting institutional policies on academic integrity (AcI) and artificial intelligence (AI), but it remains unclear whether these expectations are translated coherently into the course-level documents that govern students’ learning and assessment. This article therefore examines how AcI and AI, including generative AI (GenAI), are articulated in official teaching guides for Spain’s Master’s Degree in Teacher Training, and whether guidance is embedded coherently across course design.
Design/methodology/approach
A documentary content analysis was conducted on 254 publicly available guides from 68 universities. Explicit AcI and AI references were coded across objectives, competencies, learning outcomes, activities and assessment. Two formative diagnostic indices measured breadth of coverage across these five sections. Mann–Whitney tests compared university and subject types; 25% of the corpus was independently double-coded.
Findings
AcI was mentioned in 53.5% of guides but was concentrated in assessment and competencies; 46.5% contained no valid reference. Explicit AI guidance remained marginal (6.3%) and primarily assessment-centred. Private universities showed slightly broader AcI coverage, public universities slightly broader AI coverage and Final Master’s Project guides substantially broader AcI coverage.
Research limitations/implications
The indices measure documentary breadth, not the quality, depth or implementation of guidance, and guides are nested within universities.
Practical implications
Programme leaders should integrate task-specific integrity and AI expectations across outcomes, activities, assessment, disclosure and formative support, with attention to future teachers’ professional AI literacy.
Originality/value
The study provides a large-scale, programme-specific audit and a transparent method for benchmarking cross-sectional curricular integration without treating document coverage as a quality score.