Rethinking Learning Objectives in Media and Communication Education: A Constructive Alignment Framework for Generative Artificial Intelligence

Generative artificial intelligence (AI) is changing how creative work is produced and what educators can infer from students’ finished artefacts. This study examines how students and educators in Vietnamese media and communication programmes understand the changing purposes of creative learning, distinguish AI assistance from substitution and sustain student authorship. Semi-structured interviews were conducted with 26 students and 19 educators and analysed thematically. The findings show that creative learning is shifting from technical execution alone towards selecting, evaluating, revising and justifying AI-assisted decisions. Students located the boundary of acceptable AI use through ownership and cultural meaning, whereas educators emphasised visible evidence of critical engagement. Documentation and structured questioning helped make students’ decision-making visible, although fluent AI outputs could conceal reduced understanding. The study proposes the Reflective AI Constructive Alignment Framework and introduces the delegation threshold as its primary conceptual contribution. The designed threshold specifies what educators permit AI to support, whereas the enacted threshold captures what students actually delegate. The framework reframes AI integration as an alignment problem: AI should support rather than replace the judgement represented by intended learning outcomes.