Redesign assessment toward progressive, authentic, and reflective methods rather than intensive paperwork¶

Strategy · All strategies
Evidence · no claims cited

Description¶

To preserve academic integrity and assessment fairness in the age of GenAI, the article recommends moving away from traditional paper-based coursework. It states that "assessment methods need to be redesigned, focusing on progressive learning processes, authentic assessments, reflective debriefings, and real-life project work rather than intensive paperwork." The conclusion repeats that educators may need to redesign assessment techniques from traditional paper-based work to more progressive, reflective, and authentic methods, and previous studies are cited as suggesting promoting creativity, critical thinking, and higher-order thinking assessment.

Design Implications¶

Context¶

Requirements¶

• Assessment designs that focus on learning processes and authentic performance rather than submittable paperwork

Constraints¶

• Recommended as an author interpretation in the discussion, not a tested intervention in this study

Target Learners¶

• undergraduate students in higher education

Target Learning Goals¶

• authentic demonstration of learning
• critical thinking
• creativity

Related Strategies¶

• Redesign assessment toward supervised, oral, process-based and authentic formats to verify students' own reasoning under GenAI
• Adapt non-invigilated written assessments and their marking criteria in response to Gen-AI susceptibility
• Use GenAI-driven disruption as an occasion to redesign assessment practices rather than preserve them
• Address generative AI in higher education through assessment redesign and proportional reflective practices rather than surveillance or punitive controls
• Shift from punitive detection to proactive educative approaches, co-created detailed guidelines, and assessment designs GenAI cannot do well
• Institutional recommendations: shift from detection to process-oriented assessment, transparent AI-use protocols, and revised integrity policies
• Integrate GenAI into HSS education through scaffolded, practice-oriented training sequences and discipline-responsive, process-focused assessment
• Redesign assessments and curricula so AI availability supports rather than impedes expertise growth

Examples¶

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Key Sources¶

• Feyisa Mulisa and Tesfa Mezgebu. (2026). Tools facilitate cheating, or partner supports learning? GenAI and academic integrity issues from students’ perspectives. International Journal for Educational Integrity. https://doi.org/10.1007/s40979-026-00231-z