Address responsible design, learner experience, equity, validity, and relational assessment practice when implementing AI-agent-supported assessment¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The paper closes by identifying "ethical considerations and future research directions related to responsible design, learner experience, equity, validity, and relational assessment practice". Assessment designers adopting AI agents should treat these five areas as implementation considerations to address, alongside the low-stakes opportunities the paper describes.

Design Implications¶

Context¶

Requirements¶

• Implementation of AI-agent-supported assessment should be reviewed against responsible design, learner experience, equity, validity, and relational assessment practice.

Constraints¶

• The paper frames these as considerations and future research directions rather than as validated implementation guidance.

Target Learners¶

• students in GenAI-era courses
• assessment designers and instructors

Target Learning Goals¶

• valid assessment design
• equitable learner experience in AI-mediated assessment

Related Strategies¶

• Joyful Assessment Framework
• Higher education leaders should develop more inclusive and future-oriented GenAI policies integrating social equity, interdisciplinary experimentation, and sustainability considerations
• Foster communities of practice for AI governance instead of rigid top-down policies
• Address equity, transparency, and teacher professional judgment when deploying AI-mediated collaboration

Examples¶

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Key Sources¶

• Eliana Khoury & Xiaoyan Ma. (2026). AI Agents, Joyful Assessment, and Third Space: Rethinking Assessment in the GenAI Era. Journal of Teaching and Learning, 20(4). https://doi.org/10.22329/jtl.v20i4.11850