Explore hybrid assessment models combining AI conversational agent-based and face-to-face formats, with long-term study of effects on performance and well-being¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends that future work move beyond comparing purely AI-mediated and purely face-to-face assessment by developing and studying hybrid formats, and by examining longer-term consequences. It states: "Future research could explore the value of hybrid models that combine AI conversational agent-based and face-to-face assessment formats, and examine the long-term effects of AI-led assessments on student performance and well-being." This follows the authors' caution that benefits of AI-mediated assessment for attainment remain unestablished.

Design Implications¶

Context¶

Requirements¶

• Further investigation to ascertain whether AI-mediated assessment is ultimately beneficial for learning and attainment before large-scale adoption

Constraints¶

• The article notes AI-mediated interaction may discourage students from developing coping strategies for the discomfort authentic face-to-face assessments create

Target Learners¶

• students undertaking performance-based assessments across educational levels

Target Learning Goals¶

• reducing excessive assessment anxiety while maintaining valid assessment of competence and student well-being

Affordances¶

• Logic Model Technology Reduces Pba Anxiety

Related Strategies¶

• Design AI decision-support systems that are transparent, context-sensitive, and hybrid-intelligence oriented
• Use a mixed-methods assessment sequence: diagnostic inventory, structured verification tasks, and discipline-specific critique or workflow-design assignments
• Design AI-powered support for international students that integrates with university systems and helps sustain community for long-term use

Examples¶

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Key Sources¶

• Habeeb Yusuf, Arthur Money, Damon Daylamani-Zad. (2026). Exploring student anxiety and experience in performance-based assessments using AIvaluate: an LLM-augmented emotionally intelligent pedagogical AI conversational agent. Educational technology research and development. https://doi.org/10.1007/s11423-026-10634-x