Embed automated question categorisation in learning management systems and develop ethical guidelines for AI in formative assessment¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends that "Learning management systems could benefit from embedding automated question categorisation functions to identify students' learning needs more efficiently" and that "Educational institutions should consider developing ethical guidelines for the use of AI in formative assessment processes." Together these position automated question analysis as an LMS capability for identifying learning needs, governed by institutional ethical safeguards.

Design Implications¶

Context¶

Requirements¶

• LMS integration of question categorisation functions and institution-level ethical guidelines governing AI use in formative assessment.

Constraints¶

• The article ties AI use in formative assessment to the need for human oversight and ethical implementation, listed as future research avenues.

Target Learners¶

• higher education students

Target Learning Goals¶

• identifying students' learning needs
• ethical AI-supported formative assessment

Related Strategies¶

• Integrate AI-based question analysis tools to provide tailored feedback based on inquiry depth
• Incorporate AI-driven scaffolding strategies to support students' higher-order thinking skills
• Foster communities of practice for AI governance instead of rigid top-down policies
• Reorient AI assessment toward formative, holistic portraits of learner competencies rather than automated grading

Examples¶

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Key Sources¶

• Lee, H., Atif, A., & Kang, K. (2026). Analysing AI utilisation in education through learner question types: A constructivist approach. Australasian Journal of Educational Technology, 42(1), 79–96. https://doi.org/10.14742/ajet.10657