Use dynamic user models to recognize non-optimal learning behaviors and redirect students toward more effective behaviors¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends embedding dynamic user models that monitor students' interaction patterns in real time so the system can respond when learning goes off track. As stated, "Dynamic user models have the potential to recognize non-optimal learning behaviors and provide feedback or navigate students toward more effective learning behaviors within the practice environment." This supports adapting content presentation and feedback to each student's current learning trajectory.

Design Implications¶

Context¶

Requirements¶

• A dynamic user model fed by real-time analyses of logged student behaviors

Constraints¶

• Proposed for game-based practice environments with substantial student agency; implementation and testing are future work

Target Learners¶

• high school students in game-based ITS practice environments

Target Learning Goals¶

• self-explanation strategy practice
• sustaining optimal learning trajectories

Affordances¶

• Dynamical Systems Theory Its Behavior

Related Strategies¶

• Move beyond static skill-targeted rewriting toward interaction-aware adaptive error explanations
• Targeted interventions and adaptive feedback to move learners from Observation toward full-cycle Exploration
• Design AI tutors for complementarity across role paradigms and move beyond static prompting toward dynamic learner modeling
• Use strategy-based evidence models to trigger adaptive scaffolding toward more productive problem-solving strategies

Examples¶

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Key Sources¶

• Erica L. Snow. (2015). Dynamic User Modeling within a Game-Based ITS. Proceedings of the 8th International Conference on Educational Data Mining. https://educationaldatamining.org/EDM2015