Exploration of the robustness and generalizability of the additive factors model

Tomás Effenberger
Tomás Effenberger
Jaroslav Cechák
Jaroslav Cechák

LAK '20: 10th International Conference on Learning Analytics and Knowledge Frankfurt Germany March, 2020, pp. 472-479, 2020.

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Abstract:

Additive Factors Model is a widely used student model, which is primarily used for refining knowledge component models (Q-matrices). We explore the robustness and generalizability of the model. We explicitly formulate simplifying assumptions that the model makes and we discuss methods for visualizing learning curves based on the model. We...More

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