Exploration of the Robustness and Generalizability of the Additive Factors Model

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EFFENBERGER Tomáš PELÁNEK Radek ČECHÁK Jaroslav

Rok publikování 2020
Druh Článek ve sborníku
Konference Proceedings of the 10th International Conference on Learning Analytics and Knowledge
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www https://doi.org/10.1145/3375462.3375491
Doi http://dx.doi.org/10.1145/3375462.3375491
Klíčová slova student modeling; learning curves; knowledge components; introductory programming
Popis 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 also report on an application of the model to data from a learning system for introductory programming; these experiments illustrate possibly misleading interpretation of model results due to differences in item difficulty. Overall, our results show that greater care has to be taken in the application of the model and in the interpretation of results obtained with the model.
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