What Does Time Tell? Tracing the Forgetting Curve Using Deep Knowledge Tracing
Recurrent Neural Network (RNN) based Deep Knowledge Tracing (DKT) can extract a complex representation of student knowledge just using the historical time series of correct incorrect responses given as input and can predict the student's performance on the next problem. funtoot is a personalized and adaptive learning system used by students to practice problems in school and at home. Our analysis of students' interaction with funtoot showed a time gap as high as 1 h, 1 day and also 1 week between two problems attempted by a student in a task. In this work, along with the time series of previous correct incorrect responses, we also encode the time gap as a feature to investigate its effect on predictions. We call this variant of DKT as DKT t. We test these models on our dataset and two major publicly available datasets from Assistments and Carnegie Learning's Cognitive Tutor and analyze the predicted student knowledge by both the models and report our findings. We also show that DKT t can help us trace the forgetting curve given various response sequences and their knowledge states.
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