Titlebook: Artificial Intelligence in Education; 21st International C Ig Ibert Bittencourt,Mutlu Cukurova,Eva Millán Conference proceedings 2020 Sprin

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Predicting Learners Need for Recommendation Using Dynamic Graph-Based Knowledge Tracingdual knowledge level, we propose a new model that can predict learners needs for recommendation using dynamic graph-based knowledge tracing. By applying the Gated Recurrent Unit (GRU) and the Attention model, this approach designs a dynamic graph over different time steps. Through learning feature i

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Identification of Students’ Need Deficiency Through a Dialogue System identification of students’ need deficiency is crucial to moral education and the students themselves. Previous psychology research focusing on distinct factors only provides scattered guidelines to identify such need deficiencies and meanwhile few teachers and parents have the related expertise, w

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EdNet: A Large-Scale Hierarchical Dataset in Educationata-driven approaches for knowledge tracing and learning path recommendation. Unfortunately, collecting student interaction data is challenging and costly. As a result, there is no public large-scale benchmark dataset reflecting the wide variety of student behaviors observed in modern IESs. Although

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Mastery Learning Heuristics and Their Hidden Modelsess mastery, some technologies utilize data-driven models while others use simple heuristics. Prior work has suggested that heuristics may often perform comparably to model-based algorithms. But is there any reason we should expect these heuristics to be reasonable? In this paper, we show that two p

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What Happens When Gamification Ends? promote engagement and participation in a wide variety of areas including education. For this reason, researchers are increasingly interested in the study of gamification. There are many papers related to the impact that this methodology has on the student’s motivation, engagement or satisfaction.