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Modeling and predicting student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for student modeling is Bayesian Knowledge Tracing (BKT). BKT models, however, lack the ability to describe the hierarchy and relationship ...
Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among the ...
8th International Conference on Educational Data Mining, EDM 20152015
How does AI&EdAIED today compare to 25 years ago? This paper addresses this evolution by identifying six trends. The trends are ongoing and will influence learning technologies going forward. First, the physicality of interactions and the physical space of ...
While moving from diary survey to location-aware technologies, recent data collection techniques provide new insights about location choices. Only few dynamic models of location choice exist in the literature, and none of them to our knowledge correct for ...
Computational education offers an important add-on to conventional teaching. To provide optimal learning conditions, accurate representation of students' current skills and adaptation to newly acquired knowledge are essential. To obtain sufficient represen ...
Panel data and habits are often observed in travel behavior research, in route choice and car ownership. While moving from diary survey to location-aware technologies, recent data collection techniques provide panel data about location choice. Only few dyn ...
This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalc ...
This paper introduces a computer-based training program for enhancing numerical cognition aimed at children with developmental dyscalculia. Through modelling cognitive processes and controlling the level of their stimulation, the system optimizes the learn ...
With the general technological advances of the recent years, current learning environments amass an abundance of data. Albeit such data offer the chance of better understand the learning process, stakeholders – learners, teachers and institutions – often n ...
The idea of iterative process optimization based on collected output measurements, or "real-time optimization" (RTO), has gained much prominence in recent decades, with many RTO algorithms being proposed, researched, and developed. While the essential goal ...