Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

Intelligent tutoring systems (ITSs) teach skills using learning-by-doing principles and provide learners with individualized feedback and materials adapted to their level of understanding. Given a learner's history of past interactions with an ITS, a learner performance model estimates the current state of a learner's knowledge and predicts her…

It is unclear how children learn labels for multiple overlapping categories such as "Labrador," "dog," and "animal." Xu and Tenenbaum (2007a) suggested that learners infer correct meanings with the help of Bayesian inference. They instantiated these claims in a Bayesian model, which they tested with preschoolers and…

Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including…

A fundamental goal of educational research is identifying students' current stage of skill mastery (complete/partial/none). In recent years a number of cognitive diagnosis models have become a popular means of estimating student skill knowledge. However, these models become difficult to estimate as the number of students, items, and skills grows.…

Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better understand student learning there are two problems. First, a model's ability to predict student performance is at best weakly related to the accuracy of any one of its…

Bayes Theorem leads to three indexes of item effectiveness: 1) probability that an examinee knows the content given that the correct response was selected; 2) probability that an examinee does not know that content given that an incorrect response was selected; and 3) probability of making a correct decision about the examinee's knowledge given…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…