We propose an adaptation of the Glicko-2 rating system in a K-12 math learning software setting, where variable time intervals between solution attempts and the stratification of student-item pairings by grade levels necessitate modification of the original model. The discrete-time stochastic process underlying the original system has been…

We describe three iterations of a Massive Open Online Course (MOOC) developed from online preparation materials for a reformed introductory physics classroom at the Massachusetts Institute of Technology, in which the teaching staff interact with small groups of students doing problems using an expert problem-solving pedagogy. The MOOC contains an…

As part of the Race to the Top initiative, the United States Department of Education made nearly 1 billion dollars available in State Educational Technology grants with the goal of ramping up school technology. One result of this effort is that states, districts, and schools across the country are using computerized assessments to measure their…

One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…

This research applies multimedia technology to design a dynamic item generation method that can adaptively adjust the difficulty level of items according to the level of the testee. The method is based on interactive testing software developed by Flash Actionscript, and provides a testing solution for users by automatically distributing items of…

This study investigates the effect of fitting a unidimensional IRT model to multidimensional data in content-balanced computerized adaptive testing (CAT). Unconstrained CAT with the maximum information item selection method is chosen as the baseline, and the performances of three content balancing procedures, the constrained CAT (CCAT), the…

There has been an increased interest in developing computer-adaptive testing (CAT) and multistage assessments for K-12 accountability assessments. The move to adaptive testing has been met with some resistance by those in the field of special education who express concern about routing of students with divergent profiles (e.g., some students with…

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…

The IRT (Item Response Theory) has been studied and applied in computer-based test for decades. However, almost of all these existing studies evaluated focus merely on test questions with text-based (or static text/graphic) type of presentation form illustrated exclusively. In this paper, we present our study on test questions using both…

Computer adaptive testing is the study of scoring tests and questions based on assumptions concerning the mathematical relationship between examinees' ability and the examinees' responses. Adaptive student tests, which are based on item response theory (IRT), have many advantages over conventional tests. We use the least square method, a…

The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…