This paper aims to showcase the value of implementing a Bayesian framework to analyze and report results from international large-scale assessments and provide guidance to users who want to analyse ILSA data using this approach. The motivation for this paper stems from the recognition that Bayesian statistical inference is fast becoming a popular…

In the present study, we examined how the perceived attainability and relatability of moral exemplars predicted moral elevation and pleasantness among both adult and college student participants. Data collected from two experiments were analyzed with Bayesian multilevel modeling to explore which factors significantly predicted outcome variables at…

Engineering design plays an important role in education. However, due to its open nature and complexity, providing timely support to students has been challenging using the traditional assessment methods. This study takes an initial step to employ learning analytics to build performance prediction models to help struggling students. It allows…

We propose a method of generating teaching policies for use in intelligent tutoring systems (ITS) for concept learning tasks [1], e.g., teaching students the meanings of words by showing images that exemplify their meanings à la Rosetta Stone [2] and Duo Lingo [3]. The approach is grounded in control theory and capitalizes on recent work by [4],…

Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…

Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…

A long-standing challenge for knowledge tracing is how to update estimates of multiple subskills that underlie a single observable step. We characterize approaches to this problem by how they model knowledge tracing, fit its parameters, predict performance, and update subskill estimates. Previous methods allocated blame or credit among subskills…

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 dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…

In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…

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…

Courses in clinical epidemiology usually include acquainting students with a single 2X2 table. All diagnostic test characteristics are explained using this table. This pedagogic approach may be misleading. A new didactic approach is hereby proposed, using two tables, each with specific analogous notations (uppercase and lowercase) and derived…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…