Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback.…

Based on hundreds of thousands of hours of data about how students learn in massive open online courses, educational machine learning promises to help students who are learning to code. However, in most classrooms, students and assignments do not have enough historical data for feeding these data hungry algorithms. Previous work on predicting…

Novice programmers, who have yet to form effective mental models of the domain, often experience high cognitive load, low confidence, and high anxiety, negatively affecting learning and retention rates. These cognitive and affective limitations pose an instructional challenge. This study aimed to investigate the effectiveness of a whole-task…

Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…

Serious games are considered an effective method to engage students in programming education and have been increasingly used in classrooms. An important part of the learning process with serious games involves the presentation of the new concepts and the provided support to encounter student difficulties. Although the most common approach is the…

The integration of computational modelling in science classrooms provides a unique opportunity to promote key 21st century skills including computational thinking (CT) and collaboration. The open-ended, problem-solving nature of the task requires groups to grapple with the combination of two domains (science and computing) as they collaboratively…

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…

It is becoming increasingly necessary for every child to have experience with 21st century Computational Thinking (CT) skills including learning to program. Considerable efforts have been made within the last two decades including the development and widespread use of novice-friendly block-based programming environments such as Scratch and Snap!…

Collaborative learning is an activity in which two or more students learn something together. Many studies have found that collaborative learning improve students' memory retention and motivation to learn. Peer Instruction (PI) is one of the most successful evidence-based collaborative learning methods. This article investigates issues of student…

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…

Conventional testing systems usually give students a score as their test result, but do not show them how to improve their learning performance. Researchers have indicated that students would benefit more if individual learning guidance could be provided. However, most of the existing learning diagnosis models ignore the fact that one concept…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

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…

The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…