Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and…

Prediction of student performance in introductory programming courses can assist struggling students and improve their persistence. On the other hand, it is important for the prediction to be transparent for the instructor and students to effectively utilize the results of this prediction. Explainable Machine Learning models can effectively help…

The challenge of learning programming in a MOOC is twofold: acquiring programming skills and learning online, independently. Automated testing and feedback systems, often offered in programming courses, may scaffold MOOC learners by providing immediate feedback and unlimited re-submissions of code assignments. However, research still lacks…

Over the years, researchers have studied novice programming behaviors when doing assignments and projects to identify struggling students. Much of these efforts focused on using student programming and interaction features to predict student success at a course level. While these methods are effective at early detection of struggling students in…

In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

This work-in-progress research paper examines the relationship between two aspects of students' engagement and academic performance. With the boom of technology-mediated learning environments, many educational applications are integrated into STEM courses. However, the effectiveness of these applications in the learning environments is contingent…

The impact of a novice programmer's first language on their subsequent achievement in further computing education has been the subject of much study in the field of computer science education. Our research is a retrospective study of more than 10,000 undergraduate students enrolled in CS1 (introduction to computer programming) from 118 US college…

This paper describes the first stages on the development of a design method of digital trainings using the collaborative authoring tool "ALO". Based on the theory of instrumental conflict (Marquet, 2005), this method highlights the necessity of the design digital trainings under the optimal harmonization for users/learners in didactic,…

The aim of this study is to assess the impact upon academic success of the use of a reference block-based visual programming tool, namely the MIT App Inventor for Android, as an educational instrument for teaching object-oriented GUI-application development (CS2) concepts to students; who have previously completed a fundamental programming course…

Passive learning environments to teach programming concepts, especially in large lecture classes, hinder students' motivation, performance and may adversely affect their achievement goals. The study presents the use of two instructional strategies, teamwork, and reflective thinking, using educational technologies introduced in a class of 120…

We propose a novel tensor factorization approach, Feedback-Driven Tensor Factorization (FDTF), for modeling student learning process and predicting student performance. This approach decomposes a tensor that is built upon students' attempt sequence, while considering the quizzes students select to work with as its feedback. FDTF does not require…

In a course of the degree of computer science, the programming project has changed from individual to teamed work, tentatively in couples (pair programming). Students have full freedom to team up with minimum intervention from teachers. The analysis of the working groups made indicates that students do not tend to associate with students with a…

The Education Program Provider Chair's objective was to create a student legacy artifact archival retrieval system. The goal was to have the database system operational by Spring Semester, 2019. The purpose of the new system was to house and index student and pre-service candidate product across performance levels reflective of the program's key…

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…

Collaborative problem solving in computer-supported environments is of critical importance to the modern workforce. Coworkers or collaborators must be able to co-create and navigate a shared problem space using discourse and non-verbal cues. Analyzing this discourse can give insights into how consensus is reached and can estimate the depth of…