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…

Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…

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…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

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…

This study explored the effectiveness of scaffolding in students' reflection writing process. We compared two sections of an introductory computer programming course (N=188). In Section 1, students did not receive any scaffolding while generating reflections, whereas in Section 2, students were scaffolded during the reflection writing process.…

Is there a pattern in how students solve Parsons puzzles? Is there a difference between the puzzle-solving strategies of C++ and Java students? We used Markov transition matrix to answer these questions. We analyzed the solutions of introductory programming students solving Parsons puzzles involving if-else statements and while loops in C++ and…

Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…

Researchers and educators are concerned about student success in tertiary programming courses, a situation that is even more pronounced in open and distance e-learning institutions. The aim of this study was to integrate 60 video lessons and compare passing and failing student in terms of their performance in JavaScript with three broad online…

Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need…

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…

Transitioning to university is recognised as a challenging endeavour for commencing students. For commencing Computer Science students specifically, evidence suggests a link between poor performance in introductory technical courses, such as programming, and high attrition rates. Building resilience in students, particularly at the start of their…

As programming must be learned by doing, introductory programming course learners need to solve many problems, e.g., on systems such as 'Online Judges'. However, as such courses are often compulsory for non-Computer Science (nonCS) undergraduates, this may cause difficulties to learners that do not have the typical intrinsic motivation for…

How to support students in programming learning has been a great research challenge in the last years. To address this challenge, prior works have mainly focused on proposing solutions based on syntactic analysis to provide students with personalized feedback about their grammatical programming errors and misconceptions. However, syntactic…