In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…

Learning basic programming concepts in computer science-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed solutions to the problem can be found in the literature, such as the development of new programming languages and environments, the…

Providing timely feedback is crucial in promoting academic achievement and student success. However, for multifarious reasons (e.g., limited teaching resources), feedback often arrives too late for learners to act on the feedback and improve learning. Thus, automated feedback systems have emerged to tackle educational tasks in various domains,…

Expressing thoughts and feelings efficiently is fundamental in daily, academic, and professional life. Accordingly, self-efficacy beliefs play pivotal roles in shaping learners' speaking performance through various dimensions. Higher education institutions assume responsibility for boosting students' speaking self-efficacy, thereby contributing to…

This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…

The assessment of program functionality can generally be accomplished with straight-forward unit tests. However, assessing the design quality of a program is a much more difficult and nuanced problem. Design quality is an important consideration since it affects the readability and maintainability of programs. Assessing design quality and giving…

Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…

How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…

In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…

Educators are increasingly confronted with technology-driven learning scenarios. Even before the push from the current pandemic, digital learning apps became an integrated didactic tool. Advanced computing can thereby support the digital content creation for educational courses offered on mobile platforms. Computed media content such as natural…

Similar content has tremendous utility in classroom and online learning environments. For example, similar content can be used to combat cheating, track students' learning over time, and model students' latent knowledge. These different use cases for similar content all rely on different notions of similarity, which make it difficult to determine…

Influenced by COVID-19, online learning has become one of the most important forms of education in the world. In the era of intelligent education, knowledge tracing (KT) can provide excellent technical support for individualized teaching. For online learning, we come up with a new knowledge tracing method that integrates mathematical exercise…

This study aims to understand the extent to which English as a foreign language learners use technology for their autonomous language learning beyond the classroom. With a cross-sectional survey design approach, the study focuses on learner characteristics. It first investigates the existing language learner profiles of 512 English major…

In this paper we present a novel, data-driven algorithm for generating feedback for students on open-ended programming problems. The feedback goes beyond next-step hints, annotating a student's whole program with suggested edits, including code that should be moved or reordered. We also build on existing work to design a methodology for evaluating…

Over the last couple of decades, there have been a large variety of approaches towards modeling student knowledge within intelligent tutoring systems. With the booming development of deep learning and large-scale artificial neural networks, there have been empirical successes in a number of machine learning and data mining applications, including…