Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…

This research is part of the Artificial Intelligence Virtual Trainer (AI-VT) project which aims to create a system that can identify the user's skills from a text by means of machine learning. AI-VT is a case-based reasoning learning support system can generate customized exercise lists that are specially adapted to user needs. To attain this…

A key challenge in e-learning environments like Intelligent Tutoring Systems (ITSs) is to induce effective pedagogical policies efficiently. While Deep Reinforcement Learning (DRL) often suffers from "sample inefficiency" and "reward function" design difficulty, Apprenticeship Learning (AL) algorithms can overcome them.…

Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…

Knowledge tracing models have enabled a range of intelligent tutoring systems to provide feedback to students. However, existing methods for knowledge tracing in learning sciences are predominantly reliant on statistical data and instructor-defined knowledge components, making it challenging to integrate AI-generated educational content with…

Research into "gaming the system" behavior in intelligent tutoring systems (ITS) has been around for almost two decades, and detection has been developed for many ITSs. Machine learning models can detect this behavior in both real-time and in historical data. However, intelligent tutoring system designs often change over time, in terms…

With the impacts of COVID-19 epidemic, e-learning has become a popular research issue. Therefore, how to upgrade the interactivity of e-learning, and allow learners to quickly access personalized and popular learning information from huge digital materials, is very important. However, chatbots are mostly used in automation, as well as simple…

Adaptivity in advanced learning technologies offer the possibility to adapt to different student backgrounds, which is difficult to do in a traditional classroom setting. However, there are mixed results on the effectiveness of adaptivity based on different implementations and contexts. In this paper, we introduce AI adaptivity in the context of a…

Understanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' preferences between AI and human tutors to support their learning. While AI demonstrates growing…

Students are termed "multitaskers," and it is likely that they easily fall prey to other subjects or topics that most interest them. They occasionally took heed or gave close and thoughtful attention to the lectures they were on. In the current educational system, our young generations receive materials from their leftovers, and their…

The emergence of generative artificial intelligence (GenAI) has reignited long-standing debates about technology's role in education. While GenAI potentially offers personalized learning, adaptive tutoring, and automated support, it also raises concerns about algorithmic bias, de-skilling educators, and diminishing human connection. This…

The increasing integration of generative Artificial Intelligence (AI) tools, such as ChatGPT, in education has prompted growing interest in their pedagogical potential and the emergent competencies required for their effective use in language instruction. While generative AI is beginning to influence language teaching and learning practices,…

The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…

Developing models and using mathematics are two key practices in internationally recognized science education standards, such as the Next Generation Science Standards (NGSS). However, students often struggle with these two intersecting practices, particularly when developing mathematical models about scientific phenomena. Formative…

No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA…