Due to the rise of virtual reality and the--at least now--hypothetical construct of the Metaverse, learning processes are increasingly transferred to immersive virtual learning environments. While the literature provides few design guidelines, most papers miss an application and evaluation description of the design and development processes. As a…

Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in…

Knowledge tracing (KT) aims to trace students' evolving knowledge states based on their learning sequences. Recently, some deep learning based models have been proposed to incorporate the historical information of individuals to trace students' knowledge states and achieve encouraging progress. However, these works ignore the collaborative…

Research in learning technologies is often focused on optimizing some aspects of human learning. However, the usefulness of practical learning environments is heavily influenced by their weakest aspects, and, unfortunately, there are many things that can go wrong in the learning process. In this article, we argue that in many circumstances, it is…

One of the promises of edu-metaverse is its ability to provide a virtual environment that enables us to engage in learning activities that are similar to or on par with reality. The digital enhancements introduced in a virtual environment contribute to our increased expectations of novel learning experiences. However, despite its promising…

In this article, we advocate for and propose a novel concept map driven knowledge tracing (CMKT) model, which utilizes educational concept map for learner modeling. This article particularly addresses the issue of learner data sparseness caused by the unwillingness to practice and irregular learning behaviors on the learner side. CMKT considers…

Nowadays, online learning has become commonplace in higher education. Various factors influence the success of online learning. Factors such as low self-regulation and co-regulation of learning skills can affect student engagement and motivation in online learning activities. Therefore, it is essential to provide external support in the online…

Learning paths are curated sequences of resources organized in a way that a learner has all the prerequisite knowledge needed to achieve their learning goals. In this article, we systematically map the techniques and algorithms that are needed to create such learning paths automatically. We focus on open educational resources (OER), though a…

In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…

The present study is related to the problem associated with student assessment with online examinations at higher educational institutes (HEIs). With the current COVID-19 outbreak, the majority of educational institutes are conducting online examinations to assess their students, where there would always be a chance that the students go for…

This exploratory analysis investigates the integration of ChatGPT in self-directed learning (SDL). Specifically, this study examines YouTube content creators' language-learning experiences and the role of ChatGPT in their SDL, building upon Song and Hill's conceptual model of SDL in online contexts. Thematic analysis of interviews with 19…

To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…

The advent of generative artificial intelligence (GAI), exemplified by ChatGPT, has introduced both new opportunities and challenges in science, technology, engineering, and mathematics (STEM) and entrepreneurship education. This exploratory quasi-experimental study examined the effects of ChatGPT-assisted collaborative learning (CCL) on students'…