Since GPT-4's release it has shown novel abilities in a variety of domains. This paper explores the use of LLM-generated explanations as on-demand assistance for problems within the ASSISTments platform. In particular, we are studying whether GPT-generated explanations are better than nothing on problems that have no supports and whether…

Emotions are vital to learning success, especially in online learning environments. They make the difference between learning success and failure. Unfortunately, learners' emotional state is still rarely considered in online learning and teaching, although it is an important driver of learning success. This paper reports a work-in-progress…

This work proposes Dynamic Linear Epsilon-Greedy, a novel contextual multi-armed bandit algorithm that can adaptively assign personalized content to users while enabling unbiased statistical analysis. Traditional A/B testing and reinforcement learning approaches have trade-offs between empirical investigation and maximal impact on users. Our…

Digital Study Assistants (DSA) are an emerging type of software that combines web-based software architectures, various data sources, and algorithms from artificial intelligence (AI) to assist learners in improving their learning-related behaviors. In this paper, we summarize the implementation and results of a field study with a DSA for…

Studies have shown that on-demand assistance, additional instruction given on a problem per student request, improves student learning in online learning environments. Students may have opinions on whether an assistance was effective at improving student learning. As students are the driving force behind the effectiveness of assistance, there…

The pandemic environment forced the education sector to rely on sustainable educational processes to continue an uninterrupted delivery. Compared to any other sector, the transition to E-learning delivery presented multiple challenges for the education sector. This transformation by Educational Institutions around the world faced criticism and…

The use of social robots in education is a growing area of research and the potential future applications are various. However, the conversational models behind current social robots and chatbot systems often rely on rule-based and retrieval-based methods. This limits the social robot to predefined responses and topics, thus hindering it from…

A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…

Universities around the globe have begun implementing outcome-based learning (OBE). The curriculum will be revised, evaluated, and the outcomes of the assessments will be reported as part of this OBE implementation. Due to the importance of the evaluation method, several lecturers are searching for innovative approaches for assessing the…

Driven by new modes of information dissemination in this digital age and propelled by the necessity for online course delivery during the recent pandemic, online education, the current form of distance education, is not only the trend but the reality of teaching and learning today. It utilizes the internet and computer technology to offer…

In adaptive learning systems, various models are employed to obtain the optimal learning schedule and review for a specific learner. Models of learning are used to estimate the learner's current recall probability by incorporating features or predictors proposed by psychological theory or empirically relevant to learners' performance. Logistic…