This paper investigates using multi-label deep learning approach to extending the understanding of cognitive presence in MOOC discussions. Previous studies demonstrate the challenges of subjectivity in manual categorisation methods. Training automatic single-label classifiers may preserve this subjectivity. Using a triangulation approach, we…

Rising interest in artificial intelligence in education reinforces the demand for evidence-based implementation. This study investigates how tutor agents' physical embodiment and anthropomorphism (student-reported sociability, animacy, agency, and disturbance) relate to affective (on-task enjoyment) and cognitive (task performance) learning within…

Adaptive learning is provided in intelligent tutoring systems (ITS) to enable learners with varying abilities to meet their expected learning outcomes. Despite the personalized learning afforded by ITSes using adaptive learning, learners are still susceptible to shallow learning. Introducing metacognitive tutoring to teach learners how to be aware…

This study proposes that the gestures of an agent tutor in a multimedia learning environment can generate positive and negative emotions in learners and influence their cognitive processes. To achieve this, we developed and integrated positive and negative agent tutor gestures in a multimedia learning environment directed by cognitive gestures.…

The study investigates the effects of AI-enhanced multi-display language teaching systems on English as a Foreign Language (EFL) learners. Utilizing a pretest-posttest random assignment experimental design, the research involved 302 EFL students aged 19 to 28 in a higher education setting. The study examines the effects of AI-powered virtual…

Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension training typically focuses on the skill level required for a standardized learning stage, without considering the impact of individual differences in linguistic competence. This…

Background/Purpose: This study investigates the integration of neuropedagogy, neuroimaging, artificial intelligence (AI), and deep learning in educational systems. The research aims to elucidate how these technologies can be synergistically applied to optimize learning processes based on individual neurocognitive profiles, thereby enhancing…

In this paper, we consider a minimalistic and behavioristic view of AIS to enable a standardizable mapping of both the behavior of the system and of the learner. In this model, the "learners" interact with the learning "resources" in a given learning "environment" following preset steps of learning…

We reflect upon a paper we wrote that was published in 1995 (20 years ago). We outline the motivation for the work and situate it in the state of the art at that time. We suggest that a key contribution was to highlight the need to provide support for learners who reason with external representations. The support must be flexible enough to…

Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…

Several adaptive and intelligent tutoring systems (AITS) have been developed with different variables. These variables were the cognitive traits, cognitive styles, and learning behavior. However, these systems neglect the importance of the learner's multiple intelligences, the learner's skill level and the learner's feedback when implementing…

This article describes an advanced learning technology used to investigate hypotheses about learning by teaching. The proposed technology is an instance of a teachable agent, called SimStudent, that learns skills (e.g., for solving linear equations) from examples and from feedback on performance. SimStudent has been integrated into an online,…

Recently, there has been growing emphasis on supporting robust learning within intelligent tutoring systems, assessed by measures such as transfer to related skills, preparation for future learning, and longer term retention. It has been shown that different pedagogical strategies promote robust learning to different degrees. However, the student…

Developing personalised web-based learning systems has been an important research issue in e-learning because no fixed learning pathway will be appropriate for all learners. However, most current web-based learning platforms with personalised curriculum sequencing tend to emphasise the learner preferences and interests in relation to personalised…

The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…