Affective intelligent tutoring systems (ATSs) are gaining recognition for their role in personalized learning through adaptive automated education based on students’ affective states. This scoping review evaluates recent advancements and the educational impact of ATSs, following PRISMA guidelines for article selection and analysis. A structured search of the Web of Science (WoS) and Scopus databases resulted in 30 studies covering 27 distinct ATSs. These studies assess the effectiveness of ATSs in meeting learners’ emotional and cognitive needs. This review examines the technical and pedagogical aspects of ATSs, focusing on how emotional recognition technologies are used to customize educational content and feedback, enhancing learning experiences. The primary characteristics of the selected studies are described, emphasizing key technical features and their implications for educational outcomes. The discussion highlights the importance of emotional intelligence in educational environments and the potential of ATSs to improve learning processes. This review identifies gaps in the current research and suggests future directions, including broader implementation across diverse educational settings and deeper integration of affective data to refine system responsiveness. Future research should investigate the integration of advanced natural dialogue modules and generative AI to create more sophisticated interfaces, underscoring the role of affective adaptation in educational technology.

To test the suitability of an automatic system for emotional management in the classroom following the control‐value theory of achievement emotions (CVT) framework, the performance of an emotional expression recognition software of our creation is evaluated in an online synchronous context. Sixty students from the Faculty of Education at the University of Alicante participated in 16 educational activities recording close‐ups of their faces and completing the AEQ emotional self‐report, as well as detailed reports from the subsequent review of their videos. In addition, they completed the VCQ‐36 test to measure their volitional competencies and relate their influence on their emotional response. The results indicate a high coherence between the emotional expressions detected by the automatic system and the detailed emotional self‐reports, but insufficient precision to meet the CVT requirements. On the other hand, both the AEQ test results and the emotion expression recognition software suggest students' preference for participative activities as opposed to passive ones. Meanwhile, statistical analysis results indicate that volitional competencies seem to influence the emotional response of students in the educational context, although the AI system does not show sufficient sensitivity in this field. Implications and limitations of this study for future work are discussed. Practitioner notes: What is already known about this topic: Student motivation and involvement in the learning process are highly related to appropriate emotional regulation, which can be associated with particular educational activities, strategies and methodologies. Deep learning technology based on convolutional neural networks feeds automatic systems focused on facial expression recognition from image analysis. What this paper adds: There is high coherence between the emotional expressions detected by the AI system and the students' emotional self‐reports, but the AI system provides just emotional valences, insufficient to meet the CVT framework. Both emotional self‐reports and the emotion recognition software suggest students' preference for active educational activities as opposed to passive ones. Volitional competencies seem to influence the emotional response of students in the educational context. Implications for practice and/or policy: It is possible to use automatic systems to effectively monitor the emotional response of students in the learning process. Only if sensitivity improved, a real‐time, easy‐to‐interpret emotional expression recognition software interface could be implemented to assist teachers with the emotional management of their classes within the CVT framework, maximizing their motivation and engagement.

The use of virtual reality (VR) as an educational tool for autism spectrum disorder (ASD) children is a research field that started some 20 years ago. ASD is associated with deficiencies in communication and social interaction, as well as restricted and repetitive behavioural patterns, according to the fifth edition of the diagnostic and statistical manual of mental disorders (DSM-5). By using the ISI Web of Knowledge as the reference data basis, we perform a bibliometric study of the use of VR as an educational tool for high-functioning ASD children. By this study we can quantify, on the one hand, the up to day importance of the different types of VR applied to this field: immersive or non-immersive, as well as the use of human or agent avatars. On the other hand, we can also differentiate amongst those interventions that work on emotional and social competences. The analysis of periods of research scarce, research abundance and research trends provides a dynamic view of the strategies used in this field in the last 20 years and suggests future lines of research.

The number of Autism Spectrum Disorder (ASD) postsecondary students going to University is increasing. Nonetheless, these students face more difficulties than their neuro-typical peers, due to their communication and behaviour impairments. This fact is widely recognized worldwide, and there is an increasing concern in providing them with adequate support both in their transition and beyond. The purpose of this paper is twofold. Firstly, to provide an overall summary of the general requirements of ASD students in the postsecondary education transition with strategies for facilitation, and, secondly, to analyse the possibilities of Virtual Reality (VR) as a support instrument in the transition process. We rely on a brief review of the literature to summarize the main needs and current strategies. In spite of the increasing concern, there is room for establishing general protocols to help the transition process. The use VR in fulfilling this task appears limited, but it seems to be promising.