Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline the key aspects of designing, implementing and evaluating these agents. The data sources were empirical studies, including peer‐reviewed conference papers and journal articles, and the most recent publications, from the ACM Digital Library, IEEE Xplore, ProQuest, ScienceDirect, Scopus, SpringerLink, Taylor & Francis Online, Web of Science and Wiley Online Library. The remaining papers underwent a rigorous quality assessment. A filter study meeting the objective was based on keywords. Comparative analysis and synthesis of results were used to handle data and combine study outcomes. Out of 1162 search results, 13 studies were selected. The results indicate that agents promote dialogic learning, proficiency in knowledge domains, personalized feedback and empathic abilities as essential design principles. Most implementations employ a quantitative approach, and two variables are used for evaluation. Feedback types play a vital role in achieving positive results in learning performance and student perceptions. The main limitations and gaps are the time range for literature selection, the level of integration of the empathic field and the lack of a detailed development stage report. Moreover, future directions are the ethical implications of agents operating beyond scheduled learning times and the adoption of Responsible AI principles. In conclusion, this review provides a comprehensive framework of empathic PCAs, mostly in their evaluation. The systematic review registration number is osf.io/3xk6a . Practitioner notes: What is already known about this topic: Emotions play a pivotal role in shaping the interaction process, making it essential to consider them when designing methodological strategies or learning tools. Empathic Pedagogical Conversational Agents (PCAs) have emerged as a crucial approach for enhancing and personalizing the learning experience (24/7) for pupils and supporting human teachers in their teaching process. Despite the creation of numerous empathic PCAs, there is a scarcity of Systematic Literature Reviews (SLRs) on their application in the educational field, particularly concerning the integration of emotional abilities in combination with the competencies of each subject. What this paper adds: It offers new insights into the design principles underlying the integration of the empathic field. It reviews different approaches for incorporating students' prior knowledge in real time. It provides a comprehensive and up‐to‐date overview of the research designs used for implementation, including quantitative, qualitative and mixed methods. It examines the factors that influence the effectiveness of empathic PCA in teaching and learning. It evaluates the types of feedback that enhance the impact of the empathic field on learning outcomes. Implications for practice and/or policy: It is crucial to grasp the topics that this paper introduces in order to effectively integrate new learning tools into any context. Techno‐pedagogical designers seeking to gain insights into empathic PCAs will find immense value in this SLR, as it comprehensively covers each stage of the process. For future research endeavours, this study offers a wealth of ideas to draw upon, enabling researchers to address the challenges outlined and explore new avenues of investigation.

Emotional learning involves the acquisition of skills to recognize and manage emotions, develop care and concern for others, make responsible decisions, establish positive relationships, and handle challenging situations effectively. Time is an important variable in learning context and especially in the analysis of teaching-learning processes that take place in collaborative learning, whereas time management is crucial for effective learning. The aim of this work has been to analyze the effects of emotion management on time and self-management in e-learning and identify the competencies in time and self-management that are mostly influenced when students strive to achieve effective learning. To this end, we run an experiment with a class of high school students, which showed that increasing their ability to manage emotions better and more effectively enhances their competency to manage the time allocated to the learning practice more productively, and consequently their learning performance in terms of behavioral engagement and achievement and partly, in terms of cognitive engagement and self-regulation. Teacher affective feedback was proved to be a crucial factor to enhance cognitive engagement.Peer ReviewedPostprint (author's final draft

Monitoring users’ emotive states and using that information for providing feedback and scaffolding is crucial. In the learning context, emotions can be used to increase students’ attention as well as to improve memory and reasoning. In this context, tutors should be prepared to create affective learning situations and encourage collaborative knowledge construction as well as identify those students’ feelings which hinder learning process. In this paper, we propose a novel approach to label affective behavior in educational discourse based on fuzzy logic, which enables a human or virtual tutor to capture students’ emotions, make students aware of their own emotions, assess these emotions and provide appropriate affective feedback. To that end, we propose a fuzzy classifier that provides a priori qualitative assessment and fuzzy qualifiers bound to the amounts such as few, regular and many assigned by an affective dictionary to every word. The advantage of the statistical approach is to reduce the classical pollution problem of training and analyzing the scenario using the same dataset. Our approach has been tested in a real online learning environment and proved to have a very positive influence on students’ learning performance.

Several studies have explored the factors that influence self-efficacy as well as its contribution to academic development in online learning environments in recent years. However, little research has investigated the effect of a web-based learning environment on enhancing students’ beliefs about self-efficacy for learning. This is especially noticeable in the field of online distributed programming. We need to design online learning environments for programming education that foster both students’ self-efficacy for programming learning and the added value that students perceive of the tool as a successful learning environment. To that end, we conducted a quantitative analysis to collect and analyze data of students using an online Distributed Systems Laboratory (DSLab) in an authentic, long-term online educational experience. The results indicate that (1) our distributed programming learning tool provides an environment that increases students’ belief of programming self-efficacy; (2) the students’ experience with the tool strengthens their belief in the intrinsic value of the tool; however (3) the relationship between students’ belief in the tool intrinsic value and their self-efficacy is inconclusive. This study provides relevant implications for online distributed (or general) programming course teachers who seek to increase students’ engagement, learning and performance in this field.