Teacher Emotion, Pedagogical Agents and Psychological Well-Being: Implications for Student Development

A special issue of Education Sciences (ISSN 2227-7102). This special issue belongs to the section "Education and Psychology".

Deadline for manuscript submissions: 10 November 2026 | Viewed by 7041

Special Issue Editors


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Guest Editor
Key Laboratory of Modern Teaching Technology, Ministry of Education, Shaanxi Normal University, Xi'an 710062, China
Interests: information technology that promotes teaching and learning

E-Mail Website
Guest Editor
Key Laboratory of Modern Teaching Technology, Ministry of Education, Shaanxi Normal University, Xi’an 710062, China
Interests: video lecture design; learning strategies; cognitive neuroscience

Special Issue Information

Dear Colleagues,

For students in school settings, teachers serve as their most pivotal “significant others.” Virtually every aspect of teachers—their emotional states, pedagogical roles, and psychological well-being—profoundly shapes students’ learning, motivation, and development. Over the years, research has increasingly recognized the central role of teachers’ emotions and mental health, as well as the emerging influence of affective pedagogical agents, in shaping educational experiences. However, teachers’ individual characteristics vary widely, and the mechanisms through which their emotions, well-being, and interactions with pedagogical agents affect students’ academic outcomes and socio-emotional growth remain complex and multifaceted. For instance, factors such as emotional valence, arousal levels, complex emotions, and emotional consistency (in both teachers and affective pedagogical agents) may impact students’ development differently depending on contextual variables (e.g., teaching materials) and learner characteristics (e.g., gender, socioeconomic status, motivation, thinking style, and personality). Given the growing recognition of the intertwined roles of teacher emotion, psychological well-being, and pedagogical agents, it is crucial to advance a nuanced understanding of how these factors jointly contribute to students’ cognitive, emotional, and social development. This Special Issue aims to highlight cutting-edge research that unravels these complex interactions and informs both educational theory and classroom practices, ultimately fostering healthier, more effective learning environments.

This Special Issue aims to advance our theoretical and empirical understanding of the intricate relationships among teacher emotion, pedagogical agents, and psychological well-being, and how these factors jointly shape students’ learning and development. We welcome original studies, reviews, and conceptual papers that explore emotional, cognitive, and contextual mechanisms linking teachers’ emotional and psychological states to student outcomes and classroom processes.

Suggested Themes (including, but are not limited to, the following):

  • Teacher emotions and their impact on students’ learning, motivation, and well-being.
  • The role of teachers’ psychological well-being in shaping classroom climate and student outcomes.
  • The design and influence of affective pedagogical agents on teaching and learning processes.
  • Interactions between teacher emotion, pedagogical practices, and contextual factors (e.g., culture, subject area, teaching modality).
  • Cross-level or longitudinal studies examining the dynamic interplay between teacher and student emotions.
  • Intervention studies aimed at promoting teacher well-being and emotional regulation in educational contexts.

Prof. Dr. Xiying Li
Prof. Dr. Zhongling Pi
Guest Editors

Fenge Tan
Guest Editor Assistant

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Keywords

  • teacher emotion
  • pedagogical agents
  • psychological well-being
  • academic emotion
  • teacher–student interaction
  • student learning

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Published Papers (4 papers)

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Research

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25 pages, 916 KB  
Article
Deep Learning with Visualization-Based Worked Examples to Enhance Students’ Algebra Problem Solving Ability and Metacognitive Awareness
by Windia Hadi, Benny Hendriana, Widyah Noviana and Csaba Csíkos
Educ. Sci. 2026, 16(4), 608; https://doi.org/10.3390/educsci16040608 - 10 Apr 2026
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Abstract
This study aims to examine the improvement of algebra problem-solving ability and metacognitive awareness among junior high school students through the use of visualization based on a deep learning approach. The research employed a quantitative method with a quasi-experimental design, specifically a pretest–posttest [...] Read more.
This study aims to examine the improvement of algebra problem-solving ability and metacognitive awareness among junior high school students through the use of visualization based on a deep learning approach. The research employed a quantitative method with a quasi-experimental design, specifically a pretest–posttest control group design. The population consisted of all students from public schools in Tangerang City, Indonesia. The sample comprised seventh-grade students studying algebra. A purposive sampling technique was used to determine the experimental and control groups, with a total sample size of 51 students. The instruments included an algebra problem-solving ability test consisting of nine essay questions and a metacognitive awareness questionnaire with 52 items. Data were collected using these two instruments, with a pretest administered before the intervention and a posttest administered afterward. Data analysis was conducted using a prerequisite test, continued with independent sample t-tests, nonparametric tests, ANCOVA, and multiple linear regression. The results based on statistics indicated a significant improvement in students’ algebra problem-solving ability with a large effect. Nevertheless, the absolute increase in problem-solving scores in the experimental group is very small (N-gain mean = 0.02). Additionally, metacognitive awareness was not found to be a significant predictor of problem-solving ability; instead, initial ability (pretest) emerged as the strongest predictor. Only understanding the problem has a moderate effect; planning strategies has a small effect, and otherwise there is no effect. In conclusion, the use of visualization-based worked examples with a deep learning approach has a statistically significant effect, but its impact on improving students’ abilities should be interpreted with caution. So the practical effects of the intervention are limited; however, metacognitive awareness is not the main predictor in algebra problem-solving ability. Full article
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21 pages, 352 KB  
Article
Fostering Creative Instructional Design: Unpacking the Role of Metacognitive Scaffolding in an AI Pedagogical Agent for Pre-Service Preschool Teachers—A Moderated Mediation Model
by Xiangli Zhang and Wenlan Zhang
Educ. Sci. 2026, 16(1), 172; https://doi.org/10.3390/educsci16010172 - 22 Jan 2026
Cited by 2 | Viewed by 1153
Abstract
Despite advances in AI pedagogical agents, research on developing creative instructional design remains limited, and how they affect pre-service teachers’ creative thinking—especially with metacognitive scaffolding—is unclear. Based on metacognitive and creativity investment theories, this study examines how such scaffolding in an AI agent [...] Read more.
Despite advances in AI pedagogical agents, research on developing creative instructional design remains limited, and how they affect pre-service teachers’ creative thinking—especially with metacognitive scaffolding—is unclear. Based on metacognitive and creativity investment theories, this study examines how such scaffolding in an AI agent fosters creative instructional design among pre-service preschool teachers, and whether critical thinking mediates this relationship moderated by AI dependency. A quasi-experimental design was used with 120 pre-service preschool teachers, who were assigned to the experimental group or the control group. Data on metacognitive awareness, AI dependency, critical thinking, and creative thinking were gathered through valid measuring instruments, and innovative curricula were evaluated by experts. The results show that the experimental group achieved much better scores on creative instructional design ideas after the test than the control group. The moderated mediation analysis revealed a critical thinking-mediated pathway that was moderated by AI dependency. In conclusion, AI pedagogical agents with metacognitive scaffolding (MAS-based) improved critical thinking and promoted deeper, more independent creative thinking, thus improving creative instructional design, through a pathway that is moderated by the degree of AI dependency. This study offers valuable theoretical and practical insights to cultivate creative teaching skills. Full article
15 pages, 1663 KB  
Article
Role of the Instructor’s Social Cues in Instructional Videos
by Zhongling Pi, Xuemei Huang, Richard E. Mayer, Xin Zhao and Xiying Li
Educ. Sci. 2026, 16(1), 82; https://doi.org/10.3390/educsci16010082 - 7 Jan 2026
Viewed by 1001
Abstract
Little attention has been paid to whether an instructor’s hand-pointing gestures or use of a mouse-guided arrow can mitigate the attentional loss caused by an instructor’s happy facial expressions or can enhance the social benefits of these expressions in instructional videos. The goal [...] Read more.
Little attention has been paid to whether an instructor’s hand-pointing gestures or use of a mouse-guided arrow can mitigate the attentional loss caused by an instructor’s happy facial expressions or can enhance the social benefits of these expressions in instructional videos. The goal of the present study is to determine whether social cues in an instructional video affect learning processes and outcomes. The participants were 57 female students from a university. We employed a 2 × 2 mixed experimental design. The instructor’s facial expression was a within-subject variable, while the type of pointing cue was a between-subject variable. Students who had the smiling instructor rather than the bored instructor gave higher ratings of the perceived positive emotion of the instructor, felt more positive emotion, and had more motivation to learn. Eye-tracking technology showed that students who learned with the smiling instructor spent more time looking at the content on the slides than those who learned with a bored instructor. Students who learned with the smiling instructor scored higher on a learning outcome post-test than those who learned with the bored instructor. Among female Chinese students, this pattern is consistent with the five steps posited by the positivity principle, which concludes that people learn better from instructors who exhibit positive social cues. Pointing with a human hand was not superior to pointing with an arrow, suggesting that in this case hand-pointing was not a strong social cue and did not moderate the effects of facial expression. Given the exclusively female sample, future research should examine whether these effects generalize across genders. Full article
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24 pages, 1250 KB  
Systematic Review
Can Generative Artificial Intelligence Effectively Enhance Students’ Mathematics Learning Outcomes?—A Meta-Analysis of Empirical Studies from 2023 to 2025
by Baoxin Liu, Wenlan Zhang and Fangfang Wang
Educ. Sci. 2026, 16(1), 140; https://doi.org/10.3390/educsci16010140 - 16 Jan 2026
Cited by 2 | Viewed by 3653
Abstract
Generative artificial intelligence (GenAI) shows transformative potential in mathematics education. However, empirical findings remain inconsistent, and a systematic synthesis of its effects across distinct engagement dimensions is lacking. This preregistered meta-analysis (INPLASY2025110051) systematically reviewed 22 empirical studies (46 independent samples, N = 5232) [...] Read more.
Generative artificial intelligence (GenAI) shows transformative potential in mathematics education. However, empirical findings remain inconsistent, and a systematic synthesis of its effects across distinct engagement dimensions is lacking. This preregistered meta-analysis (INPLASY2025110051) systematically reviewed 22 empirical studies (46 independent samples, N = 5232) published between 2023 and 2025. The results indicated that GenAI has a moderate positive impact on students’ mathematics learning outcomes (g = 0.534). Moderation analysis further revealed that the level of GenAI integration in teaching, sample size, and learning content are the primary factors influencing this effect. The study found that the effect was most pronounced under the creative transformation (CT) integration mode, was significant when applied to geometry learning, and was stronger in studies with small samples or small class sizes; collaborative learning approaches also significantly enhance these mathematics learning outcomes. By contrast, educational stage and intervention duration did not show significant moderating effects. The GRADE assessment indicated that while the overall evidence is supportive, the certainty of evidence is stronger for cognitive outcomes than for non-cognitive domains. The findings also offer a reference for future research on constructing a human–machine collaborative learning environment. Full article
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