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Beege, Maik; Schneider, Sascha – Educational Technology Research and Development, 2023
Pedagogical agents were found to enhance learning but studies on the emotional effects of such agents are still missing. While first results show that pedagogical agents with an emotionally positive design might especially foster learning, these findings might depend on the gender of the agent and the learner. This study investigated whether…
Descriptors: Psychological Patterns, Design, Emotional Response, Educational Technology
Yen-Jung Chen; Liwei Hsu; Shao-wei Lu – Computer Assisted Language Learning, 2024
It is well known that teachers' feedback plays an important role in students' learning, as it enhances learners' cognitive development; yet there has been little research on how positive feedback given in the form of emojis works in computer-assisted language learning (CALL) courses. In this study, an experiment was designed to clarify how English…
Descriptors: Visual Aids, English (Second Language), Second Language Learning, Feedback (Response)
Said A. Salloum; Khaled Mohammad Alomari; Aseel M. Alfaisal; Rose A. Aljanada; Azza Basiouni – Smart Learning Environments, 2025
The integration of artificial intelligence in educational environments has the potential to revolutionize teaching and learning by enabling real-time analysis of students' emotions, which are crucial determinants of engagement, motivation, and learning outcomes. However, accurately detecting and responding to these emotions remains a significant…
Descriptors: Artificial Intelligence, Emotional Response, Psychological Patterns, Individualized Instruction
Daniel Kangwa; Mgambi Msambwa Msafiri; Xiulan Wan; Antony Fute – Social Psychology of Education: An International Journal, 2024
Online and computer-assisted learning have become widespread in the rapidly evolving education landscape. However, these learning modalities uniquely challenge academic integrity, escalating the potential for academic cheating. This systematic review used thematic and narrative syntheses to examine the relationships and the effects of self-doubt…
Descriptors: Self Esteem, Self Concept, Self Management, Influences
Long Li; Mira Kim – Australasian Journal of Educational Technology, 2024
This paper explores international students' engagement with educational technology for self-regulated English learning at an Australian university. Despite the increased use of automated feedback systems (AFSs) for language assessment, students' critical engagement with them for independent learning remains under-researched. The study primarily…
Descriptors: Feedback (Response), Automation, English Language Learners, English (Second Language)
Elif Sari; Turgay Han – Journal of Computer Assisted Learning, 2024
Background: With the growing trend of integrating technology into teaching environments, using Automated Writing Evaluation (AWE) in writing instruction has been extensively studied over the last two decades. The studies on AWE mostly investigated its impact on students' writing proficiencies and revealed conflicting results. However, very few…
Descriptors: Writing Evaluation, Second Language Learning, Second Language Instruction, English (Second Language)
Meurice, Alice; Henin, Véronique; Van Reet, Marie – Research-publishing.net, 2019
We are three teachers of business English in higher education who have developed a project for our second-year management students to co-create their own video document, exploring a business question. Our intention is to determine whether the complexity of our entire teaching sequence, and more specifically the use of Information and Communication…
Descriptors: Student Reaction, Emotional Response, Second Language Learning, Computer Assisted Instruction
Bringula, Rex P.; Fosgate, Ian Clement O., Jr.; Garcia, Neil Peter R.; Yorobe, Josf Luinico M. – Journal of Educational Computing Research, 2018
This experimental study investigated the effects of the use of two versions of a pedagogical agent named personal instructing agent (PIA) on the mathematics performance of students. The first version exhibits synthetic facial expressions while the second version does not exhibit facial expression (i.e., neutral facial expression). Two groups of…
Descriptors: Comparative Analysis, Mathematics Achievement, Feedback (Response), Mathematics Tests
D'Mello, Sidney; Graesser, Art – Learning and Instruction, 2012
We propose a model to explain the dynamics of affective states that emerge during deep learning activities. The model predicts that learners in a state of engagement/flow will experience cognitive disequilibrium and confusion when they face contradictions, incongruities, anomalies, obstacles to goals, and other impasses. Learners revert into the…
Descriptors: Motivation Techniques, Emotional Response, Learning Processes, Affective Behavior
Shen, Liping; Wang, Minjuan; Shen, Ruimin – Educational Technology & Society, 2009
Using emotion detection technologies from biophysical signals, this study explored how emotion evolves during learning process and how emotion feedback could be used to improve learning experiences. This article also described a cutting-edge pervasive e-Learning platform used in a Shanghai online college and proposed an affective e-Learning model,…
Descriptors: Feedback (Response), Student Attitudes, Learning Experience, Foreign Countries
Lin, Hao-Chiang Koong; Wang, Cheng-Hung; Chao, Ching-Ju; Chien, Ming-Kuan – Turkish Online Journal of Educational Technology - TOJET, 2012
Emotional expression in Artificial Intelligence has gained lots of attention in recent years, people applied its affective computing not only in enhancing and realizing the interaction between computers and human, it also makes computer more humane. In this study, emotional expressions were applied into intelligent tutoring system, where learners'…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Artificial Intelligence, Focus Groups