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Showing 1 to 15 of 46 results Save | Export
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Deniz Yesi?l; Fatma Bayrak – Open Praxis, 2025
Feedback is a critical component of the learning process and is essential to reinforce the effect of feedback with affective elements. Due to technological developments, providing automated feedback has become easy. Therefore, this study examined the effect of automated elaborated feedback provided with affective feedback on situational intrinsic…
Descriptors: Feedback (Response), Automation, Student Motivation, Self Efficacy
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Marlene Steinbach; Johanna Fleckenstein; Livia Kuklick; Jennifer Meyer – Journal of Computer Assisted Learning, 2025
Background: Providing students with information on their current performance could help them improve by stimulating their reflection, but negative feedback that saliently mirrors task-related failure can harm motivation. In the context of automated scoring based on artificial intelligence, we explored how feedback on written texts might be…
Descriptors: Student Motivation, Academic Achievement, Low Achievement, Feedback (Response)
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Yingbin Zhang; Luc Paquette; Nigel Bosch – International Journal of Artificial Intelligence in Education, 2025
Understanding the transitions among affective states during computer-based learning may guide the design of affect-responsive learning environments. Current studies have focused on the marginal strength of an affect transition, which is the average transition tendency over possible affective states preceding the transition. However, marginal…
Descriptors: Affective Behavior, Emotional Response, Electronic Learning, Learning Experience
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Sarah Seeley; Michael Cournoyea – Teaching & Learning Inquiry, 2025
Qualitative studies that examine the impact of generative AI technologies on higher education remain scant. Whether it is the ethical dimensions of modeling human emotions within these technologies or the authentic emotional reactions to these technologies and their outputs--emotionality is at the centre of generative AI discourse. This paper…
Descriptors: Robotics, Artificial Intelligence, Technology Uses in Education, Psychological Patterns
Mohammadreza Jalaeian Taghadomi – ProQuest LLC, 2021
Law enforcement officers can come into conflict with suspects when they need to act fast under time pressure. Improving such a decision-making skill is a challenge in a police academy. Academies can train future officers in correct psychomotor responses to attacks by a suspect. However, the ability to anticipate such attacks, and thereby make more…
Descriptors: Police, Police Education, Educational Technology, Video Technology
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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
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Torres-Jimenez, Jose; Lescano, Germán; Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo – Education and Information Technologies, 2023
Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…
Descriptors: Conflict, Identification, Computer Assisted Instruction, Cooperative Learning
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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
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Susanne Walan – International Journal of Technology and Design Education, 2025
Since the end of 2022, global discussions on Artificial Intelligence (AI) have surged, influencing diverse societal groups, such as teachers, students and policymakers. This case study focuses on Swedish primary school students aged 11-12. The aim is to examine their cognitive and affective perceptions of AI and their current usage. Data,…
Descriptors: Foreign Countries, Elementary School Students, Artificial Intelligence, Student Attitudes
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Slakmon, Benzi; Keynan, Omer; Shapira, Orly – International Journal of Computer-Supported Collaborative Learning, 2022
This study examines emotion regulation strategies in written digital discussions revolving around controversial issues. Twenty-five undergraduate students, placed in five study groups, took part in written digital discussions. Two groups were chosen to participate in the study. Participants were interviewed and were asked to read the transcript of…
Descriptors: Undergraduate Students, Emotional Response, Written Language, Computer Mediated Communication
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Samane Chamani; Atefeh Razi; Ismail Xodabande – Discover Education, 2023
The current longitudinal case study investigated emotional and motivational states in a self-directed and mobile-assisted language learning environment. The participant of the study was a highly motivated language learner who used the Busuu application for a period of one year to learn German. Tracing the participant's emotional and motivational…
Descriptors: Independent Study, Second Language Learning, Second Language Instruction, German
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Wang, Cong; Zhu, Sida; Zhang, Haijing – Journal of Computer Assisted Learning, 2023
Background: Since the outbreak of COVID-19, universities in Hong Kong have implemented online and hybrid teaching modes, making computer-assisted language learning (CALL) a primary way for English learning. Research on English learning motivation and self-regulation has seldom considered learners' emotions (satisfaction and preparedness) and the…
Descriptors: Foreign Countries, Student Motivation, Online Courses, English (Second Language)
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Zhang Yingbin; Paquette, Luc; Baker, Ryan S.; Ocumpaugh, Jaclyn; Bosch, Nigel; Biswas, Gautam; Munshi, Anabil – Journal of Learning Analytics, 2021
Confusion may benefit learning when it is resolved or partially resolved. Metacognitive strategies (MS) may help learners to resolve confusion when it occurs during learning and problem solving. This study examined the relationship between confusion and MS that students evoked in Betty's Brain, a computer-based learning-by-modelling environment…
Descriptors: Metacognition, Brain, Grade 6, Emotional Response
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Pawlak, Miroslaw – Language Teaching Research Quarterly, 2022
Research into the role of individual difference (ID) factors in the process of second and foreign language (L2) learning and teaching has been one of the most robust lines of inquiry in the field of second language acquisition (SLA; Dörnyei & Ryan, 2015; Griffiths & Soruç, 2020; Pawlak & Kruk, 2022). Most of these empirical…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Teaching Methods
Gorbunova, Irina B.; Kiseleva, Yulia N. – Journal of Educational Psychology - Propositos y Representaciones, 2020
The "Listening to Music" course is an important link in the music education of a child. The "Listening to Music" course fosters love and interest in music, teaches to understand its language, and develops emotional responsiveness in children. The article considers new opportunities in teaching the "Listening to Music"…
Descriptors: Music Education, Art Education, Teaching Methods, Listening Skills
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