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Di Wu; Xinyan Zhang; Kaili Wang; Longkai Wu; Wei Yang – Educational Technology Research and Development, 2025
Artificial Intelligence (AI) is driving ecological shifts and systemic reforms in education. As practitioners of educational reform, teachers' behavioral intention to experience and accept the effectiveness of AI technologies will affect the quality of educational change. From an educational ecology perspective, this study explores the impact of…
Descriptors: Teacher Behavior, Intention, Technology Uses in Education, Educational Technology
Kangkang Li; Jiaming Lan; Yongbin Hu – Educational Technology Research and Development, 2025
To investigate the potential of GPT-4.0 feedback to substitute teacher feedback in flipped classrooms, we conducted research that GPT-4.0 and a course teacher provided cognitive, praise, and mitigating feedback weekly via a course discussion platform, respectively. At the end of each topic, 89 third-year university students majoring in Educational…
Descriptors: Comparative Analysis, Artificial Intelligence, Feedback (Response), Questioning Techniques
Efren de la Mora Velasco; Matthew Moreno – Educational Technology Research and Development, 2025
The measurable effects of music in online learning remains a topic of extensive debate, largely due to inconsistent findings within existing literature. Many of these inconclusive results stem from research methodologies that focus on singular perspectives, often overlooking a balance between cognitive challenges and emotional benefits of…
Descriptors: Music, Acoustics, Electronic Learning, Cognitive Processes
Webb, Mary E.; Fluck, Andrew; Magenheim, Johannes; Malyn-Smith, Joyce; Waters, Juliet; Deschênes, Michelle; Zagami, Jason – Educational Technology Research and Development, 2021
Machine learning systems are infiltrating our lives and are beginning to become important in our education systems. This article, developed from a synthesis and analysis of previous research, examines the implications of recent developments in machine learning for human learners and learning. In this article we first compare deep learning in…
Descriptors: Artificial Intelligence, Learning, Adjustment (to Environment), Accountability
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
Linda Castañeda; Victoria I. Marín; Daniel Villar-Onrubia – Educational Technology Research and Development, 2024
Technology-mediated interactions and datafication are increasingly central in contemporary social dynamics and institutions, including teaching and learning processes. In order to fully understand the complex entanglements of human and non-human actants that emerge in postdigital education, it is essential to imagine new methodological approaches…
Descriptors: Learning Activities, Topology, Learning Processes, Technology Uses in Education
Bhavya, Bhavya; Chen, Si; Zhang, Zhilin; Li, Wenting; Zhai, Chengxiang; Angrave, Lawrence; Huang, Yun – Educational Technology Research and Development, 2022
Captions play a major role in making educational videos accessible to all and are known to benefit a wide range of learners. However, many educational videos either do not have captions or have inaccurate captions. Prior work has shown the benefits of using crowdsourcing to obtain accurate captions in a cost-efficient way, though there is a lack…
Descriptors: Layout (Publications), Video Technology, Accessibility (for Disabled), Cooperation
Lu, Hong; Wang, Yue; Wu, Xiu-yuan; Lu, Xiao-feng; Liu, Xing-bo – Educational Technology Research and Development, 2023
The current study aimed to measure preservice teachers' skills in implementing pedagogical model of collaborative problem solving (CPS) using a more advanced and novel human-to-agent computerized assessment instrument. By doing so, a framework with three major skills in the implementation of CPS and four major individual problem-solving processes…
Descriptors: Preservice Teachers, Cooperative Learning, Problem Solving, Artificial Intelligence
Xiaoyan Chu; Minjuan Wang; Jonathan Michael Spector; Nian-Shing Chen; Ching Sing Chai; Gwo-Jen Hwang; Xuesong Zhai – Educational Technology Research and Development, 2025
The Flipped Classroom Model (FCM) has gained widespread acceptance in higher education as an effective pedagogical strategy. Despite its success, the FCM still faces persistent concerns, including a lack of personalized interaction, limited application to introductory courses, and insufficient analysis of the learning process. The integration of…
Descriptors: Flipped Classroom, Artificial Intelligence, Technology Uses in Education, Educational Technology
Chen-Chung Liu; Chen Wei Chiu; Chia-Hui Chang; Fang-ying Lo – Educational Technology Research and Development, 2024
Educational chatbots are gaining momentum due to their distinctive affordances of interactivity, immediacy, ease of use, and individualized experience. However, a fairly limited body of literature discusses how a chatbot can facilitate collaborative learning among peers in extensive reading contexts to encourage more vibrant interactions…
Descriptors: Educational Technology, Cooperative Learning, Peer Relationship, Reading Instruction
Liu, Jianhua – Educational Technology Research and Development, 2013
This article reports the design, development, and evaluation of an online software application for assessing students' understanding of curricular content based on concept maps. This computer-based assessment program, called the Assessment Agent System, was designed by following an agent-oriented software design method. The Assessment Agent System…
Descriptors: Artificial Intelligence, Computer System Design, Computer Software, Use Studies
Chin, Doris B.; Dohmen, Ilsa M.; Cheng, Britte H.; Oppezzo, Marily A.; Chase, Catherine C.; Schwartz, Daniel L. – Educational Technology Research and Development, 2010
One valuable goal of instructional technologies in K-12 education is to prepare students for future learning. Two classroom studies examined whether Teachable Agents (TA) achieves this goal. TA is an instructional technology that draws on the social metaphor of teaching a computer agent to help students learn. Students teach their agent by…
Descriptors: Concept Mapping, Educational Technology, Elementary School Students, Science Instruction
Jonassen, David H.; Ionas, Ioan Gelu – Educational Technology Research and Development, 2008
Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…
Descriptors: Cognitive Processes, Inferences, Thinking Skills, Causal Models
Peer reviewedBopry, Jeanette – Educational Technology Research and Development, 1999
Discusses educational technology as a form of technical rationality and considers the conflict between practitioners' epistemological position as constructivists and technical rationality. Topics include cybernetics; autonomous systems theory; enactive constructivism; representation versus effective action; mind and memory; enaction in artificial…
Descriptors: Artificial Intelligence, Constructivism (Learning), Cybernetics, Educational Technology

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