NotesFAQContact Us
Collection
Advanced
Search Tips
What Works Clearinghouse Rating
Showing 1 to 15 of 637 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Baerheim, Anders; Ødegaard, Elin E.; Ness, Ingunn Johanne – Policy Futures in Education, 2023
In interprofessional (IP) workplace education, course and project leaders need a deeper understanding of how students learn. Basically, in IP workplace learning students learn from each other, from the affected agents (patients, clients, children, youth, or elderly), from the staff, and from using multitudes of artifacts. Most of these…
Descriptors: Interprofessional Relationship, Teamwork, Group Unity, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Keiichi Kobayashi – Educational Psychology Review, 2024
This study was conducted to meta-analytically investigate the influence of teaching vs. no teaching expectancy on the learning effects of teaching after preparatory learning. A meta-analysis of 39 studies revealed that a weighted mean effect size for the effect of teaching after studying with or without teaching expectancy vs. merely studying…
Descriptors: Learning Processes, Expectation, Prior Learning, Teacher Role
Peer reviewed Peer reviewed
Direct linkDirect link
George Veletsianos; Shandell Houlden; Nicole Johnson – TechTrends: Linking Research and Practice to Improve Learning, 2024
Much of the literature on artificial intelligence (AI) in education imagines AI as a tool in the service of teaching and learning. Is such a one-way relationship all that exists between AI and learners? In this paper we report on a thematic analysis of 92 participant responses to a story completion exercise which asked them to describe a classroom…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Interaction
Yingbo Ma – ProQuest LLC, 2023
Collaborative learning provides learners with significant opportunities to collaborate on solving problems and creating better products. There has been a growing utilization of adaptive and intelligent systems to support productive learning while promoting collaborative practices. One of the core capabilities of these adaptive and intelligent…
Descriptors: Cooperative Learning, Models, Interaction, Behavior
Peer reviewed Peer reviewed
Direct linkDirect link
Di Sun; Gang Cheng; Heng Luo – Interactive Learning Environments, 2024
Recently, researchers have proposed to leverage technology-supported data (log files) to investigate temporal and sequential patterns of interaction behaviors in learning processes. There are two major challenges to be addressed: clarifying the positioning of interaction levels and identifying the evolution of the interaction action patterns in…
Descriptors: Foreign Countries, Undergraduate Students, Computer Science, MOOCs
Peer reviewed Peer reviewed
Direct linkDirect link
Changqin Huang; Jianhui Yu; Fei Wu; Yi Wang; Nian-Shing Chen – Journal of Computer Assisted Learning, 2024
Background: Investigating emotion sequence patterns in the posts of discussion forums in massive open online courses (MOOCs) holds a vital role in shaping online interactions and impacting learning achievement. While the majority of research focuses on the relationship between emotions and interactions in MOOC forum discussions, research on…
Descriptors: MOOCs, Discussion Groups, Computer Mediated Communication, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Yun-Qi Bai; Ya-Qian Xu; Jian-Jun Xiao – Interactive Learning Environments, 2024
This study takes the value-based adoption model and CIE model of the learning process as the theoretical basis and combines them to explore the influencing factors and mechanisms of learners' online interaction and perceived value. Based on the questionnaire survey data of 81 learners' potential factors and their 45,166 real-time behavior data on…
Descriptors: MOOCs, Interaction, Student Behavior, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Martha, Ati Suci Dian; Santoso, Harry B.; Junus, Kasiyah; Suhartanto, Heru – IEEE Transactions on Learning Technologies, 2023
Nowadays, online learning has become commonplace in higher education. Various factors influence the success of online learning. Factors such as low self-regulation and co-regulation of learning skills can affect student engagement and motivation in online learning activities. Therefore, it is essential to provide external support in the online…
Descriptors: Metacognition, Motivation, Scaffolding (Teaching Technique), Self Management
Peer reviewed Peer reviewed
Direct linkDirect link
Osipenko, Maria – Education and Information Technologies, 2022
A data-driven model where individual learning behavior is a linear combination of certain stylized learning patterns scaled by learners' affinities is proposed. The absorption of stylized behavior through the affinities constitutes "building blocks" in the model. Non-negative matrix factorization is employed to extract common learning…
Descriptors: Behavior Patterns, Models, Undergraduate Students, Preferences
Peer reviewed Peer reviewed
Direct linkDirect link
Lachner, Andreas; Hoogerheide, Vincent; van Gog, Tamara; Renkl, Alexander – Educational Psychology Review, 2022
Teaching the contents of study materials by providing explanations to fellow students can be a beneficial instructional activity. A learning-by-teaching effect can also occur when students provide explanations to a real, remote, or even fictitious audience that cannot be interacted with. It is unclear, however, which underlying mechanisms drive…
Descriptors: Instruction, Instructional Effectiveness, Models, Educational Practices
Peer reviewed Peer reviewed
Direct linkDirect link
Xia, Xiaona – SAGE Open, 2022
Mining problems and exploring rules are the key problems in the learning process, and also the difficulties in education big data. Therefore, taking learning behavior as the research objective, this study demonstrates the collaborative training method of multi view learning interaction process driven by big data, so as to realize the tendency…
Descriptors: Learning Analytics, Learning Processes, Cooperative Learning, Training Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Robin Samuelsson – Journal of Mixed Methods Research, 2025
Video has become a widespread tool for capturing naturalistic behavioral data. While mixed methods show great potential in understanding the active nature of children's interaction, only a few studies have developed mixed methods for video-based interaction research. This paper presents a mixed methods embodied interaction model appropriate for…
Descriptors: Video Technology, Data Collection, Child Behavior, Interaction
Peer reviewed Peer reviewed
Direct linkDirect link
Min Lee; Tan Roy Jun Yi; Chen Der-Thanq; Huang Jun Song; Hung Wei Loong David – Education and Information Technologies, 2025
A noticeable surge in students' widespread adoption of ChatGPT in the past year brought attention to the need for a deeper understanding of their interactions with this new technology. While attempts at theorising learner-ChatGPT interactions have been made, few studies offer empirical accounts of the interactions between learners and ChatGPT.…
Descriptors: Interaction, Man Machine Systems, Artificial Intelligence, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Goldman, Susan R.; Hmelo-Silver, Cindy E.; Kyza, Eleni ?. – Cognition and Instruction, 2022
This special issue joins the recent but growing effort to expand knowledge in the learning sciences, by examining the notion of participation in teacher-researcher collaborative design (co-design). Co-design is not just a means to an end; it is a context where professional learning happens. Each of the seven papers describes teacher-researcher…
Descriptors: Teacher Collaboration, Educational Researchers, Partnerships in Education, Learning Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Bellocchi, Alberto – Journal of Research in Science Teaching, 2022
Emerging research is beginning to explore the role of social bonds in science learning. In this study, I develop a novel conceptual framework extending recent science education research that has adopted Scheff's social bond theory in understanding science learning. I use microsociological methods to understand social bonds and knowledge…
Descriptors: Science Education, Interpersonal Relationship, Learning Processes, Educational Sociology
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  43