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Paredes, Yancy Vance – ProQuest LLC, 2023
Experience, whether personal or vicarious, plays an influential role in shaping human knowledge. Through these experiences, one develops an understanding of the world, which leads to learning. The process of gaining knowledge in higher education transcends beyond the passive transmission of knowledge from an expert to a novice. Instead, students…
Descriptors: Artificial Intelligence, Learning Analytics, Man Machine Systems, Educational Technology
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Zamecnik, Andrew; Kovanovíc, Vitomir; Joksimovíc, Srécko; Grossmann, Georg; Ladjal, Djazia; Marshall, Ruth; Pardo, Abelardo – Journal of Computer Assisted Learning, 2023
Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…
Descriptors: Data Use, Group Dynamics, College Students, Cooperative Learning
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Galiya A. Abayeva; Gulzhan S. Orazayeva; Saltanat J. Omirbek; Gaukhar B. Ibatova; Venera G. Zakirova; Vera K. Vlasova – Contemporary Educational Technology, 2023
The concept of ubiquitous learning has emerged as a pedagogical approach in response to the advancements made in mobile, wireless communication, and sensing technologies. The domain of ubiquitous learning is distinguished by swift progression, thereby presenting a difficulty in maintaining current knowledge of its developments. The implementation…
Descriptors: Bibliometrics, Databases, Electronic Learning, Educational Technology
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Warakon Phommanee; Boonrat Plangsorn; Sutithep Siripipattanakul – Contemporary Educational Technology, 2023
Learning experience design (LXD) is a new wave in educational technology and learning design. This study was conducted to clarify conceptual change to practice by applying a systematic literature review to a combination text mining and bibliometric analysis technique to visualization network. Based on the study selection articles from SCOPUS. Our…
Descriptors: Learning Analytics, Learning Experience, Instructional Design, Bibliometrics
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Rotelli, Daniela; Monreale, Anna – Journal of Learning Analytics, 2023
The increased adoption of online learning environments has resulted in the availability of vast amounts of educational log data, which raises questions that could be answered by a thorough and accurate examination of students' online learning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensions that…
Descriptors: Learning Analytics, Learning Management Systems, Time on Task, Student Behavior
Collin Shepley; Justin D. Lane; Devin Graley – Remedial and Special Education, 2023
This study serves as an initial attempt to establish content validity for graphs likely to be included in trainings targeting progress monitoring for professionals serving learners with or at risk for disabilities. We created a survey containing 32 graphic displays of hypothetical learner data. These surveys were administered to a sample of…
Descriptors: Progress Monitoring, Students with Disabilities, Content Validity, Graphs
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Karaoglan Yilmaz, Fatma Gizem – Journal of Computing in Higher Education, 2022
This research examined the effect of learning analytics (LA) on students' metacognitive awareness and academic achievement in an online learning environment. In this study, a mixed methods approach was used and applied as a quasi-experimental design. The results of LA were sent to students weekly in LA group (experimental group) via learning…
Descriptors: Learning Analytics, Feedback (Response), Metacognition, Academic Achievement
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Darvishi, Ali; Khosravi, Hassan; Sadiq, Shazia; Gaševic, Dragan – British Journal of Educational Technology, 2022
Peer assessment has been recognised as a sustainable and scalable assessment method that promotes higher-order learning and provides students with fast and detailed feedback on their work. Despite these benefits, some common concerns and criticisms are associated with the use of peer assessments (eg, scarcity of high-quality feedback from peer…
Descriptors: Artificial Intelligence, Learning Analytics, Peer Evaluation, Student Evaluation
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Iordan, Marius Catalin; Giallanza, Tyler; Ellis, Cameron T.; Beckage, Nicole M.; Cohen, Jonathan D. – Cognitive Science, 2022
Applying machine learning algorithms to automatically infer relationships between concepts from large-scale collections of documents presents a unique opportunity to investigate at scale how human semantic knowledge is organized, how people use it to make fundamental judgments ("How similar are cats and bears?"), and how these judgments…
Descriptors: Artificial Intelligence, Mathematics, Learning Analytics, Semantics
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Ma, Boxuan; Lu, Min; Taniguchi, Yuta; Konomi, Shin'ichi – Smart Learning Environments, 2022
With the increasing use of digital learning materials in higher education, the accumulated operational log data provide a unique opportunity to analyzing student learning behaviors and their effects on student learning performance to understand how students learn with e-books. Among the students' reading behaviors interacting with e-book systems,…
Descriptors: Behavior Patterns, Electronic Publishing, Books, Reading Processes
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Baars, Martine; Viberg, Olga – International Journal of Mobile and Blended Learning, 2022
This paper discusses the possibilities of using and designing mobile technology for learning purposes coupled with learning analytics to support self-regulated learning (SRL). Being able to self-regulate one's own learning is important for academic success but is also challenging. Research has shown that without instructional support, students are…
Descriptors: Electronic Learning, Independent Study, Learning Analytics, Metacognition
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Pérez Sánchez, Carlos Javier; Calle-Alonso, Fernando; Vega-Rodríguez, Miguel A. – Education and Information Technologies, 2022
In this work, 29 features were defined and implemented to be automatically extracted and analysed in the context of NeuroK, a learning platform within the neurodidactics paradigm. Neurodidactics is an educational paradigm that addresses optimization of the learning and teaching process from the perspective of how the brain functions. In this…
Descriptors: Learning Analytics, Grade Prediction, Academic Achievement, Cooperative Learning
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Sidi, Yael; Blau, Ina; Shamir-Inbal, Tamar – Journal of Computer Assisted Learning, 2022
Background: Hyper-video technology allows reflection on learning materials by writing personal notes and by interactions with lecturers and peers through shared posts and replies. While research shows that integrating hyper-videos in educational systems can promote the learning processes and outcomes, an open question remains regarding its actual…
Descriptors: Active Learning, Cooperative Learning, College Students, Documentation
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Winne, Philip H. – Metacognition and Learning, 2022
Metacognition is the engine of self-regulated learning. At the object level, learners seek information and choose learning tactics and strategies they forecast will develop knowledge. At the meta level, learners gather and analyze data about learning events to draw conclusions, such as: Is this tactic a good fit to conditions? Was it effective?…
Descriptors: Metacognition, Learning Strategies, Computer Software, Data Analysis
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Lucía Márquez; Valeria Henríquez; Henrique Chevreux; Eliana Scheihing; Julio Guerra – British Journal of Educational Technology, 2024
Learning analytics (LA) is an emerging area that has had extensive development in higher education in recent years, focused both on the learning process of students within subjects and on monitoring their trajectories in training programmes. However, most of the developments remain in the pilot phase without reaching institutional adoption. This…
Descriptors: Higher Education, Learning Analytics, Ethics, Leadership
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