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Kasepalu, Reet; Chejara, Pankaj; Prieto, Luis P.; Ley, Tobias – Technology, Knowledge and Learning, 2022
Monitoring and guiding multiple groups of students in face-to-face collaborative work is a demanding task which could possibly be alleviated with the use of a technological assistant in the form of learning analytics. However, it is still unclear whether teachers would indeed trust, understand, and use such analytics in their classroom practice…
Descriptors: Teacher Attitudes, Secondary School Teachers, Technology Uses in Education, Online Systems
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García-Senín, Stéphanie; Arguedas, Marta; Daradoumis, Thanasis – Research on Education and Media, 2022
The assessment of students' academic achievements helps to increase learning effectiveness by encouraging each student to recognise his/her strengths and areas for improvement. To do so, pedagogical activities that encourage direct and frequent evaluation must be considered. This paper focuses on how a learning management system such as Google…
Descriptors: Learning Analytics, STEM Education, Art Education, Academic Achievement
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Albó, Laia; Barria-Pineda, Jordan; Brusilovsky, Peter; Hernández-Leo, Davinia – International Journal of Artificial Intelligence in Education, 2022
Over the last 10 years, learning analytics have provided educators with both dashboards and tools to understand student behaviors within specific technological environments. However, there is a lack of work to support educators in making data-informed design decisions when designing a blended course and planning appropriate learning activities. In…
Descriptors: Learning Analytics, Visual Aids, Design, Learning Activities
González, Carlos; López, Dany; Calle-Arango, Lina; Montenegro, Helena; Clasing, Paula – ECNU Review of Education, 2022
Purpose: This study aims to explore Chilean students' digital technology usage patterns and approaches to learning. Design/Approach/Methods: We conducted this study in two stages. We worked with one semester learning management systems (LMS), library, and students' records data in the first one. We performed a k-means cluster analysis to identify…
Descriptors: Foreign Countries, Electronic Learning, Technology Uses in Education, Use Studies
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Hershkovitz, Arnon; Tabach, Michal; Cohen, Anat – Journal of Educational Computing Research, 2022
In a large-scale quantitative study that adopted a learning analytics approach, we searched for associations between students' activity in a game-based online mathematics learning environment and their mathematics achievements on a national standardized test. Students were active in the environment throughout the school year, and particularly…
Descriptors: Electronic Learning, Learning Activities, Mathematics Achievement, Elementary School Students
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Tzeng, Jian-Wei; Lee, Chia-An; Huang, Nen-Fu; Huang, Hao-Hsuan; Lai, Chin-Feng – International Review of Research in Open and Distributed Learning, 2022
Massive open online courses (MOOCs) are open access, Web-based courses that enroll thousands of students. MOOCs deliver content through recorded video lectures, online readings, assessments, and both student-student and student-instructor interactions. Course designers have attempted to evaluate the experiences of MOOC participants, though due to…
Descriptors: Online Courses, Models, Learning Analytics, Artificial Intelligence
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Weidlich, Joshua; Gaševic, Dragan; Drachsler, Hendrik – Journal of Learning Analytics, 2022
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…
Descriptors: Causal Models, Inferences, Learning Analytics, Comparative Analysis
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Zhang, Jingjing; Huang, Yicheng; Gao, Ming – Journal of Learning Analytics, 2022
Network analytics has the potential to examine new behaviour patterns that are often hidden by the complexity of online interactions. One of the varied network analytics approaches and methods, the model of collective attention, takes an ecological system perspective to exploring the dynamic process of participation patterns in online and flexible…
Descriptors: Network Analysis, Video Technology, MOOCs, Attention Control
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Mubarak, Ahmed A.; Cao, Han; Zhang, Weizhen – Interactive Learning Environments, 2022
Online learning has become more popular in higher education since it adds convenience and flexibility to students' schedule. But, it has faced difficulties in the retention of the continuity of students and ensure continual growth in course. Dropout is a concerning factor in online course continuity. Therefore, it has sparked great interest among…
Descriptors: Prediction, Dropouts, Interaction, Learning Analytics
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Li, Xu; Ouyang, Fan; Chen, WenZhi – Journal of Computing in Higher Education, 2022
Group formation is a critical factor which influences collaborative processes and performances in computer-supported collaborative learning (CSCL). Automatic grouping has been widely used to generate groups with heterogeneous attributes and to maximize the diversity of students' characteristics within a group. But there are two dominant challenges…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Group Dynamics, Grouping (Instructional Purposes)
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Wang, Han; Huang, Tao; Tian, Jun; Yang, Huali; Han, Pengdong – Best Evidence in Chinese Education, 2022
In the age of Internet Plus, the deep integration of information technology into education and individualized instruction have become a growing trend in education development. Self-regulated learning is a key element of student core competence, but easy to be overlooked in basic education. The purpose of this study is to establish the data…
Descriptors: Elementary School Students, Scaffolding (Teaching Technique), Learning Strategies, Models
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Isaac Kofi Nti; Faiza Umar Bawah; Juanita Ahia Quarcoo; Favour Kalos – Africa Education Review, 2022
Computers in education, along with soft-computing technology applications, have revolutionised global interconnectedness and the need for a well-educated workforce. Many studies worldwide explore technology in education, often relying on systematic reviews, though concerns about selection bias have emerged. This article takes a different approach,…
Descriptors: Bibliometrics, Computer Uses in Education, Artificial Intelligence, Educational Research
Jionghao Lin; Shaveen Singh; Lela Sha; Wei Tan; David Lang; Dragan Gasevic; Guanliang Chen – Grantee Submission, 2022
To construct dialogue-based Intelligent Tutoring Systems (ITS) with sufficient pedagogical expertise, a trendy research method is to mine large-scale data collected by existing dialogue-based ITS or generated between human tutors and students to discover effective tutoring strategies. However, most of the existing research has mainly focused on…
Descriptors: Intelligent Tutoring Systems, Teaching Methods, Dialogs (Language), Man Machine Systems
Vincent Aleven; Jori Blankestijn; LuEttaMae Lawrence; Tomohiro Nagashima; Niels Taatgen – Grantee Submission, 2022
Past research has yielded ample knowledge regarding the design of analytics-based tools for teachers and has found beneficial effects of several tools on teaching and learning. Yet there is relatively little knowledge regarding the design of tools that support teachers when a class of students uses AI-based tutoring software for self-paced…
Descriptors: Educational Technology, Artificial Intelligence, Problem Solving, Intelligent Tutoring Systems
Heeryung Choi – ProQuest LLC, 2022
Learning analytics researchers have been diligently integrating trace data to study Self-Regulated Learning (SRL). Compared to traditionally used survey data, trace data, such as log or clickstream data designed and interpreted to understand a certain SRL construct, are considered to be more effective in capturing dynamic SRL as fine-grained…
Descriptors: Learning Analytics, Metacognition, Validity, Comparative Analysis
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