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Paul Prinsloo; Mohammad Khalil; Sharon Slade – Journal of Computing in Higher Education, 2024
Central to the institutionalization of learning analytics is the need to understand and improve student learning. Frameworks guiding the implementation of learning analytics flow from and perpetuate specific understandings of learning. Crucially, they also provide insights into how learning analytics acknowledges and positions itself as entangled…
Descriptors: Learning Analytics, Data, Ecology, Models
Michelle Wong – ProQuest LLC, 2023
Teacher data use is often centered around standardized testing. Such data use that is commonly centered on standardized tests and used during professional development does not necessarily transform teacher practice toward equity and fails to change teacher conceptualizations of students while also perpetuating inequitable practices. Conversely,…
Descriptors: Data Use, Standardized Tests, Faculty Development, Outcomes of Education
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Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
Marco D'Alessio – ProQuest LLC, 2024
Learning designers face challenges integrating learning analytics (LA) when designing learner-content interactions in corporate online education. The quality of the learning design directly affects learners' engagement and impacts the transfer of learning at work. This qualitative study aimed to explore the perspectives of experienced learning…
Descriptors: Curriculum Design, Attitudes, Learning Analytics, Data Use
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Baig, Maria Ijaz; Shuib, Liyana; Yadegaridehkordi, Elaheh – International Journal of Educational Technology in Higher Education, 2020
Big data is an essential aspect of innovation which has recently gained major attention from both academics and practitioners. Considering the importance of the education sector, the current tendency is moving towards examining the role of big data in this sector. So far, many studies have been conducted to comprehend the application of big data…
Descriptors: Educational Research, Educational Trends, Learning Analytics, Student Behavior
Perez, Zeke, Jr.; von Zastrow, Claus – Education Commission of the States, 2023
Data governance is a core obligation for leaders and staff across any agency that collects, stores or uses individuals' data. It ensures that individuals' personal information is protected, and can support the continuous improvement of data quality and use, particularly when it includes well-defined processes, structure and responsibilities.…
Descriptors: Governance, Data Use, Privacy, Information Management
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Lasater, Kara; Albiladi, Waheeb S.; Bengtson, Ed – Journal of Cases in Educational Leadership, 2021
Data use is considered a key lever in school improvement processes, but the punitive pressure of high-stakes accountability can influence whether or not data use is enacted in ways which facilitate improvement. School leaders must learn to respond to high-stakes accountability in ways which lead teachers to feel safe, efficacious, and agentic with…
Descriptors: Leadership Role, High Stakes Tests, Data Use, Educational Improvement
US Department of Education, 2020
The U.S. Department of Education's (Department) mission is to promote student achievement and preparation for global competitiveness by fostering educational excellence and ensuring equal access. The Department pursues its mission by establishing policies and distributing corresponding funds, focusing national attention on key educational issues,…
Descriptors: Public Agencies, Institutional Mission, Academic Achievement, Educational Policy