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Damian Betebenner; Charles A. DePascale – National Center for the Improvement of Educational Assessment, 2024
In the wake of the COVID-19 pandemic, educators and policymakers have scrambled to assess the impact on student learning. Popular metrics that have gained traction are the notions of "years of learning lost" or "months behind," which attempt to quantify the educational setbacks caused by the pandemic. The allure of these…
Descriptors: COVID-19, Pandemics, Progress Monitoring, Academic Achievement
Hess, Richard M. – ProQuest LLC, 2021
The purpose of this study was to explore and analyze the utilization of learning analytics data produced by a learning management system as an indicator of learners' self-regulation. In the Spring of 2021, 258 learners at a four-year, mid-Atlantic university provided access to their learning management system data. Of those 258 learners, 86…
Descriptors: Self Control, Integrated Learning Systems, Learning Analytics, Undergraduate Students
Krivova, Anna Leonidovna; Kalliopin, Alexander Konstantinovich; Korotaeva, Irina Eduardovna; Shafazhinskaya, Natalia Evgenievna; Ermilova, Daria Yuryevna – Journal of Educational Psychology - Propositos y Representaciones, 2021
In the era of the digital educational environment, where each participant of the educational process is actively involved in its development, the Internet and its services have become a popular tool. Open education network tools are defined as ICT tools that ensure the formation and maintenance of network electronic information resources of an…
Descriptors: Social Networks, Social Media, Educational Technology, Technology Integration
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Forthmann, Boris; Förster, Natalie; Souvignier, Elmar – Journal of Intelligence, 2022
Monitoring the progress of student learning is an important part of teachers' data-based decision making. One such tool that can equip teachers with information about students' learning progress throughout the school year and thus facilitate monitoring and instructional decision making is learning progress assessments. In practical contexts and…
Descriptors: Learning Processes, Progress Monitoring, Robustness (Statistics), Bayesian Statistics
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Foster, Ed; Siddle, Rebecca – Assessment & Evaluation in Higher Education, 2020
In this article we investigate the effectiveness of learning analytics for identifying at-risk students in higher education institutions using data output from an in-situ learning analytics platform. Amongst other things, the platform generates 'no-engagement' alerts if students have not engaged with any of the data sources measured for 14…
Descriptors: Learning Analytics, At Risk Students, Identification, Higher Education
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Crescenzi-Lanna, Lucrezia – British Journal of Educational Technology, 2020
Learning Analytics and Multimodal Learning Analytics are changing the way of analysing the learning process while students interact with an educational content. This paper presents a systematic literature review aimed at describing practices in recent Multimodal Learning Analytics and Learning Analytics research literature in order to identify…
Descriptors: Learning Modalities, Learning Analytics, Student Behavior, Progress Monitoring
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Crowley-Cyr, Lynda; Hevers, James – Journal of University Teaching and Learning Practice, 2021
The University of Southern Queensland's online study environment continues to grow with over 16,000 students studying online. Pre-Covid-19, online enrolments typically represent around 67% of all students studying at USQ. This article usefully analyses quantitative data in order to evaluate the effectiveness of the pilot of an online peer-assisted…
Descriptors: Peer Teaching, Learner Engagement, Academic Achievement, Electronic Learning
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Mozahem, Najib Ali – International Journal of Mobile and Blended Learning, 2020
Higher education institutes are increasingly turning their attention to web-based learning management systems. The purpose of this study is to investigate whether data collected from LMS can be used to predict student performance in classrooms that use LMS to supplement face-to-face teaching. Data was collected from eight courses spread across two…
Descriptors: Integrated Learning Systems, Data Use, Prediction, Academic Achievement