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Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement
Baran, Evrim; AlZoubi, Dana; Morales, Anasilvia Salazar – TechTrends: Linking Research and Practice to Improve Learning, 2023
Computational analysis methods and machine learning techniques introduce innovative ways to capture classroom interactions and display data on analytics dashboards. Automated classroom analytics employ advanced data analysis, providing educators with comprehensive insights into student participation, engagement, and behavioral trends within…
Descriptors: Automation, Learning Analytics, Stakeholders, Computation
Veluvali, Parimala; Surisetti, Jayesh – Higher Education for the Future, 2022
Online education helped resume learning that had come to a momentary and uncertain pause with the onset of COVID-19 pandemic across the globe. Since then, learning in many educational institutions continued through synchronous and asynchronous modes, with teaching being undertaken remotely on digital platforms. In this large-scale migration…
Descriptors: Integrated Learning Systems, Learner Engagement, Higher Education, Literature Reviews
Brown, Alice; Lawrence, Jill; Basson, Marita; Redmond, Petrea – Higher Education Research and Development, 2022
Student engagement is consistently identified as a key predictor of learner outcomes within the online learning environment. However, there is limited guidance about using proactive strategies to improve engagement for low and non-engaged students: for example by specifically employing course learning analytics (CLA) and nudging strategies in…
Descriptors: Electronic Learning, Learner Engagement, Instructional Improvement, College Instruction
Lynnette Brice; Alison Harrison; Alan Cadwallader – Journal of Open, Flexible and Distance Learning, 2023
The purpose of this paper is to share insights gained from the discovery, design, and delivery phases of creating a three-tiered model of non-academic learning support in open, distance, and flexible learning (ODFL): "Learner Engagement and Success Services (LESS)", at Open Polytechnic | Te Pukenga, New Zealand. Presented as a case…
Descriptors: Ethics, Learning Analytics, Intervention, Foreign Countries
Kirp, David; Wechsler, Marjorie; Gardner, Madelyn; Ali, Titilayo Tinubu – Oxford University Press, 2022
"Disrupting Disruption" shows how three racially and ethnically diverse school districts--Union NJ, Union City OK, and Roanoke City VA--have defied the demographic odds, boosting overall graduation rates while shrinking or eliminating the opportunity gap. These districts resemble many others in their student population. What makes them…
Descriptors: School Restructuring, Ethnicity, Race, Student Diversity
Abe, Kousuke; Tanaka, Tetsuo; Matsumoto, Kazunori – International Association for Development of the Information Society, 2020
The authors are developing and using a fill-in workbook system that allows faculty members to ascertain the attitude of all students to classes including students who are not active, and to improve lectures through well-timed and appropriate actions. In this paper, in order to help teachers improve lessons and teaching materials, and to help…
Descriptors: Student Attitudes, Educational Improvement, Instructional Materials, Learning Management Systems
Solomon, Bonnie J.; Sun, Sarah; Temkin, Deborah – Child Trends, 2021
With the passage of the 2015 Every Student Succeeds Act (ESSA), states were required to add a fifth indicator on "School Quality or Student Success" (SQSS) to their school accountability systems. An analysis of submitted ESSA state plans found that 13 states included measures of school climate as their SQSS indicator or incorporated…
Descriptors: School Districts, Learning Analytics, Educational Environment, Educational Quality
Hershkovitz, Arnon – Technology, Instruction, Cognition and Learning, 2015
Still lacking in the mainstream data-driven approaches to studying educational settings is the very basic, most popular educational setting -- that is, the classroom. Capturing data that describes learning in the classroom is the focus of the current issue. The articles in this issue present a large variety of data sources, data collection tools…
Descriptors: Data, Data Use, Instructional Improvement, Data Collection