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Xu, Zhuojia; Yuan, Hua; Liu, Qishan – IEEE Transactions on Education, 2021
Contribution: This article explored blended learning by implementing a student-centered teaching method based on the flipped classroom and small private online course (SPOC). The impact of general online learning behavior on student performance was analyzed. This work is practical and provides enlightenment for learning analysis and individualized…
Descriptors: Academic Achievement, Blended Learning, Prediction, Performance Factors
Hriez, Raghda Fawzey; Al-Naymat, Ghazi – Journal of Computing in Higher Education, 2021
Depicting the reason for the mismatch between instructor expectations of students' performance in advanced courses and their actual performance has been a challenging issue for a long time, which raises the question of why such a mismatch exists. An implicit reason for this mismatch is the student's weakness in prerequisite course skills. To solve…
Descriptors: Required Courses, Advanced Courses, Graphs, Outcomes of Education
Cormack, Sophie H.; Eagle, Laurence A.; Davies, Mark S. – Assessment & Evaluation in Higher Education, 2020
Many studies have found a relationship between students' self-reported procrastination and their grades. Few studies have used learning analytic data as a behavioural measure of procrastination in order to predict performance, and there is no systematic research on how this relationship may differ across assessments or disciplines. In this study…
Descriptors: Correlation, Time Management, Academic Achievement, Grades (Scholastic)
Li, Shuang; Wang, Shuang; Du, Junlei; Pei, Yu; Shen, Xinyi – Journal of Computer Assisted Learning, 2022
Background: Failure to effectively organize and manage learning time is an important factor influencing online learners' performance. Investigation of time-investment patterns for online learning will provide educators with useful knowledge of how learners engage in and regulate their online learning and support them in tailoring online course…
Descriptors: Online Courses, Time Management, Time Factors (Learning), Learning Strategies
Picones, Gio; PaaBen, Benjamin; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2022
In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…
Descriptors: Prediction, Academic Achievement, Learning Analytics, Concept Mapping
Mohammed Alzaid – ProQuest LLC, 2022
Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…
Descriptors: Learning Analytics, Self Evaluation (Individuals), Programming, Problem Solving
Darko, Charles – SAGE Open, 2021
"Blackboard" is an important Learning Management System (LMS) employed at most higher education institutions to engage and interact with students during their studies. Students within Material Science and Engineering (MSE) often use these LMS's to absorb mathematical derivations, scientific information and submit coursework tasks. In…
Descriptors: Integrated Learning Systems, Correlation, Grades (Scholastic), Academic Achievement
Foimapafisi, Tuamanaia; Raudonyte, Ieva – UNESCO International Institute for Educational Planning, 2021
Large-scale learning assessments can be used to generate performance and contextual data on student learning outcomes. The UNESCO International Institute for Educational Planning (IIEP-UNESCO) has conducted a qualitative study to explore both how and why learning assessment data are used in six sub-Saharan African countries. This Information Sheet…
Descriptors: International Organizations, Foreign Countries, Educational Policy, Policy Formation
Meaney, Michael J.; Fikes, Tom – Journal of Learning Analytics, 2023
This paper leverages cluster analysis to provide insight into how traditionally underrepresented learners engage with entry-level massive open online courses (MOOCs) intended to lower the barrier to university enrolment, produced by a major research university in the United States. From an initial sample of 260,239 learners, we cluster analyze a…
Descriptors: MOOCs, Ethics, Equal Education, Socioeconomic Status
Phillips, Tanner; Ozogul, Gamze – TechTrends: Linking Research and Practice to Improve Learning, 2020
In this study the authors conducted an empirical, bibliometric analysis of current literature in learning analytics. The authors performed a citation network analysis and found three dominant clusters of research. A qualitative thematic review of publications in these clusters revealed distinct context, goals, and topics. The largest cluster…
Descriptors: Learning Analytics, Educational Research, Bibliometrics, Citation Analysis
Parkes, Sarah; Benkwitz, Adam; Bardy, Helen; Myler, Kerry; Peters, John – Higher Education Research and Development, 2020
Universities are now compelled to attend to metrics that (re)shape our conceptualisation of the student experience. New technologies such as learning analytics (LA) promise the ability to target personalised support to profiled 'at risk' students through mapping large-scale historic student engagement data such as attendance, library use, and…
Descriptors: Learning Analytics, Higher Education, Educational Objectives, Foreign Countries
Leu, Katherine – RTI International, 2020
Postsecondary education is awash in data. Postsecondary institutions track data on students' demographics, academic performance, course-taking, and financial aid, and have put these data to use, applying data analytics and data science to issues in college completion. Meanwhile, an extensive amount of higher education data are being collected…
Descriptors: Learning Analytics, Postsecondary Education, Academic Achievement, Graduation Rate
Priya Harindranathan – ProQuest LLC, 2020
A major problem faced by instructors post-implementation of unsupervised online assessments is that they may lack real-time access to the students' actual learning behaviors. Limitations in student-feedback, limited know-how of accessing and analyzing log data, and large class sizes could restrict instructors' access to learners' behaviors. This…
Descriptors: Tests, Supervision, Student Evaluation, Computer Assisted Testing
Ahmad Faza; Ilyana Agri Lestari – International Review of Research in Open and Distributed Learning, 2025
When students enter higher education, self-regulated learning (SRL) involving goal setting, planning, monitoring, and reflection is crucial for academic success. This study systematically reviews SRL strategies, supporting technologies, and their impacts, especially with the shift to online learning due to the COVID-19 pandemic. Following…
Descriptors: Metacognition, Educational Benefits, Learning Management Systems, Goal Orientation
Chinsook, Kittipong; Khajonmote, Withamon; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jantakoon, Thada – Higher Education Studies, 2022
Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…
Descriptors: Student Behavior, Learning Analytics, Computer Software, Rating Scales

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