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Ali Alshammari – Education and Information Technologies, 2024
In online education, it is widely recognized that interaction and engagement have an impact on students' academic performance. While previous research has extensively explored interactions between students, instructors, and content, there has been limited exploration of course design elements that promote the fourth type of interaction:…
Descriptors: Learning Analytics, Learning Management Systems, Academic Achievement, Correlation
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Na-Ra Nam; Sue-Yeon Song – Innovations in Education and Teaching International, 2025
This empirical study uses a random forest algorithm to examine the factors that influence learners' persistence in online learning at a prominent Korean institution. The data were collected from students who began their studies in Spring 2021, and encompassed a range of variables including individual attributes, academic engagement, academic…
Descriptors: Adult Students, Academic Persistence, Foreign Countries, Influences
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Zheng, Chen – International Journal for the Scholarship of Teaching and Learning, 2023
This paper examines whether and to what extent student engagement with the learning management system (LMS) Blackboard affects students' academic performance during the COVID-19 pandemic. We find strong evidence that higher student engagement with Blackboard is associated with better academic performance. We also find that the association between…
Descriptors: Learner Engagement, Academic Achievement, COVID-19, Pandemics
Peterson, Sarah E. – ProQuest LLC, 2023
Instructors are steadily incorporating collaborative learning technology into their online classes to help promote effective learning strategies. A learning management system (LMS), such as Blackboard, offers their own collaborative technologies, but some instructors are turning to free and open source system (FOSS) to conduct these collaborative…
Descriptors: Technology Integration, Learning Management Systems, Open Educational Resources, Cooperative Learning
Morenike Adebodun – ProQuest LLC, 2020
The purpose of this study was to examine the predictive power of Academic and Learning Analytics models on the persistence, retention, and graduation rates for students enrolled in higher education institutions in the United States. Specifically, this study is concerned with the relationships between the present usage of Academic and Learning…
Descriptors: Predictor Variables, Learning Analytics, Academic Achievement, Higher Education
Rina Levy Cohen – ProQuest LLC, 2022
The aim of this study was to examine the relationship between common classroom help-seeking determinants (achievement goals, self-efficacy, prior knowledge, gender, and help-seeking perceptions) and help-seeking behaviors online (hint use percentage, latency of help seeking, answer attempt percentage, feedback level percentage, and seeking help…
Descriptors: Correlation, Help Seeking, Self Efficacy, Prior Learning
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Saqr, Mohammed; Jovanovic, Jelena; Viberg, Olga; Gaševic, Dragan – Studies in Higher Education, 2022
Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…
Descriptors: Meta Analysis, Learning Analytics, Predictor Variables, Correlation
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Foung, Dennis; Chen, Julia; Cheung, Kin – International Journal of Educational Technology in Higher Education, 2023
College transfer students are those who follow a different trajectory in their higher education journeys than traditional students, completing a sub-degree before pursuing a bachelor's degree at a university. While the possibility of transferring makes higher education accessible to these students, previous studies have found that they face…
Descriptors: College Transfer Students, Student Needs, Barriers, Academic Achievement