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Lili Aunimo; Janne Kauttonen; Marko Vahtola; Salla Huttunen – Journal of Computing in Higher Education, 2025
Institutions of higher education possess large amounts of learning-related data in their student registers and learning management systems (LMS). This data can be mined to gain insights into study paths, study styles and possible bottlenecks on the study paths. In this study, we focused on creating a predictive model for study completion time…
Descriptors: Data Collection, Learning Management Systems, Study Habits, Time on Task
Ameloot, Elise; Rotsaert, Tijs; Schellens, Tammy – Journal of Computer Assisted Learning, 2022
Background: Although blended learning (BL) has multiple educational prospects, it also poses challenges such as keeping students motivated. Objectives: This study investigates students' perceptions of how learning analytics (LA) can be used to support the design of a BL environment in order to promote students' basic need for relatedness, which is…
Descriptors: Learning Analytics, Blended Learning, Student Attitudes, Need Gratification
Ifenthaler, Dirk; Gibson, David; Zheng, Longwei – International Association for Development of the Information Society, 2018
This study is part of a research programme investigating the dynamics and impacts of learning engagement in a challenge-based digital learning environment. Learning engagement is a multidimensional concept which includes an individual's ability to behaviourally, cognitively, emotionally, and motivationally engage in an on-going learning process.…
Descriptors: Learner Engagement, Electronic Learning, Learning Analytics, College Students
de Smet, Milou J. R.; Leijten, Mariëlle; Van Waes, Luuk – Written Communication, 2018
This study aims to explore the process of reading during writing. More specifically, it investigates whether a combination of keystroke logging data and eye tracking data yields a better understanding of cognitive processes underlying fluent and nonfluent text production. First, a technical procedure describes how writing process data from the…
Descriptors: College Students, Reading Processes, Writing Processes, Eye Movements
Zimbardi, Kirsten; Colthorpe, Kay; Dekker, Andrew; Engstrom, Craig; Bugarcic, Andrea; Worthy, Peter; Victor, Ruban; Chunduri, Prasad; Lluka, Lesley; Long, Phil – Assessment & Evaluation in Higher Education, 2017
Feedback is known to have a large influence on student learning gains, and the emergence of online tools has greatly enhanced the opportunity for delivering timely, expressive, digital feedback and for investigating its learning impacts. However, to date there have been no large quantitative investigations of the feedback provided by large teams…
Descriptors: Student Evaluation, Feedback (Response), Academic Achievement, Achievement Gains
Junco, Reynol – Learning, Media and Technology, 2014
Numerous studies have shown that college students use computers, the internet, and social networking websites (SNS) at high rates; however, all of these studies have relied on self-report measures of technology use. Research in other areas of human behavior has shown that self-report measures are considerably inaccurate when compared to actual…
Descriptors: College Students, Social Networks, Web Sites, Time on Task
Peer reviewedJacobs, George M. – Issues in Applied Linguistics, 1994
Studies the effect of vocabulary glossing on reading comprehension in second-language learning. Findings reveal that there was a significant effect for glossing but no significant interactions between the treatment and any of the other variables, i.e., psychological type, tolerance of ambiguity, proficiency, frequency of gloss use, perceived value…
Descriptors: Ambiguity, College Students, Data Analysis, Data Collection

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