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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
Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
Maria Theobald – British Journal of Educational Psychology, 2025
Background and Aims: The hypothesis that study strategies can compensate for less study time in predicting learning outcomes has often been proposed but rarely tested empirically. Methods: In the present study, 231 university students reported their daily perceived time spent on self-study, study strategies (planning, monitoring, concentration and…
Descriptors: Study Skills, Study Habits, Learning Strategies, Time on Task
Vilija Hiltunen; Saule Raiziene; Gintautas Silinskas – Reading and Writing: An Interdisciplinary Journal, 2025
The main aim of the current study was to investigate the role of teacher-child relationship quality in kindergarten on children's motivation (interest in reading and task persistence) and reading skills in Grade 1. A total of 231 children (age at baseline 6.8 years; 50.6% girls) completed reading-related tasks and answered questions about their…
Descriptors: Teacher Student Relationship, Kindergarten, Student Motivation, Reading Motivation
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
Olanrewaju P. Olaogun; Nathaniel J. Hunsu – European Journal of Psychology of Education, 2025
Students have misconceptions about many scientific topics they encounter in the classroom--such misconceptions are especially rife in subjects with counterintuitive concepts. Several studies have copiously documented students' misconceptions in different science domains. Research shows that students' misconceptions can be resistant to change and…
Descriptors: College Students, College Faculty, Engineering Education, Misconceptions

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