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David P. Reid; Timothy D. Drysdale – IEEE Transactions on Learning Technologies, 2024
The designs of many student-facing learning analytics (SFLA) dashboards are insufficiently informed by educational research and lack rigorous evaluation in authentic learning contexts, including during remote laboratory practical work. In this article, we present and evaluate an SFLA dashboard designed using the principles of formative assessment…
Descriptors: Learning Analytics, Laboratory Experiments, Electronic Learning, Feedback (Response)
Kingir, Sevgi; Gok, Bilge; Bozkir, Ahmet Selman – Journal of Baltic Science Education, 2020
Educational data mining is a developing research trend for exploring hidden patterns and natural associations among a set of student, teacher or school related variables. Discovering profiles of preservice science teachers using data mining methods would give important information about quality of teacher education programs and future science…
Descriptors: Data Analysis, Preservice Teachers, Science Teachers, Motivation
van Halema, Nicolette; van Klaveren, Chris; Drachsler, Hendrik; Schmitz, Marcel; Cornelisz, Ilja – Frontline Learning Research, 2020
For decades, self-report instruments -- which rely heavily on students' perceptions and beliefs -- have been the dominant way of measuring motivation and strategy use. Event-based measures based on online trace data arguably has the potential to remove analytical restrictions of self-report measures. The purpose of this study is therefore to…
Descriptors: Independent Study, Learning Motivation, Learning Strategies, Student Behavior
Van Horne, Sam; Curran, Maura; Smith, Anna; VanBuren, John; Zahrieh, David; Larsen, Russell; Miller, Ross – Technology, Knowledge and Learning, 2018
Instructional technologists and faculty in post-secondary institutions have increasingly adopted learning analytics interventions such as dashboards that provide real-time feedback to students to support student' ability to regulate their learning. But analyses of the effectiveness of such interventions can be confounded by measures of students'…
Descriptors: Chemistry, Science Instruction, Learning Strategies, Questionnaires
Cho, Moon-Heum; Yoo, Jin Soung – Interactive Learning Environments, 2017
Many researchers who are interested in studying students' online self-regulated learning (SRL) have heavily relied on self-reported surveys. Data mining is an alternative technique that can be used to discover students' SRL patterns from large data logs saved on a course management system. The purpose of this study was to identify students' online…
Descriptors: Online Courses, Self Management, Active Learning, Data Analysis
Lin, Guan-Yu – Journal of Educational Computing Research, 2016
This study has two central purposes: First, it examines not only the roles of gender and persistence in undergraduate computing majors' learning self-efficacy, computer self-efficacy, and programming self-efficacy but also Bandura's hypothesized sources of self-efficacy; second, it examines the influence of sources of efficacy on the three…
Descriptors: Sex Role, Persistence, Self Efficacy, Beliefs
Miller, L. Dee; Soh, Leen-Kiat; Samal, Ashok; Kupzyk, Kevin; Nugent, Gwen – Journal of Educational Data Mining, 2015
Learning objects (LOs) are important online resources for both learners and instructors and usage for LOs is growing. Automatic LO tracking collects large amounts of metadata about individual students as well as data aggregated across courses, learning objects, and other demographic characteristics (e.g. gender). The challenge becomes identifying…
Descriptors: Comparative Analysis, Data Analysis, Hierarchical Linear Modeling, Electronic Learning
Pardo, Abelardo; Han, Feifei; Ellis, Robert A. – IEEE Transactions on Learning Technologies, 2017
Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…
Descriptors: Student Centered Learning, Learning Theories, College Students, Academic Achievement
Lawanto, Oenardi; Stewardson, Gary – National Center for Engineering and Technology Education, 2009
The objective of this study was to evaluate grade 9-12 students' motivation while engaged in two different engineering design projects: marble-sorter and bridge designs. The motivation components measured in this study were focused on students' intrinsic (IGO) and extrinsic (EGO) goal orientations, task value (TV), self-efficacy for learning and…
Descriptors: Student Surveys, Questionnaires, Correlation, Student Motivation