NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Type
Reports - Research10
Tests/Questionnaires10
Journal Articles9
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 10 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Marijn Martens; Ralf De Wolf; Lieven De Marez – Education and Information Technologies, 2024
Algorithmic systems such as Learning Analytics (LA) are driving the datafication and algorithmization of education. In this research, we focus on the appropriateness of LA systems from the perspective of parents and students in secondary education. Anchored in the contextual integrity framework (Nissenbaum, "Washington Law Review, 79,"…
Descriptors: Parent Attitudes, Student Attitudes, Learning Analytics, Algorithms
Peer reviewed Peer reviewed
Direct linkDirect link
Qian Liu; Tehmina Gladman; Julia Muir; Chen Wang; Rebecca Grainger – SAGE Open, 2023
One apparent challenge associated with learning analytics (LA) has been to promote adoption by university educators. Researchers suggest that a visualization dashboard could serve to help educators use LA to improve learning design (LD) practice. We therefore used an educational design approach to develop a pedagogically useful and easy-to-use LA…
Descriptors: Learning Management Systems, Learning Analytics, Visual Aids, Instructional Design
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Saar, Merike; Rodríguez-Triana, María Jesús; Prieto, Luis P. – Journal of Learning Analytics, 2022
Data-informed decision-making in teachers' practice, now recommended by different teacher inquiry models and policy documents, implies deep practice change for many teachers. However, not much is known about how teachers perceive the different steps that analytics-informed teacher inquiry entails. This paper presents the results of a study into…
Descriptors: Learning Analytics, Evidence Based Practice, Data, Decision Making
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Warren; Sun, Kaiwen; Schaub, Florian; Brooks, Christopher – International Journal of Artificial Intelligence in Education, 2022
Use of university students' educational data for learning analytics has spurred a debate about whether and how to provide students with agency regarding data collection and use. A concern is that students opting out of learning analytics may skew predictive models, in particular if certain student populations disproportionately opt out and biases…
Descriptors: College Students, Learning Analytics, Student Attitudes, Informed Consent
Peer reviewed Peer reviewed
Direct linkDirect link
Rosemary Vellar; Boris Handal; Sean Kearney; Chris Forlin – Issues in Educational Research, 2024
Evidence based decision making is essential for enabling improved student learning. Teacher motivations and beliefs about the types and use of data are critical determinants of decision making. Our research explored the types of data teachers use and consider valuable when measuring improvement in student learning. Findings from 294 teachers from…
Descriptors: Catholic Schools, Elementary Secondary Education, Learning Analytics, Student Needs
Peer reviewed Peer reviewed
Direct linkDirect link
Kasepalu, Reet; Chejara, Pankaj; Prieto, Luis P.; Ley, Tobias – Technology, Knowledge and Learning, 2022
Monitoring and guiding multiple groups of students in face-to-face collaborative work is a demanding task which could possibly be alleviated with the use of a technological assistant in the form of learning analytics. However, it is still unclear whether teachers would indeed trust, understand, and use such analytics in their classroom practice…
Descriptors: Teacher Attitudes, Secondary School Teachers, Technology Uses in Education, Online Systems
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gasevic, Dragan – Journal of Learning Analytics, 2021
The adoption of learning analytics (LA) in complex educational systems is woven into sociocultural and technical challenges that have induced distrust in data and difficulties in scaling LA. This paper presents a study that investigated areas of distrust and threats to trustworthy LA through a series of consultations with teaching staff and…
Descriptors: Learning Analytics, Program Implementation, Trust (Psychology), Higher Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Ladino Nocua, Andrea Catalina; Cruz Gonzalez, Joan Paola; Castiblanco Jimenez, Ivonne Angelica; Gomez Acevedo, Juan Sebastian; Marcolin, Federica; Vezzetti, Enrico – Education Sciences, 2021
Student engagement allows educational institutions to make better decisions regarding teaching methodologies, methods for evaluating the quality of education, and ways to provide timely feedback. Due to the COVID-19 pandemic, identifying cognitive student engagement in distance learning has been a challenge in higher education institutions. In…
Descriptors: Learner Engagement, Cognitive Processes, Metabolism, Physiology
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Lenhart, Cindy; Bouwma-Gearhart, Jana – Education Sciences, 2021
This paper explores the affordances and constraints of STEM faculty members' instructional data-use practices and how they engage students (or not) in reflection around their own learning data. We found faculty used a wide variety of instructional data-use practices. We also found several constraints that influenced their instructional data-use…
Descriptors: STEM Education, Data Use, Reflection, College Faculty
Craig, Scotty D.; Li, Siyuan; Prewitt, Deborah; Morgan, Laurie A.; Schroeder, Noah L. – Advanced Distributed Learning Initiative, 2020
The Science of Learning and Readiness (SoLaR) project seeks to demonstrate to Defense and other Government stakeholders the "art of the possible" for high-quality distributed learning and to create a practical guide for how to infuse such qualities into the broader Department of Defense (DoD) distributed learning ecosystem. This report…
Descriptors: Distance Education, Educational Technology, Learning Analytics, Data Collection