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Hilbert, Sven; Coors, Stefan; Kraus, Elisabeth; Bischl, Bernd; Lindl, Alfred; Frei, Mario; Wild, Johannes; Krauss, Stefan; Goretzko, David; Stachl, Clemens – Review of Education, 2021
Machine learning (ML) provides a powerful framework for the analysis of high-dimensional datasets by modelling complex relationships, often encountered in modern data with many variables, cases and potentially non-linear effects. The impact of ML methods on research and practical applications in the educational sciences is still limited, but…
Descriptors: Artificial Intelligence, Online Courses, Educational Research, Data Analysis
National Forum on Education Statistics, 2015
When properly employed, technology may enhance and support learning opportunities available to any student, at any location, and at any time. Determining which instructional and delivery methods are best for a specific individual, group of students, community, or circumstance demands that high-quality data be available to students, parents,…
Descriptors: Elementary Secondary Education, Educational Technology, Technology Uses in Education, Data Collection
Means, Barbara; Bakia, Marianne; Murphy, Robert – Routledge, Taylor & Francis Group, 2014
At a time when more and more of what people learn both in formal courses and in everyday life is mediated by technology, "Learning Online" provides a much-needed guide to different forms and applications of online learning. This book describes how online learning is being used in both K-12 and higher education settings as well as in…
Descriptors: Electronic Learning, Educational Research, Elementary Secondary Education, Higher Education
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Sahin, Ismail; Shelley, Mack – Educational Technology & Society, 2008
In the current study, the Distance Education Student Satisfaction Model, estimated as a structural equation model, is proposed to understand better what predicts student satisfaction from online learning environments. In the present study, the following variables are employed based on the Technology Acceptance Model (TAM) (Davis, Bagozzi, &…
Descriptors: Undergraduate Students, Student Attitudes, Distance Education, Online Courses
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McPherson, Maggie; Nunes, Miguel Baptista – International Journal of Educational Management, 2006
Purpose: The purpose of this paper is to report on a research project that identified organisational critical success factors (CSFs) for e-learning implementation in higher education (HE). These CSFs can be used as a theoretical foundation upon which to base decision-making and strategic thinking about e-learning. Design/methodology/approach: The…
Descriptors: Research Methodology, Focus Groups, Data Analysis, Success
Watson, John; Gemin, Butch; Ryan, Jennifer; Wicks, Matthew – Evergreen Education Group, 2009
"Keeping Pace" has several goals. First, it strives to add to the body of knowledge about online education policy and practice and make recommendations for advances. Second, it serves as a reference source for information about programs and policies across the country, both for policymakers and practitioners who are new to online…
Descriptors: Electronic Learning, Schools, Elementary Secondary Education, State Schools
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Friend, Linda – Journal of Academic Librarianship, 1985
Describes program of end user training designed to teach students rudiments of searching using Bibliographic Retrieval Service/After Dark. Results of participant responses to post-search questionnaire are reported, including suggestions of what to cover in basic training, problems of end users, and developing role of online searcher as consultant.…
Descriptors: College Libraries, Databases, Graduate Students, Higher Education