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Winne, Philip H.; Nesbit, John C.; Popowich, Fred – Technology, Knowledge and Learning, 2017
A bottleneck in gathering big data about learning is instrumentation designed to record data about processes students use to learn and information on which those processes operate. The software system nStudy fills this gap. nStudy is an extension to the Chrome web browser plus a server side database for logged trace data plus peripheral modules…
Descriptors: Data Collection, Research Methodology, Learning Processes, Computer Software
Lee, Jong-Ki – Journal of Instructional Pedagogies, 2009
An e-learner's characteristics are very important variables with regards to educational performance and the e-learning environment. This study suggests a research model, based on a successful e-learning model, which presents the relationship between e-learner's self-regulated learning strategies and the quality perception in LMS (learning…
Descriptors: Electronic Learning, Learning Strategies, Self Control, Satisfaction
Strang, Kenneth David – International Journal of Virtual and Personal Learning Environments, 2011
Virtual learning is a popular teaching modality, and it has been reported in research that there is no significant difference in academic outcome as compared with face-to-face courses. Not all researchers agree with this assertion and some claim it is more difficult to teach math-oriented subjects online. Given that educational psychology theories…
Descriptors: Constructivism (Learning), Online Courses, Asynchronous Communication, Synchronous Communication
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection

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