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Joseph T. Wong; Edward Chen; Natalie Au-Yeung; Bella S. Lerner; Lindsey Engle Richland – Education and Information Technologies, 2024
Traditionally, learning among young students has taken place within structured, physical classroom settings. However, the emergence of distance learning has introduced a diverse range of learning methods, including online, hybrid, and blended approaches. When the COVID-19 pandemic led to extended delays in in-person instruction, use of educational…
Descriptors: Electronic Learning, Learning Experience, Attention Span, Interests
Renick, Jennifer; Reich, Stephanie M. – Middle School Journal, 2023
The COVID-19 pandemic caused schools to shift to virtual or hybrid instruction, thrusting young adolescents into a very different educational environment. Stage-environment fit theory outlines ways in which educational contexts may, or may not, meet the developmental needs of young adolescents. Yet little is known about how virtual environments…
Descriptors: Middle School Students, Early Adolescents, Adolescent Development, Needs
Larson, Lotta C. – Reading Teacher, 2015
This article examines how sixth-grade students navigated and perceived a combined e-book and audiobook reading experience using Kindle Fires. While audiobooks and e-books are not new, little is known about students' use and perceptions of the combination of these two media, as the ability to synchronize audio contents with digital texts is rather…
Descriptors: Audio Books, Electronic Learning, Electronic Publishing, Handheld Devices
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