Innovative Learning Environments in STEM Higher Education
Opportunities, Challenges, and Looking Forward
Contributor(s)
Ryoo, Jungwoo (editor)
Winkelmann, Kurt (editor)
Language
EnglishAbstract
As explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education.
Keywords
Statistics for Social Sciences, Humanities, Law; Machine Learning; Statistics and Computing/Statistics Programs; Learning & Instruction; Knowledge based Systems; Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy; Statistics and Computing; Education; Innovative Learning Environments; ILEs; Science, Technology, Engineering, and Math; STEM; virtual reality; VR; augmented reality; mixed reality; cross reality; extended reality; artificial intelligence; AI; adaptive learning; personalized learning; higher education; multimodal learning; mobile learning; Open Access; Social research & statistics; Mathematical & statistical software; Teaching skills & techniques; Cognition & cognitive psychology; Expert systems / knowledge-based systemsDOI
10.1007/978-3-030-58948-6ISBN
9783030589486, 9783030589486Publisher
Springer NaturePublisher website
https://www.springernature.com/gp/products/booksPublication date and place
2021Series
SpringerBriefs in Statistics,Classification
Social research and statistics
Machine learning
Mathematical and statistical software
Teaching skills and techniques
Expert systems / knowledge-based systems