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Innovative Learning Environments in STEM Higher Education: Opportunities, Challenges, and Looking Forward /

Innovative Learning Environments in STEM Higher Education: Opportunities, Challenges, and Looking Forward /
Catalogue Information
Field name Details
Dewey Class 300.727
Title Innovative Learning Environments in STEM Higher Education ([EBook] :) : Opportunities, Challenges, and Looking Forward / / edited by Jungwoo Ryoo, Kurt Winkelmann.
Added Personal Name Ryoo, Jungwoo
Winkelmann, Kurt
Other name(s) SpringerLink (Online service)
Edition statement 1st ed. 2021.
Publication Cham : : Springer International Publishing : : Imprint: Springer, , 2021.
Physical Details XV, 137 p. 8 illus., 7 illus. in color. : online resource.
Series SpringerBriefs in Statistics 2191-5458
ISBN 9783030589486
Summary Note 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.:
Contents note 1. Introduction -- 2. X-FILEs Vision for personalized and Adaptive Learning -- 3. X-FILEs Vision for Multi-modal Learning Formats -- 4. X-FILEs Vision for Extended/Cross Reality (XR) -- 5. X-FILEs Vision for Artificial Intelligence (AI) and Machine Learning (ML) -- 6. Cross-Cutting Concerns -- 7. Epilogue.
Mode of acces to digital resource Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site https://doi.org/10.1007/978-3-030-58948-6
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