The Future of Social Learning: A Novel Approach to Connectivism

Simple item page
dc.contributor.authorSmidt, Holm
dc.contributor.authorThornton, Matsu
dc.contributor.authorAbhari, Kaveh
dc.date.accessioned2016-12-29T00:51:18Z
dc.date.available2016-12-29T00:51:18Z
dc.date.issued2017-01-04
dc.description.abstractThe primary goal of this paper is to operationalize the connectivism approach into a new learning model with additions from problem-based and contextual learning that can be effectively implemented together, to improve socioeconomically diverse learners’ educational outcomes (attitude and persistence) in STEM (Science, Technology, Education and Mathematics) areas. We model this approach through the development and demonstration of an innovative, evidence-based, and scalable how-to-learn program that leverages connectivism principles and technology. This paper uses the case of energy education to provide contextual relevancy and prepare learners for the high demand jobs of the future. The new model is developed within the context of Internet of Things (IoT), where students have a unique opportunity to participate in a real-world application of an IoT system for green energy governance.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.256
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41410
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectConnectivism
dc.subjectContextual learning
dc.subjectIoT Energy education
dc.subjectProblem-based learning
dc.subjectSocial learning
dc.titleThe Future of Social Learning: A Novel Approach to Connectivism
dc.typeConference Paper
dc.type.dcmiText

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
paper0261.pdf
Size:
1.8 MB
Format:
Adobe Portable Document Format
Download

Collections

Learning within Digital and Social Media Minitrack