A Framework for Applying the Learning Sciences to MOOC Design
© Copyright © 2021 Gordon and Wiltrout. Evidence-based practices grounded in the learning sciences provide an opportunity for improved learning experiences in traditional in-person, as well as in hybrid and online environments. We advocate specifically that large-scale, online learning experiences,...
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Format: | Article |
Language: | English |
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Frontiers Media SA
2021
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Online Access: | https://hdl.handle.net/1721.1/135276 |
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author | Gordon, DG Wiltrout, ME |
author2 | Massachusetts Institute of Technology. Department of Biology |
author_facet | Massachusetts Institute of Technology. Department of Biology Gordon, DG Wiltrout, ME |
author_sort | Gordon, DG |
collection | MIT |
description | © Copyright © 2021 Gordon and Wiltrout. Evidence-based practices grounded in the learning sciences provide an opportunity for improved learning experiences in traditional in-person, as well as in hybrid and online environments. We advocate specifically that large-scale, online learning experiences, such as Massive Open Online Courses (MOOCs) benefit from applications of the learning sciences. To that end, we present a description of how and why we use specific learning science practices in a biochemistry MOOC with the intention to contribute to the discussion about the quality of online learning experiences and lower the barrier for other practitioners seeking a framework for implementing evidence-based course design. We believe that the application of the learning sciences makes online learning experiences more rigorous and effective, and practitioners should optimize the use of these strategies through clever tests in specific contexts. |
first_indexed | 2024-09-23T08:38:29Z |
format | Article |
id | mit-1721.1/135276 |
institution | Massachusetts Institute of Technology |
language | English |
last_indexed | 2024-09-23T08:38:29Z |
publishDate | 2021 |
publisher | Frontiers Media SA |
record_format | dspace |
spelling | mit-1721.1/1352762023-02-17T20:24:15Z A Framework for Applying the Learning Sciences to MOOC Design Gordon, DG Wiltrout, ME Massachusetts Institute of Technology. Department of Biology © Copyright © 2021 Gordon and Wiltrout. Evidence-based practices grounded in the learning sciences provide an opportunity for improved learning experiences in traditional in-person, as well as in hybrid and online environments. We advocate specifically that large-scale, online learning experiences, such as Massive Open Online Courses (MOOCs) benefit from applications of the learning sciences. To that end, we present a description of how and why we use specific learning science practices in a biochemistry MOOC with the intention to contribute to the discussion about the quality of online learning experiences and lower the barrier for other practitioners seeking a framework for implementing evidence-based course design. We believe that the application of the learning sciences makes online learning experiences more rigorous and effective, and practitioners should optimize the use of these strategies through clever tests in specific contexts. 2021-10-27T20:22:45Z 2021-10-27T20:22:45Z 2021-01-18 2021-03-11T15:53:03Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/135276 en 10.3389/feduc.2020.500481 Frontiers in Education Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Frontiers Media SA Frontiers |
spellingShingle | Gordon, DG Wiltrout, ME A Framework for Applying the Learning Sciences to MOOC Design |
title | A Framework for Applying the Learning Sciences to MOOC Design |
title_full | A Framework for Applying the Learning Sciences to MOOC Design |
title_fullStr | A Framework for Applying the Learning Sciences to MOOC Design |
title_full_unstemmed | A Framework for Applying the Learning Sciences to MOOC Design |
title_short | A Framework for Applying the Learning Sciences to MOOC Design |
title_sort | framework for applying the learning sciences to mooc design |
url | https://hdl.handle.net/1721.1/135276 |
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