The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement

The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This i...

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Autores principales:	Robert Bodily, Rob Nyland, David Wiley
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2017
Materias:	OER open educational resources course evaluation learning analytics continuous improvement The RISE Framework Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/cbd93f5b07334da383996ddcd6e86089
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spelling	oai:doaj.org-article:cbd93f5b07334da383996ddcd6e860892021-12-02T19:20:54ZThe RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement10.19173/irrodl.v18i2.29521492-3831https://doaj.org/article/cbd93f5b07334da383996ddcd6e860892017-04-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/2952https://doaj.org/toc/1492-3831The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This is particularly useful in OER contexts where the copyright permissions of resources allow for remixing, editing, and improving content. The RISE Framework presents a scatterplot with resource usage on the x-axis and grade on the assessments associated with that resource on the y-axis. This scatterplot is broken down into four different quadrants (the mean of each variable being the origin) to find resources that are candidates for improvement. Resources that reside deep within their respective quadrant (farthest from the origin) should be further analyzed for continuous course improvement. We present a case study applying our framework with an Introduction to Business course. Aggregate resource use data was collected from Google Analytics and aggregate assessment data was collected from an online assessment system. Using the RISE Framework, we successfully identified resources, time periods, and modules in the course that should be further evaluated for improvement. Robert BodilyRob NylandDavid WileyAthabasca University PressarticleOERopen educational resourcescourse evaluationlearning analyticscontinuous improvementThe RISE FrameworkSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 18, Iss 2 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	OER open educational resources course evaluation learning analytics continuous improvement The RISE Framework Special aspects of education LC8-6691
spellingShingle	OER open educational resources course evaluation learning analytics continuous improvement The RISE Framework Special aspects of education LC8-6691 Robert Bodily Rob Nyland David Wiley The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement
description	The RISE (Resource Inspection, Selection, and Enhancement) Framework is a framework supporting the continuous improvement of open educational resources (OER). The framework is an automated process that identifies learning resources that should be evaluated and either eliminated or improved. This is particularly useful in OER contexts where the copyright permissions of resources allow for remixing, editing, and improving content. The RISE Framework presents a scatterplot with resource usage on the x-axis and grade on the assessments associated with that resource on the y-axis. This scatterplot is broken down into four different quadrants (the mean of each variable being the origin) to find resources that are candidates for improvement. Resources that reside deep within their respective quadrant (farthest from the origin) should be further analyzed for continuous course improvement. We present a case study applying our framework with an Introduction to Business course. Aggregate resource use data was collected from Google Analytics and aggregate assessment data was collected from an online assessment system. Using the RISE Framework, we successfully identified resources, time periods, and modules in the course that should be further evaluated for improvement.
format	article
author	Robert Bodily Rob Nyland David Wiley
author_facet	Robert Bodily Rob Nyland David Wiley
author_sort	Robert Bodily
title	The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement
title_short	The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement
title_full	The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement
title_fullStr	The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement
title_full_unstemmed	The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement
title_sort	rise framework: using learning analytics to automatically identify open educational resources for continuous improvement
publisher	Athabasca University Press
publishDate	2017
url	https://doaj.org/article/cbd93f5b07334da383996ddcd6e86089
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The RISE Framework: Using Learning Analytics to Automatically Identify Open Educational Resources for Continuous Improvement

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