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Protocol for a mixed-methods evaluation of a massive open online course on real world evidence

INTRODUCTION: Increasing number of Massive Open Online Courses (MOOCs) are being used to train learners at scale in various healthcare-related skills. However, many challenges in course delivery require further understanding, for example, factors exploring the reasons for high MOOC dropout rates, re...

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Autores principales: Meinert, Edward, Alturkistani, Abrar, Brindley, David, Carter, Alison, Wells, Glenn, Car, Josip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091905/
https://www.ncbi.nlm.nih.gov/pubmed/30104321
http://dx.doi.org/10.1136/bmjopen-2018-025188
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author Meinert, Edward
Alturkistani, Abrar
Brindley, David
Carter, Alison
Wells, Glenn
Car, Josip
author_facet Meinert, Edward
Alturkistani, Abrar
Brindley, David
Carter, Alison
Wells, Glenn
Car, Josip
author_sort Meinert, Edward
collection PubMed
description INTRODUCTION: Increasing number of Massive Open Online Courses (MOOCs) are being used to train learners at scale in various healthcare-related skills. However, many challenges in course delivery require further understanding, for example, factors exploring the reasons for high MOOC dropout rates, recorded low social interaction between learners and the lack of understanding of the impact of a course facilitators’ presence in course engagement. There is a need to generate further evidence to explore these detriments to MOOC course delivery to enable enhanced course learning design. The proposed mixed-methods evaluation of the MOOC was determined based on the MOOC’s aims and objectives and the methodological approaches used to evaluate this type of a course. The MOOC evaluation will help appraise the effectiveness of the MOOC in delivering its intended objectives. This protocol aims to describe the design of a study evaluating learners knowledge, skills and attitudes in a MOOCs about data science for healthcare. METHODS AND ANALYSIS: Study participants will be recruited from learners who have registered for the MOOC. On registration, learners will be given an opportunity to opt into the study and complete informed consent. Following completion of the course, study participants will be contacted to complete semistructured interviews. Interviews will be transcribed and coded using thematic analysis, with data analysed using two evaluation models: (1) the reach, effectiveness, adoption, implementation, maintenance framework and the (2) Kirkpatrick model drawing data from pre and post-course surveys and post-MOOC semi-structured interviews. The primary goal of the evaluation is to appraise participants' knowledge, skills and attitude after taking the MOOC. ETHICS AND DISSEMINATION: Ethics approval for this study was obtained from Imperial College London through the Education Ethics Review Process (EERP) (EERP1617-030). A summary of the research findings will be reported through a peer-reviewed journal and will be presented at an international conference.
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spelling pubmed-60919052018-08-17 Protocol for a mixed-methods evaluation of a massive open online course on real world evidence Meinert, Edward Alturkistani, Abrar Brindley, David Carter, Alison Wells, Glenn Car, Josip BMJ Open Medical Education and Training INTRODUCTION: Increasing number of Massive Open Online Courses (MOOCs) are being used to train learners at scale in various healthcare-related skills. However, many challenges in course delivery require further understanding, for example, factors exploring the reasons for high MOOC dropout rates, recorded low social interaction between learners and the lack of understanding of the impact of a course facilitators’ presence in course engagement. There is a need to generate further evidence to explore these detriments to MOOC course delivery to enable enhanced course learning design. The proposed mixed-methods evaluation of the MOOC was determined based on the MOOC’s aims and objectives and the methodological approaches used to evaluate this type of a course. The MOOC evaluation will help appraise the effectiveness of the MOOC in delivering its intended objectives. This protocol aims to describe the design of a study evaluating learners knowledge, skills and attitudes in a MOOCs about data science for healthcare. METHODS AND ANALYSIS: Study participants will be recruited from learners who have registered for the MOOC. On registration, learners will be given an opportunity to opt into the study and complete informed consent. Following completion of the course, study participants will be contacted to complete semistructured interviews. Interviews will be transcribed and coded using thematic analysis, with data analysed using two evaluation models: (1) the reach, effectiveness, adoption, implementation, maintenance framework and the (2) Kirkpatrick model drawing data from pre and post-course surveys and post-MOOC semi-structured interviews. The primary goal of the evaluation is to appraise participants' knowledge, skills and attitude after taking the MOOC. ETHICS AND DISSEMINATION: Ethics approval for this study was obtained from Imperial College London through the Education Ethics Review Process (EERP) (EERP1617-030). A summary of the research findings will be reported through a peer-reviewed journal and will be presented at an international conference. BMJ Publishing Group 2018-08-13 /pmc/articles/PMC6091905/ /pubmed/30104321 http://dx.doi.org/10.1136/bmjopen-2018-025188 Text en © Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Medical Education and Training
Meinert, Edward
Alturkistani, Abrar
Brindley, David
Carter, Alison
Wells, Glenn
Car, Josip
Protocol for a mixed-methods evaluation of a massive open online course on real world evidence
title Protocol for a mixed-methods evaluation of a massive open online course on real world evidence
title_full Protocol for a mixed-methods evaluation of a massive open online course on real world evidence
title_fullStr Protocol for a mixed-methods evaluation of a massive open online course on real world evidence
title_full_unstemmed Protocol for a mixed-methods evaluation of a massive open online course on real world evidence
title_short Protocol for a mixed-methods evaluation of a massive open online course on real world evidence
title_sort protocol for a mixed-methods evaluation of a massive open online course on real world evidence
topic Medical Education and Training
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6091905/
https://www.ncbi.nlm.nih.gov/pubmed/30104321
http://dx.doi.org/10.1136/bmjopen-2018-025188
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