Real world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online Course
<h4>Introduction</h4> <p>There is an increased need for improving data science skills of healthcare professionals. Massive Open Online Courses (MOOCs) provide the opportunity to train professionals in a sustainable and cost-effective way. We present a protocol for the design and d...
| Main Authors: | , , , , , |
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| Format: | Journal article |
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BMJ Publishing Group
2018
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| _version_ | 1797090045577920512 |
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| author | Meinert, E Alturkistani, A Car, J Carter, A Wells, G Brindley, D |
| author_facet | Meinert, E Alturkistani, A Car, J Carter, A Wells, G Brindley, D |
| author_sort | Meinert, E |
| collection | OXFORD |
| description | <h4>Introduction</h4> <p>There is an increased need for improving data science skills of healthcare professionals. Massive Open Online Courses (MOOCs) provide the opportunity to train professionals in a sustainable and cost-effective way. We present a protocol for the design and development of a blended MOOC on RWE aimed at improving RWE data science skills. The primary objective is to provide the opportunity to understand the fundamentals of RWE data science and to implement methods for analysing RWD. The blended format of the MOOC will combine the expertise of healthcare professionals joining the course online with the students on-campus. We expect learners to take skills taught in the MOOC and use them to seek new employment or start to initiatives in these domains.</p> <h4>Methods and Analysis</h4> <p>The proposed MOOC will be developed through a blended format using the ADDIE (Analysis, Design, Development, Implementation and Evaluation) instructional design model and following the connectivist-heutagogical learning theories (as a hybrid MOOC). The target learners will include postgraduate students and professionals working in the health-related roles with interest in data science. An evaluation of the MOOC will be performed to assess the MOOCs success in meeting its intended outcomes and to improve future iterations of the course.</p> <h4>Ethics and dissemination</h4> <p>The education course design protocol was approved by EIT Health (Grant 18654) as part of the EIT Health CAMPUS Deferred Call for Innovative Education 2018. Results will be published in a peer-reviewed journal.</p> |
| first_indexed | 2024-03-07T03:12:50Z |
| format | Journal article |
| id | oxford-uuid:b4c9046a-621d-41fd-9214-057cda22db74 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T03:12:50Z |
| publishDate | 2018 |
| publisher | BMJ Publishing Group |
| record_format | dspace |
| spelling | oxford-uuid:b4c9046a-621d-41fd-9214-057cda22db742022-03-27T04:28:38ZReal world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online CourseJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:b4c9046a-621d-41fd-9214-057cda22db74Symplectic Elements at OxfordBMJ Publishing Group2018Meinert, EAlturkistani, ACar, JCarter, AWells, GBrindley, D <h4>Introduction</h4> <p>There is an increased need for improving data science skills of healthcare professionals. Massive Open Online Courses (MOOCs) provide the opportunity to train professionals in a sustainable and cost-effective way. We present a protocol for the design and development of a blended MOOC on RWE aimed at improving RWE data science skills. The primary objective is to provide the opportunity to understand the fundamentals of RWE data science and to implement methods for analysing RWD. The blended format of the MOOC will combine the expertise of healthcare professionals joining the course online with the students on-campus. We expect learners to take skills taught in the MOOC and use them to seek new employment or start to initiatives in these domains.</p> <h4>Methods and Analysis</h4> <p>The proposed MOOC will be developed through a blended format using the ADDIE (Analysis, Design, Development, Implementation and Evaluation) instructional design model and following the connectivist-heutagogical learning theories (as a hybrid MOOC). The target learners will include postgraduate students and professionals working in the health-related roles with interest in data science. An evaluation of the MOOC will be performed to assess the MOOCs success in meeting its intended outcomes and to improve future iterations of the course.</p> <h4>Ethics and dissemination</h4> <p>The education course design protocol was approved by EIT Health (Grant 18654) as part of the EIT Health CAMPUS Deferred Call for Innovative Education 2018. Results will be published in a peer-reviewed journal.</p> |
| spellingShingle | Meinert, E Alturkistani, A Car, J Carter, A Wells, G Brindley, D Real world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online Course |
| title | Real world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online Course |
| title_full | Real world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online Course |
| title_fullStr | Real world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online Course |
| title_full_unstemmed | Real world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online Course |
| title_short | Real world evidence for postgraduate students and professionals in healthcare: Protocol for the design of a blended Massive Open Online Course |
| title_sort | real world evidence for postgraduate students and professionals in healthcare protocol for the design of a blended massive open online course |
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