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dc.contributor.authorDoudesis, Dimitrios
dc.contributor.authorManataki, Areti
dc.date.accessioned2022-12-20T00:41:18Z
dc.date.available2022-12-20T00:41:18Z
dc.date.issued2022-03
dc.identifier277182463
dc.identifierb4cca7cb-e2cb-4a5a-a180-eb6035b7f216
dc.identifier85122708664
dc.identifier000788794900007
dc.identifier.citationDoudesis , D & Manataki , A 2022 , ' Data science in undergraduate medicine : course overview and student perspectives ' , International Journal of Medical Informatics , vol. 159 , 104668 . https://doi.org/10.1016/j.ijmedinf.2021.104668en
dc.identifier.issn1386-5056
dc.identifier.otherRIS: urn:05E2150D9EFE51A694345DDAC7D3F2E8
dc.identifier.otherORCID: /0000-0003-3698-8535/work/105318670
dc.identifier.urihttps://hdl.handle.net/10023/26627
dc.descriptionThe authors would like to thank the Usher Institute at the University of Edinburgh for funding this work through an Usher Education Development Grant.en
dc.description.abstractBackground  Despite the growing interest in health data science education, it is not embedded in undergraduate medical curricula and little is known about best teaching practices. This paper presents a highly innovative course in a UK university that introduces undergraduate medical students to data science. It also discusses a study on student perspectives on the learning and teaching of health data science.  Methods  The pedagogical design elements of the Data Science in Medicine course are discussed, along with its syllabus, assessment methodology and flipped classroom delivery. The course has been offered to approximately 630 students over three years. Student perspectives were investigated through three focus groups with the participation of 19 students across different study years in medicine. An experiment was conducted regarding instructor-led vs. video-based modalities of online programming labs, with the participation of 8 students.  Results  The course has led to improved data competency among medical students and to a positive change in their opinions about data science. Motivating the course and showing relevance to clinical practice was one of the biggest challenges. Statistics was perceived by focus group participants as an essential data skill. Including data science in the medical curriculum was perceived as important by Year 1 students, while opinions varied between Year 4/5 participants. Video-based online labs were preferred over instructor-led online labs, and they were found to be more useful and enjoyable, without leading to any significant difference in academic performance.  Conclusions  Teaching data science to undergraduate medicine students is highly desirable and feasible. We recommend including statistics in the curriculum and practical skill development through simple and clinically-relevant data science tasks, supported through video-based online labs. Further reporting on similar courses is needed, as well as larger-scale studies on student perspectives.
dc.format.extent7
dc.format.extent1953549
dc.language.isoeng
dc.relation.ispartofInternational Journal of Medical Informaticsen
dc.subjectData scienceen
dc.subjectHealthen
dc.subjectMedicineen
dc.subjectEducationen
dc.subjectTrainingen
dc.subjectHealth informaticsen
dc.subjectLB2300 Higher Educationen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectR Medicineen
dc.subjectZA4450 Databasesen
dc.subjectDASen
dc.subjectACen
dc.subject.lccLB2300en
dc.subject.lccQA75en
dc.subject.lccRen
dc.subject.lccZA4450en
dc.titleData science in undergraduate medicine : course overview and student perspectivesen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1016/j.ijmedinf.2021.104668
dc.description.statusPeer revieweden
dc.date.embargoedUntil2022-12-20


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