Assessing an effective undergraduate module teaching applied bioinformatics to biology students.

: Applied bioinformatics skills are becoming ever more indispensable for biologists, yet incorporation of these skills into the undergraduate biology curriculum is lagging behind, in part due to a lack of instructors willing and able to teach basic bioinformatics in classes that don't specifically focus on quantitative skill development, such as statistics or computer sciences. To help undergraduate course instructors who themselves did not learn bioinformatics as part of their own education and are hesitant to plunge into teaching big data analysis, a module was developed that is written in plain-enough language, using publicly available computing tools and data, to allow novice instructors to teach next-generation sequence analysis to upper-level undergraduate students. To determine if the module allowed students to develop a better understanding of and appreciation for applied bioinformatics, various tools were developed and employed to assess the impact of the module. This article describes both the module and its assessment. Students found the activity valuable for their education and, in focus group discussions, emphasized that they saw a need for more and earlier instruction of big data analysis as part of the undergraduate biology curriculum.

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PID https://www.doi.org/10.1371/journal.pcbi.1005872
PID pmc:PMC5764237
PID pmid:29324777
URL https://doaj.org/toc/1553-734X
URL http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005872
URL https://doaj.org/toc/1553-7358
URL https://doi.org/10.1371/journal.pcbi.1005872
URL http://dx.plos.org/10.1371/journal.pcbi.1005872
URL http://dx.doi.org/10.1371/journal.pcbi.1005872
URL https://dblp.uni-trier.de/db/journals/ploscb/ploscb14.html#Madlung18
URL https://core.ac.uk/display/149303467
URL http://europepmc.org/articles/PMC5764237
URL https://academic.microsoft.com/#/detail/2783454336
URL https://dx.plos.org/10.1371/journal.pcbi.1005872
URL http://europepmc.org/articles/PMC5764237?pdf=render
URL https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005872&type=printable
URL https://www.ncbi.nlm.nih.gov/pubmed/29324777
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Access Right Open Access
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Author Andreas Madlung, 0000-0003-3563-5797
Contributor Ouellette, Francis
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Collected From PubMed Central; Datacite; UnpayWall; DOAJ-Articles; Crossref; Microsoft Academic Graph
Hosted By Europe PubMed Central; PLoS Computational Biology
Journal PLoS Computational Biology, ,
Publication Date 2018-01-11
Publisher Public Library of Science (PLoS)
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Language English
Resource Type Other literature type; Article
keyword keywords.Ecology, Evolution, Behavior and Systematics
system:type publication
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::5db586bd92536374f0c40dba9baa4c09
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Last Updated 21 December 2020, 18:07 (CET)
Created 21 December 2020, 18:07 (CET)