Ten simple rules for collaborative lesson development

Devenyi, Gabriel A.; Emonet, Rémi; Harris, Rayna M.; Hertweck, Kate L.; Irving, Damien; Milligan, Ian; Wilson, Greg

doi:10.1371/journal.pcbi.1005963

Cited by 15 publications

(10 citation statements)

References 4 publications

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“…What is far less common is collaborative lesson construction, i.e., people taking material, improving it, and then offering their changes back to the community. This model has served the open source software community well, and as [9] describes, it works equally well for lessons—provided that materials are designed to make fine-grained collaboration easy. Unfortunately, widely-used systems like Git are designed to handle text files and struggle with structured document formats like Microsoft Word or PowerPoint.…”

Section: Resultsmentioning

confidence: 99%

Ten quick tips for creating an effective lesson

Wilson¹

2019

PLoS Comput Biol

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Section: Resultsmentioning

confidence: 99%

Ten quick tips for creating an effective lesson

Wilson¹

2019

PLoS Comput Biol

Self Cite

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“…While OERs are well known for reducing the costs of educational materials and permitting customization, 9,10 their use and development in a new field such as bioinformatics presents several challenges. Foremost, up-todate, reliable resources are not always readily available.…”

Section: Challenges To the Development And Incorporation Of Educatimentioning

confidence: 99%

Incubators: Building community networks and developing open educational resources to integrate bioinformatics into life science education

Ryder

Morgan

Sierk

et al. 2020

Biochem Molecular Bio Educ

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While it is essential for life science students to be trained in modern techniques and approaches, rapidly developing, interdisciplinary fields such as bioinformatics present distinct challenges to undergraduate educators. In particular, many educators lack training in new fields, and high-quality teaching and learning materials may be sparse. To address this challenge with respect to bioinformatics, the Network for the Integration of Bioinformatics into Life Science Education (NIBLSE), in partnership with Quantitative Undergraduate Biology Education and Synthesis (QUBES), developed incubators, a novel collaborative process for the development of open educational resources (OER). Incubators are short-term, online communities that refine unpublished teaching lessons into more polished and widely usable learning resources. The resulting products are published and made freely available in the NIBLSE Resource Collection, providing recognition of scholarly work by incubator participants. In

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“…One possible way to help coordinate education efforts may be by using the tools of scientific reproducibility that have already become a staple for data science (e.g., open code repositories like GitHub and the Open Science Framework). By openly sharing these materials, organizers of new efforts can see what topics have been covered by other efforts and prevent the unnecessary duplication of efforts by reusing existing materials as appropriate [18,22,33]. Efforts that have generated a stable repository of education materials reported this to be a major achievement and benefit for future sessions.…”

Section: Suggestions For Ad Hoc Education Effortsmentioning

confidence: 99%

“…Other work has addressed the institutional change of data science education [11] and how to design formal efforts or courses related to computational skills [10,21]. Prior work has also considered lessons learned from individual event formats, such as short courses or workshops [8,19,20,[22][23][24], mentor-mentee relationships [25], and summer programs [26]. However, to our knowledge, no study has yet looked holistically at the benefits that different extracurricular formats can provide and has extracted lessons learned for future efforts and novel formats.…”

Section: Introductionmentioning

confidence: 99%

Ad hoc efforts for advancing data science education

2020

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With increasing demand for training in data science, extracurricular or "ad hoc" education efforts have emerged to help individuals acquire relevant skills and expertise. Although extracurricular efforts already exist for many computationally intensive disciplines, their support of data science education has significantly helped in coping with the speed of innovation in data science practice and formal curricula. While the proliferation of ad hoc efforts is an indication of their popularity, less has been documented about the needs that they are designed to meet, the limitations that they face, and practical suggestions for holding successful efforts. To holistically understand the role of different ad hoc formats for data science, we surveyed organizers of ad hoc data science education efforts to understand how organizers perceived the events to have gone-including areas of strength and areas requiring growth. We also gathered recommendations from these past events for future organizers. Our results suggest that the perceived benefits of ad hoc efforts go beyond developing technical skills and may provide continued benefit in conjunction with formal curricula, which warrants further investigation. As increasing numbers of researchers from computational fields with a history of complex data become involved with ad hoc efforts to share their skills, the lessons learned that we extract from the surveys will provide concrete suggestions for the practitioner-leaders interested in creating, improving, and sustaining future efforts.

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Ten simple rules for collaborative lesson development

Abstract: The collaborative development methods pioneered by the open source software community offer a way to create lessons that are open, accessible, and sustainable. This paper presents ten simple rules for doing this drawn from our experience with several successful projects.

Cited by 15 publications

References 4 publications

Ten quick tips for creating an effective lesson

Ten quick tips for creating an effective lesson

Incubators: Building community networks and developing open educational resources to integrate bioinformatics into life science education

Ad hoc efforts for advancing data science education

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