ReviewF1000Research2019
The why, when, and how of computing in biology classrooms.
Review in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Galaxy as a gateway to bioinformatics: Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for scRNA-seq.GigaScience · 2025Article
- Design and implementation of an asynchronous online course-based undergraduate research experience (CURE) in computational genomics.PLoS computational biology · 2024Article
- Insight from Biology Program Learning Outcomes: Implications for Teaching, Learning, and Assessment.CBE life sciences education · 2023Article
- Integrating computational skills in undergraduate Microbiology curricula in developing countries.Biology methods & protocols · 2023Article
- Ten simple rules for teaching yourself R.PLoS computational biology · 2022Article
- Undergraduate R Programming Anxiety in Ecology: Persistent Gender Gaps and Coping Strategies.CBE life sciences education · 2022Article
- Opening the Pathway: An Example of Universal Design for Learning as a Guide to Inclusive Teaching Practices.CBE life sciences education · 2022Article
- Data Science in Undergraduate Life Science Education: A Need for Instructor Skills Training.Bioscience · 2021Article
- From panic to pedagogy: Using online active learning to promote inclusive instruction in ecology and evolutionary biology courses and beyond.Ecology and evolution · 2020Article
- Ten quick tips for teaching with participatory live coding.PLoS computational biology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Many biologists are interested in teaching computing skills or using computing in the classroom, despite not being formally trained in these skills themselves. Thus biologists may find themselves researching how to teach these skills, and therefore many individuals are individually attempting to discover resources and methods to do so. Recent years have seen an expansion of new technologies to assist in delivering course content interactively. Educational research provides insights into how learners absorb and process information during interactive learning. In this review, we discuss the value of teaching foundational computing skills to biologists, and strategies and tools to do so. Additionally, we review the literature on teaching practices to support the development of these skills. We pay special attention to meeting the needs of diverse learners, and consider how different ways of delivering course content can be leveraged to provide a more inclusive classroom experience. Our goal is to enable biologists to teach computational skills and use computing in the classroom successfully.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.