Ten quick tips for teaching programming

Brown, Neil C. C.; Wilson, Greg

doi:10.1371/journal.pcbi.1006023

Cited by 106Teaching and Learning ProgrammingInnovative Teaching MethodsEducational Robotics and Engineering

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Ten quick tips for teaching programming

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Brown, Neil C. C., Wilson, Greg·2018·PLOS Computational Biology

DOI 10.1371/journal.pcbi.1006023PMC PMC5886386

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Abstract

Research from educational psychology suggests that teaching and learning are subject-specific activities: learning programming has a different set of challenges and techniques than learning physics or learning to read and write. Computing is a younger discipline than mathematics, physics, or biology, and while there have been correspondingly fewer studies of how best to teach it, there is a growing body of evidence about what works and what doesn’t. This paper presents ten quick tips that should be the foundation of any teaching of programming, whether formal or informal.

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Live-coding by the instructor creates a shared experience for all participants and encourages peer learning by providing an opportunity for question and answer during guided activities.
“This strategy creates a shared experience for all participants, and encourages peer learning by providing an opportunity for question and answer during guided activities (Brown & Wilson, 2018; McClatchy et al., 2020).”
From Student‐led workshops: Filling skills gaps in computational research for life scientists (2021) · cites this paper as Brown & Wilson, 2018
Tip 3: Use live coding (page not provided) says instructors create programs in front of learners and can respond to their questions. The paper discusses learning from peers in Tip 2: Use peer instruction, but does not say that live coding itself encourages peer learning through question-and-answer during guided activities. A shared experience is plausible from the described practice, but is not stated as an outcome. (LLM, conf=0.84)
Experimental — accuracy not yet measured
This strategy can improve application of new skills to individual research tasks in the future.
“This strategy can improve application of new skills to individual research tasks in the future (Brown & Wilson, 2018).”
From Student‐led workshops: Filling skills gaps in computational research for life scientists (2021) · cites this paper as Brown & Wilson, 2018
Tip 6 (‘Use worked examples with labelled subgoals’; page unavailable) says learners can apply subgoal labels to future tasks they attempt themselves, supporting future independent application. It does not specifically address applying new skills to individual research tasks, so that setting goes beyond the source. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Online delivery, especially of complex technical topics like bioinformatics, can lead to cognitive overload that impedes participant learning.
“Second, online delivery, especially of complex technical topics like bioinformatics, can lead to cognitive overload that impedes participant learning (Brown & Wilson, 2018).”
From Student‐led workshops: Filling skills gaps in computational research for life scientists (2021) · cites this paper as Brown & Wilson, 2018
Tip 10 (“Don’t just code”; page unavailable) says that programming examples can overwhelm novices and that breaking problems into single-concept pieces reduces cognitive load. It does not attribute that overload to online delivery or specifically discuss bioinformatics instruction. (LLM, conf=0.87)
Experimental — accuracy not yet measured

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Authors: Brown, N. C. C., & Wilson, G.
Affiliations: King's College London (GB)
Corresponding author: Wilson, Greg
ORCID: Brown, Neil C. C.
Wilson, Greg
Venue: PLOS Computational Biology
Publisher: Public Library of Science (PLoS)
Published: 2018-04-05
Volume: 14
Issue: 4
Pages: e1006023
ISSN: 1553-734X (ISSN-L)
1553-7358
DOI: 10.1371/journal.pcbi.1006023
PMC: PMC5886386
OpenAlex: W2795628086
Cited by: 89
References: 31
Citations by year: 2026: 5 · 2025: 7 · 2024: 10 · 2023: 15 · 2022: 16 · 2021: 15 · 2020: 9 · 2019: 11 · 2018: 1
FWCI: 11.38
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: PLoS Computational Biology (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Research Portal (King's College London) (submittedVersion, cc-by)
Topics: Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
Social Sciences › Education › Innovative Teaching Methods
Social Sciences › Education › Educational Robotics and Engineering
Keywords: programming education, computer science education, educational psychology, informal learning, best practices in teaching
MeSH terms: Humans, Programming Languages, Software, Computational Biology

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