PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub

A Ramezani; Stephen Bradley

doi:10.1145/3633053.3633062

PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub

A Ramezani
, Stephen Bradley

School of Arts & Humanities

Durham University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

We explore the use of the PRIMM methodology (Predict, Run, Investigate, Modify, Make) within a higher education introductory programming setting, particularly focusing on the three first three steps. Formative prediction questions on the effects of changes to HTML, CSS or JavaScript code are constructed by students using PeerWise system, based on their own investigation. Authenticity of the task is enhanced by presenting the peer prediction questions as pull requests to a GitHub repository, mirroring the code review process followed by professionals working within software development teams. We report on student engagement with the formative practical exercises and analyse the content of the questions they asked.

Original language	English
Title of host publication	CEP '24: Proceedings of the 8th Conference on Computing Education Practice
Number of pages	4
ISBN (Electronic)	9798400709326
DOIs	https://doi.org/10.1145/3633053.3633062
Publication status	Published online - 5 Jan 2024
Event	CEP '24: Computing Education Practice - Durham, United Kingdom Duration: 5 Jan 2024 → …

Conference

Conference	CEP '24: Computing Education Practice
Country/Territory	United Kingdom
City	Durham
Period	5/01/24 → …

Access to Document

10.1145/3633053.3633062

Automated customer management with sequential pattern mining of journey data logs
Ramezani, A. (Author), Charles, D. (Supervisor), Scotney, B. (Supervisor) & Hawe, G. (Supervisor), Jan 2026
Student thesis: Doctoral Thesis

Cite this

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title = "PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub",

abstract = "We explore the use of the PRIMM methodology (Predict, Run, Investigate, Modify, Make) within a higher education introductory programming setting, particularly focusing on the three first three steps. Formative prediction questions on the effects of changes to HTML, CSS or JavaScript code are constructed by students using PeerWise system, based on their own investigation. Authenticity of the task is enhanced by presenting the peer prediction questions as pull requests to a GitHub repository, mirroring the code review process followed by professionals working within software development teams. We report on student engagement with the formative practical exercises and analyse the content of the questions they asked.",

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AU - Bradley, Stephen

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N2 - We explore the use of the PRIMM methodology (Predict, Run, Investigate, Modify, Make) within a higher education introductory programming setting, particularly focusing on the three first three steps. Formative prediction questions on the effects of changes to HTML, CSS or JavaScript code are constructed by students using PeerWise system, based on their own investigation. Authenticity of the task is enhanced by presenting the peer prediction questions as pull requests to a GitHub repository, mirroring the code review process followed by professionals working within software development teams. We report on student engagement with the formative practical exercises and analyse the content of the questions they asked.

AB - We explore the use of the PRIMM methodology (Predict, Run, Investigate, Modify, Make) within a higher education introductory programming setting, particularly focusing on the three first three steps. Formative prediction questions on the effects of changes to HTML, CSS or JavaScript code are constructed by students using PeerWise system, based on their own investigation. Authenticity of the task is enhanced by presenting the peer prediction questions as pull requests to a GitHub repository, mirroring the code review process followed by professionals working within software development teams. We report on student engagement with the formative practical exercises and analyse the content of the questions they asked.

U2 - 10.1145/3633053.3633062

DO - 10.1145/3633053.3633062

M3 - Conference contribution

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Y2 - 5 January 2024

ER -

PRIMM and Proper: Authentic Investigation in HE Introductory Programming with PeerWise and GitHub

Abstract

Conference

Access to Document

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Student theses

Automated customer management with sequential pattern mining of journey data logs

Cite this