Two Approaches for Programming Education in the Domain of Graphics: An Experiment

Context Graphics is a popular domain for teaching introductory programming in a motivating way, even in text-based programming languages.Over the last few decades, a large number of libraries using different approaches have been developed for this purpose.Inquiry Prior work in introductory programming that uses graphics as input and output has shown positive results in terms of engagement, but research is scarce on whether learners are able to use programming concepts learned through graphics for programming in other domains, transferring what they have learned.Approach We conducted a randomized, controlled experiment with 145 students as participants divided into two groups.Both groups programmed using graphics in Python, but used different approaches: one group used a compositional graphics library named PyTamaro; the other used the Turtle graphics library from Python's standard library.Student engagement was assessed with surveys, and programming knowledge with a post-test on general programming concepts and programming tasks in the domain of graphics.Knowledge We find few differences between the two groups on the post-test, despite the PyTamaro group having practiced on problems isomorphic to those in the post-test.The participants traced a compositional graphics program more accurately than a 'comparable' turtle graphics program.Both groups report high engagement and perceived learning; both perform well on simple program-writing tasks to create graphics.Grounding Our findings are based on a controlled experiment with a count of 145 participants, which exceeds the sample size indicated by power analysis to detect a medium effect size.The complete instrument and teaching materials used in the study are available as appendixes.Importance This study adds further evidence that graphics is an engaging domain for introductory programming; moreover, it shows that the compositional graphics approach adopted by PyTamaro yields engagement levels comparable to the venerable turtle approach.Compositional graphics code appears to be easier to trace than turtle graphics code.As for conceptual knowledge, our results indicate that practicing on programming tasks isomorphic to those of the test can still not be enough to achieve better transfer.This challenges programming educators and researchers to investigate further which graphics-based approaches work best and how to facilitate transfer.

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Publication Details

Journal
The Art Science and Engineering of Programming
Published
2025-02-15
DOI
https://doi.org/10.22152/programming-journal.org/2025/10/14
Citations
1
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
1.69

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article

Two Approaches for Programming Education in the Domain of Graphics: An Experiment

Luca Chiodini, Otto Seppälä, Juha Sorva, Arto Hellas et al.
1 citations
The Art Science and Engineering of Programming
Teaching and Learning Programming
1.69
article

Two Approaches for Programming Education in the Domain of Graphics: An Experiment

Luca Chiodini, Otto Seppälä, Juha Sorva, Arto Hellas, Matthias Hauswirth
article en
1 citations

Abstract

Context Graphics is a popular domain for teaching introductory programming in a motivating way, even in text-based programming languages.Over the last few decades, a large number of libraries using different approaches have been developed for this purpose.Inquiry Prior work in introductory programming that uses graphics as input and output has shown positive results in terms of engagement, but research is scarce on whether learners are able to use programming concepts learned through graphics for programming in other domains, transferring what they have learned.Approach We conducted a randomized, controlled experiment with 145 students as participants divided into two groups.Both groups programmed using graphics in Python, but used different approaches: one group used a compositional graphics library named PyTamaro; the other used the Turtle graphics library from Python's standard library.Student engagement was assessed with surveys, and programming knowledge with a post-test on general programming concepts and programming tasks in the domain of graphics.Knowledge We find few differences between the two groups on the post-test, despite the PyTamaro group having practiced on problems isomorphic to those in the post-test.The participants traced a compositional graphics program more accurately than a 'comparable' turtle graphics program.Both groups report high engagement and perceived learning; both perform well on simple program-writing tasks to create graphics.Grounding Our findings are based on a controlled experiment with a count of 145 participants, which exceeds the sample size indicated by power analysis to detect a medium effect size.The complete instrument and teaching materials used in the study are available as appendixes.Importance This study adds further evidence that graphics is an engaging domain for introductory programming; moreover, it shows that the compositional graphics approach adopted by PyTamaro yields engagement levels comparable to the venerable turtle approach.Compositional graphics code appears to be easier to trace than turtle graphics code.As for conceptual knowledge, our results indicate that practicing on programming tasks isomorphic to those of the test can still not be enough to achieve better transfer.This challenges programming educators and researchers to investigate further which graphics-based approaches work best and how to facilitate transfer.

The Art Science and Engineering of ProgrammingVol. 10(1)
Università della Svizzera italiana (CH), Aalto University (FI)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Quality Education
Openalex Percentile: Top 15%
Teaching and Learning Programming
1.69
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