Examining Student Coding Behaviours in Creative Computing Lessons using Abstract Syntax Trees and Vocabulary Analysis

Matthew Yee-King, Louis Mccallum, Maria Teresa Llano, Vit Ruzicka, Mark D'inverno, Mick Grierson

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

Creative computing is an approach to computing education which emphasises the creation of interactive audiovisual software and an art-school influenced pedagogy. Given this emphasis on Dewey's "learning by doing", we set out to investigate the processes students use to develop their programs. We refer to these processes as the students' 'coding behaviour', and we expect that understanding it will provide us with valuable information about how students learn in our creative computing classes. As existing metrics were not sufficient, we introduce a new set of quantitative metrics to describe coding behaviours. The metrics consider factors such as students' vocabulary use and development, how fast and how much they alter the functionality of code over time and how they iterate on their code through text insert and delete operations. Many of our lessons involve providing students with demonstrator code which they use as a base for the development of their programs, so we use demo code as an entry point to our dataset. We look at programs students have written through developing the demo code in a dataset of over 16,000 programs. We clustered the demo code using the set of descriptive metrics. This lead to a set of clusters containing programs which are associated with distinct coding behaviours. Four was the ideal number of clusters for cluster density and separation. We found that the clusters had distinct behaviour patterns, that they were associated with different instructors and that they contained demo programs with different lengths.

Original languageEnglish
Title of host publicationITiCSE 2020 - Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages273-279
Number of pages7
ISBN (Electronic)9781450368742
DOIs
Publication statusPublished - 15 Jun 2020
Event25th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2020 - Trondheim, Norway
Duration: 15 Jun 202019 Jun 2020
https://dl.acm.org/doi/proceedings/10.1145/3341525 (Conference Proceedings)
https://iticse.acm.org/ITiCSE2020/ (Conference Website)

Publication series

NameITiCSE - Proceedings of the ACM Conference on Innovation and Technology in Computer Science Education
ISSN (Print)1942-647X

Conference

Conference25th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2020
Country/TerritoryNorway
CityTrondheim
Period15/06/2019/06/20
Internet address

User-Defined Keywords

  • Demonstrator Code
  • Creative Computing
  • MOOCs
  • Automated Code Analysis

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