Towards a fine-grained analysis of complexity of programming tasks

Rodrigo Duran*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Bloom's and SOLO taxonomies have been used to describe the complexity of computer science tasks and student's outcome. However, using these taxonomies have coarse granularity and programming tasks with very different demands could be equally classified at the same level. My research proposes a new framework using Neo- Piagetian stages of development based on the Model of Hierarchical Complexity (MHC) that enable formal definition and fine-grained evaluation of programming tasks nuances in paradigms, languages, and constructs. By empirically validating the model, I expect it to be a valuable tool to provide best practices to develop pedagogical approaches and tools.

Original languageEnglish
Title of host publicationICER 2017 - Proceedings of the 2017 ACM Conference on International Computing Education Research
PublisherACM
Pages271-272
Number of pages2
ISBN (Electronic)9781450349680
DOIs
Publication statusPublished - 14 Aug 2017
MoE publication typeA4 Article in a conference publication
EventACM Conference on International Computing Education Research - Tacoma, United States
Duration: 18 Aug 201720 Aug 2017
Conference number: 13

Conference

ConferenceACM Conference on International Computing Education Research
Abbreviated titleICER
CountryUnited States
CityTacoma
Period18/08/201720/08/2017

Keywords

  • Model of hierarchical complexity
  • Neo-piagetian stages
  • Task complexity

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    Duran, R. (2017). Towards a fine-grained analysis of complexity of programming tasks. In ICER 2017 - Proceedings of the 2017 ACM Conference on International Computing Education Research (pp. 271-272). ACM. https://doi.org/10.1145/3105726.3105731