Evaluating software inspection cognition levels using Blooms Taxonomy

This paper reports on results from a pilot study that used Bloom's Taxonomy to observe cognition levels during software inspections conducted by undergraduate computer science and software engineering students. Cognition levels associated with three different code inspection techniques were inv...

Full description

Bibliographic Details
Main Authors: McMeekin, David, von Konsky, Brian, Chang, Elizabeth, Cooper, David
Other Authors: Vasudeva Varma
Format: Conference Paper
Published: IEEE Computer Society 2009
Online Access:http://doi.ieeecomputersociety.org/10.1109/CSEET.2009.15
http://hdl.handle.net/20.500.11937/30338
_version_ 1848753060871929856
author McMeekin, David
von Konsky, Brian
Chang, Elizabeth
Cooper, David
author2 Vasudeva Varma
author_facet Vasudeva Varma
McMeekin, David
von Konsky, Brian
Chang, Elizabeth
Cooper, David
author_sort McMeekin, David
building Curtin Institutional Repository
collection Online Access
description This paper reports on results from a pilot study that used Bloom's Taxonomy to observe cognition levels during software inspections conducted by undergraduate computer science and software engineering students. Cognition levels associated with three different code inspection techniques were investigated. These were the Ad hoc, Abstraction Driven, and Checklist-based reading strategies. Higher cognition levels were observed when using inspection techniques that utilise a more structured reading process. This result highlights the importance of introducing novice programmers to structured code reading strategies. Findings suggest that teaching different software inspection techniques throughout software courses, beginning with structured techniques, is an excellent way to build a student's critical software reading and analysis skills.
first_indexed 2025-11-14T08:18:31Z
format Conference Paper
id curtin-20.500.11937-30338
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T08:18:31Z
publishDate 2009
publisher IEEE Computer Society
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-303382019-02-19T05:36:13Z Evaluating software inspection cognition levels using Blooms Taxonomy McMeekin, David von Konsky, Brian Chang, Elizabeth Cooper, David Vasudeva Varma This paper reports on results from a pilot study that used Bloom's Taxonomy to observe cognition levels during software inspections conducted by undergraduate computer science and software engineering students. Cognition levels associated with three different code inspection techniques were investigated. These were the Ad hoc, Abstraction Driven, and Checklist-based reading strategies. Higher cognition levels were observed when using inspection techniques that utilise a more structured reading process. This result highlights the importance of introducing novice programmers to structured code reading strategies. Findings suggest that teaching different software inspection techniques throughout software courses, beginning with structured techniques, is an excellent way to build a student's critical software reading and analysis skills. 2009 Conference Paper http://hdl.handle.net/20.500.11937/30338 http://doi.ieeecomputersociety.org/10.1109/CSEET.2009.15 IEEE Computer Society fulltext
spellingShingle McMeekin, David
von Konsky, Brian
Chang, Elizabeth
Cooper, David
Evaluating software inspection cognition levels using Blooms Taxonomy
title Evaluating software inspection cognition levels using Blooms Taxonomy
title_full Evaluating software inspection cognition levels using Blooms Taxonomy
title_fullStr Evaluating software inspection cognition levels using Blooms Taxonomy
title_full_unstemmed Evaluating software inspection cognition levels using Blooms Taxonomy
title_short Evaluating software inspection cognition levels using Blooms Taxonomy
title_sort evaluating software inspection cognition levels using blooms taxonomy
url http://doi.ieeecomputersociety.org/10.1109/CSEET.2009.15
http://hdl.handle.net/20.500.11937/30338