Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Student perceptions and attitudes towards the software factory as a learning environment
University of Oulu, Finland.ORCID iD: 0000-0002-7885-0369
University of Oulu, Finland .
University of Oulu, Finland.
2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Industry needs graduates from universities having knowledge and skills to tackle the practical issues of real life software development. To facilitate software engineering students and fulfill industry need, the Department of Information Processing Science, University of Oulu, Finland, built a Software Factory laboratory (SWF) in 2012 based on Lean concept. This study examines factors in the SWF learning environment that affect learning of a SWF course by the students. It employs amended Computer laboratory Environment Inventory (CLEI) and Attitude towards Computers and Computing Courses Questionnaire instrument (ACCC) with two additional constructs: 1) Kanban board 2) Collaborative learning. The general findings indicate that SWF learning environment, collaborative learning and Kanban board play important role in software engineering students learning, academic achievements and professional skills gaining. The findings are helpful to develop a better understanding about learning environments. The information gathered in this study can also be used to improve the software engineering learning environment.

Place, publisher, year, edition, pages
IEEE, 2014. p. 422-428
Keywords [en]
software engineering education, software factory, computer laboratory learning enviroment, smart classroom, collaborative learning, teaching and learning
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-74303DOI: 10.1109/EDUCON.2014.6826129ISBN: 9781479931927 (print)OAI: oai:DiVA.org:kau-74303DiVA, id: diva2:1341913
Conference
IEEE Global Engineering Education Conference,3-5 April 2014, Istanbul, Turkey
Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-10-16Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Ahmad, Muhammad Ovais
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 48 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf