SwePub
Sök i LIBRIS databas

  Extended search

WFRF:(Minguillon C.)
 

Search: WFRF:(Minguillon C.) > A Methodology for I...

A Methodology for Investigating Women's Module Choices in Computer Science

Bradley, Steven (author)
Parker, Miranda C. (author)
Altin, Rukiye (author)
show more...
Barker, Lecia (author)
Hooshangi, Sara (author)
Kamal, Samia (author)
Kunkeler, Thom (author)
Uppsala universitet,Datavetenskapens didaktik,Avdelningen Vi3,UpCERG
Lennon, Ruth G. (author)
McNeill, Fiona (author)
Minguillón, Julià (author)
Parkinson, Jack (author)
Peltsverger, Svetlana (author)
Sibia, Naaz (author)
show less...
 (creator_code:org_t)
Association for Computing Machinery (ACM), 2023
2023
English.
In: ITiCSE 2023. - : Association for Computing Machinery (ACM). - 9798400701399 ; , s. 569-570
  • Conference paper (peer-reviewed)
Abstract Subject headings
Close  
  • At ITiCSE 2021, Working Group 3 examined the evidence for teaching practices that broaden participation for women in computing, based on the National Center for Women & Information Technology (NCWIT) Engagement Practices framework. One of the report's recommendations was "Make connections from computing to your students' lives and interests (Make it Matter) but don't assume you know what those interests are; find out!" The goal of this 2023 working group is to find out what interests women students by bringing together data from our institutions on undergraduate module enrollment, seeing how they differ for women and men, and what drives those choices. We will code published module content based on ACM curriculum guidelines and combine these data to build a hierarchical statistical model of factors affecting student choice. This model should be able to tell us how interesting or valuable different topics are to women, and to what extent topic affects choice of module - as opposed to other factors such as the instructor, the timetable, or the mode of assessment. Equipped with this knowledge we can advise departments how to focus curriculum development on areas that are of value to women, and hence work towards making the discipline more inclusive.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

Datavetenskap med inriktning mot datavetenskapens didaktik
Computer Science with specialization in Computer Science Education Research

Publication and Content Type

ref (subject category)
kon (subject category)

Find in a library

To the university's database

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view