Enabling wide-scale computer science education through improved automated assessment tools
- Degree Grantor:
- University of California, Santa Barbara. Computer Science
- Degree Supervisor:
- Diana Franklin
- Place of Publication:
- [Santa Barbara, Calif.]
- Publisher:
- University of California, Santa Barbara
- Creation Date:
- 2014
- Issued Date:
- 2014
- Topics:
- Computer Science and Education, Sciences
- Keywords:
- Static analysis,
Scratch,
Assessment tools, and
Computer science education - Genres:
- Online resources and Dissertations, Academic
- Dissertation:
- Ph.D.--University of California, Santa Barbara, 2014
- Description:
There is a proliferating demand for newly trained computer scientists as the number of computer science related jobs continues to increase. University programs will only be able to train enough new computer scientists to meet this demand when two things happen: when there are more primary and secondary school students interested in computer science, and when university departments have the resources to handle the resulting increase in enrollment. To meet these goals, significant effort is being made to both incorporate computational thinking into existing primary school education, and to support larger university computer science class sizes. We contribute to this effort through the creation and use of improved automated assessment tools.
To enable wide-scale computer science education we do two things. First, we create a framework called Hairball to support the static analysis of Scratch programs targeted for fourth, fifth, and sixth grade students. Scratch is a popular building-block language utilized to pique interest in and teach the basics of computer science. We observe that Hairball allows for rapid curriculum alterations and thus contributes to wide-scale deployment of computer science curriculum. Second, we create a real-time feedback and assessment system utilized in university computer science classes to provide better feedback to students while reducing assessment time. Insights from our analysis of student submission data show that modifications to the system configuration support the way students learn and progress through course material, making it possible for instructors to tailor assignments to optimize learning in growing computer science classes.
- Physical Description:
- 1 online resource (148 pages)
- Format:
- Text
- Collection(s):
- UCSB electronic theses and dissertations
- Other Versions:
- http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:3645611
- ARK:
- ark:/48907/f3vh5m02
- ISBN:
- 9781321349146
- Catalog System Number:
- 990045116700203776
- Copyright:
- Bryce Boe, 2014
- Rights:
- In Copyright
- Copyright Holder:
- Bryce Boe
File | Description |
---|---|
Access: Public access | |
Boe_ucsb_0035D_12298.pdf | pdf (Portable Document Format) |