Thumbnail
Access Restriction
Subscribed

Author Whitcomb, Ryan ♦ Kafura, Dennis ♦ Bart, Austin Cory ♦ Shaffer, Clifford A. ♦ Tilevich, Eli
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Keyword Authenticity ♦ Pedagogy ♦ Motivation ♦ Real-world data ♦ Computational thinking ♦ Data science ♦ Big data ♦ Corgis
Abstract To successfully bring introductory computing to non-CS majors, one needs to create a curriculum that will appeal to students from diverse disciplines. Several educational theories emphasize the need for introductory contexts that align with students' long-term goals and are perceived as useful. Data Science, using algorithms to manipulate real-world data and interpreting the results, has emerged as a field with cross-disciplinary value, and has strong potential as an appealing context for introductory computing courses. However, it is not easy to find, clean, and integrate datasets that will satisfy a broad variety of learners. The CORGIS project (https://think.cs.vt.edu/corgis) enables instructors to easily incorporate data science into their classroom. Specifically, it provides over 40 datasets in areas including history, politics, medicine, and education. Additionally, the CORGIS infrastructure supports the integration of new datasets with simple libraries for Java, Python, and Racket, thus empowering introductory students to write programs that manipulate real data. Finally, the CORGIS web-based tools allow learners to visualize and explore datasets without programming, enabling data science lessons on day one. We have incorporated CORGIS assignments into an introductory course for non-majors to study their impact on learners' motivation, with positive initial results. These results indicate that external adopters are likely to find the CORGIS tools and materials useful in their own pedagogical pursuits.
Description Affiliation: Virginia Tech, Blacksburg, VA, USA (Bart, Austin Cory; Whitcomb, Ryan; Kafura, Dennis; Shaffer, Clifford A.; Tilevich, Eli)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-12-01
Publisher Place New York
Journal Inroads
Volume Number 8
Issue Number 2
Page Count 7
Starting Page 66
Ending Page 72


Open content in new tab

   Open content in new tab
Source: ACM Digital Library