Cory Bart, computer science PhD student, won the Best Research Paper award at the SIGCSE conference in March. The SIGCSE Technical Symposium is the largest computing education conference worldwide organized by ACM SIGCSE. It attracts around 1,300 researchers, educators, and others interested in improving computing education in K-12 and higher education. Ryan Whitcomb, computer science undergraduate student, along with CS faculty members: Dennis Kafura, Cliff Shaffer, and Eli Tilevich are co-authors of the paper.
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 eld with crossdisciplinary value, and has strong potential as an appealing context for introductory computing courses. However, it is not easy to nd, 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 nd the CORGIS tools and materials useful in their own pedagogical pursuits.