Collective development of large scale data science products via modularized assignments: An experience report

Bhavya, Assma Boughoula, Aaron Green, Cheng Xiang Zhai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many universities are offering data science (DS) courses to fulfill the growing demands for skilled DS practitioners. Assignments and projects are essential parts of the DS curriculum as they enable students to gain hands-on experience in real-world DS tasks. However, most current assignments and projects are lacking in at least one of two ways: 1) they do not comprehensively teach all the steps involved in the complete workflow of DS projects; 2) students work on separate problems individually or in small teams, limiting the scale and impact of their solutions. To overcome these limitations, we envision novel synergistic modular assignments where a large number of students work collectively on all the tasks equired to develop a large-scale DS product. The resulting product can be continuously improved with students' contributions every semester. We report our experience with developing and deploying such an assignment in an Information Retrieval course. Through the assignment, students collectively developed a search engine for finding expert faculty specializing in a given field. This shows the utility of such assignments both for teaching useful DS skills and driving innovation and research. We share useful lessons for other instructors to adopt similar assignments for their DS courses.

Original languageEnglish (US)
Title of host publicationSIGCSE 2020 - Proceedings of the 51st ACM Technical Symposium on Computer Science Education
PublisherAssociation for Computing Machinery
Pages1200-1206
Number of pages7
ISBN (Electronic)9781450367936
DOIs
StatePublished - Feb 26 2020
Event51st ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2020 - Portland, United States
Duration: Mar 11 2020Mar 14 2020

Publication series

NameAnnual Conference on Innovation and Technology in Computer Science Education, ITiCSE
ISSN (Print)1942-647X

Conference

Conference51st ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2020
CountryUnited States
CityPortland
Period3/11/203/14/20

Keywords

  • Experience report
  • Practical data science education
  • Synergistic modular assignments

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Education

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    Bhavya, Boughoula, A., Green, A., & Zhai, C. X. (2020). Collective development of large scale data science products via modularized assignments: An experience report. In SIGCSE 2020 - Proceedings of the 51st ACM Technical Symposium on Computer Science Education (pp. 1200-1206). (Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE). Association for Computing Machinery. https://doi.org/10.1145/3328778.3366961