Assessment and Continuous Improvement of an Undergraduate Data Science Program.
In recent years, there has been an explosion in the growth of undergraduate statistics and data science programs across the US. Simultaneously, there has been clear guidance written on curriculum development for both data science (De Veaux et al.) and statistics (Carver et al.) programs. While this...
| Published in: | American Statistician Vol. 79; no. 1; pp. 102 - 122 |
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| Main Authors: | , , |
| Format: | Article |
| Published: |
Taylor & Francis Ltd
Feb2025
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=182438224&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 182438224 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: Y pubinfo: dt: Feb2025 vid: 79 iid: 1 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 182438224 10.1080/00031305.2024.2365673 ppf: 102 ppct: 20 formats: tig: atl: Assessment and Continuous Improvement of an Undergraduate Data Science Program. aug: au: Clark, Nicholas Morrell, Christopher Powell, Mike affil: Department of Mathematical Sciences, United States Military Academy, West Point, NY Department of Electrical Engineering and Computer Science, United States Military Academy, West Point, NY su: Continuous improvement process Data science Statistical association Curriculum evaluation Curriculum planning sug: subj: Continuous improvement process Data science Statistical association Curriculum evaluation Curriculum planning keyword: Accreditation Curriculum Program evaluation Accreditation Curriculum Program evaluation ab: In recent years, there has been an explosion in the growth of undergraduate statistics and data science programs across the US. Simultaneously, there has been clear guidance written on curriculum development for both data science (De Veaux et al.) and statistics (Carver et al.) programs. While this was occurring, ABET (now simply an acronym, but previously standing for the Accreditation Board for Engineering and Technology), in coordination with organizations such as the American Statistical Association, developed accreditation criteria for Data Science programs. In this article, we discuss our journey through ABET accreditation and discuss how adopting ABET processes for continuous improvement strengthens a program's assessment process. We share best practices for working across multiple departments to collect data not only on individual courses, but also on the program as a whole. While the framework presented was initially established to support ABET accreditation, we argue that a properly executed program assessment should occur regardless of whether or not an institution is seeking ABET accreditation for their data science program. Throughout this article, we also discuss the extent to which ABET requirements naturally fit within our program's existing goals, including an assessment of how ABET requirements align with major ideas in the field of data science education. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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