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Description / Abstract
Submitted to the Department of Mathematics and Computer Science in partial fulfillment of the requirements for the degree of Bachelor of Arts.
Assessing General Education (GE) student outcomes for accreditation occurs regularly at higher education liberal arts institutions; however, the process can be complicated and time-consuming, and the resulting outcome data may not be meaningful on its own. This project automates Northwest Nazarene University’s GE outcome assessment process using Python scripts and the Canvas Application Programming Interface (API). The Python scripts automatically send personalized training and reminder emails to GE instructors, retrieve, clean and enrich GE outcome data, and create GE assessment compliance data. Upon completion, Microsoft Power BI visualizes the data. By automating these actions, the project streamlined Northwest Nazarene University’s GE pipeline and transformed years of data into actionable information that could also be shown to accreditors. Furthermore, Microsoft Power BI was leveraged to show how consistently specific colleges, disciplines, departments, courses, and instructors were assessing their GE outcomes, thereby providing college deans and department chairs with information on where to focus their efforts to increase GE outcome compliance.
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Copyright Notes
This material is used by permission of the rightsholder in accordance with the terms of the relevant content release. As a user, you have permission to use this content and download a copy for non-commercial use only. Downloading multiple quantities of this resource is expressly forbidden.
KeywordsGeneral education, Outcomes, Automation
Degree AwardedBachelor of Arts
Awarding InstitutionNorthwest Nazarene University
Committee MembersCatherine Becker
Supervisor or ChairDale Hamilton
Peer Reviewed?No
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NNU Computer Science Theses
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