Abstract
The quality of student learning and academic rigor is central to higher education. Nonetheless, colleges often prioritize metrics such as enrollment and graduation rates or use assessment data to solely fulfill accreditation requirements. The Academic Quality Assurance (AQA) team at a university ventured to expand the academic quality data landscape to learn more about student achievement. The paper shares the team’s journey to collect and report on student performance data for continuous improvement of academic programs. Specifically, this paper includes the methods to promote a culture of assessment by incorporating new concepts into the AQA process: Data visualization and storytelling with data. This paper includes the methodology to collect and report on data, samples of the systems and visualizations used, and the challenges faced in the context of people, process, and tools.
Highlights
Introduction and Historical ContextHow do higher education institutions define student success? Institutions define success based on competing priorities –while funding models in one institution may deem graduation and retention rates the hallmark of student success, student demographic in another institution may prescribe enrollment and completion rates as critical data points to track
Who focus on class or individual learner performance, one of the most critical aspects of student success is achievement of the intended learning outcomes within a degree program or course
Ty attitudes on technology, “faculty members are most likely to rely on student grades on exams and other assessments, and on student demonstration of competency in specified learning outcomes, to gauge whether their course is meeting its intended aims” [2, p.7]
Summary
How do higher education institutions define student success? Institutions define success based on competing priorities –while funding models in one institution may deem graduation and retention rates the hallmark of student success, student demographic in another institution may prescribe enrollment and completion rates as critical data points to track. As Suskie states, “Because we're not telling the stories of our successful outcomes in simple, understandable terms, the public continues to define quality using the outdated concept of inputs like faculty credentials, student aptitude, and institutional wealth — things that by themselves don’t say a whole lot about student learning” [3] This challenge afforded the opportunity for a college to refocus the attention on assessment data to obtain a more holistic picture of student success in the context of learning. Per recommendations from accrediting bodies and professional organizations such as the National Institute for Learning Outcomes Assessment, the team established Assessment Plans for academic programs These Assessment Plans included the typical Student Learning Outcomes (SLOs) and faculty-selected direct measures, or authentic demonstrations of learner performance such as capstone projects, case studies, projects with employers, or field exams [4]. The results were used, as intended, to inform teaching and learning
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