Preliminary Results from a High-Resolution Analysis of Accreditation Data to Assess Indicators, Identify Predictors and Assess Equitability of Teaching Practices

Mohammad Hosseini,Roza Vaez Ghaemi,Gabriel Potvin

Proceedings of the Canadian Engineering Education Association (CEEA)(2022)

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Abstract
The Department of Chemical and Biological Engineering (CHBE) at UBC has undertaken a high-resolution analysis of its accreditation data with the aim to identify any correlations between students’ declared gender, visa status (international or domestic), performance in individual indicators, course grades, and/or overall program GPAs. The hope is to extract meaningful information about the value of the indicators used in collecting information about our programs, increase the reliability of the data collected by reviewing those indicators that do not yield actionable data, identify predictors of student performance, and identify biases, if any, in the success rates of our students. This paper presents the results of the first steps of this analysis, using four core courses spanning CHBE’s programs. Correlations between performance in different indicators is represented by interaction heat maps and scatterplots, and performance by gender or student status are represented as violin plots. This paper serves as a proof of concept for this type of analysis, highlighting the value of this high-resolution look at accreditation data.
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Key words
accreditation data,teaching practices,assess equitability,assess indicators,high-resolution
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