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This study demonstrates that self-starting control charts for program-level assessment in higher education provide improved decision support over the use of fixed performance standards. Using a 5-year case study of program outcome assessment data, self-starting control charts yielded more accurate and actionable interpretations in 34% of observations when compared to the use of fixed performance standards. The advantages of self-starting control charts include their ability to detect true changes in student achievement levels; monitor outcomes achieved at both high and low levels, and remain effective as programs evolve. The Q-chart self-starting statistical process control (SPC) methodology presented offers a flexible and statistically valid approach applicable to various types of assessment methods and data sources in program-level evaluation. Q-charts are readily implementable with common software such as spreadsheets. The implications of adopting this approach include improved efficiency in the use of resources, increased program outcome achievement, and statistically sound continuous improvement documentation.
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Matt Brown (2025) studied this question.
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