The primary goal of this study was to assess the validity of a standardized math test (ALEKS) as a means of math
placement. We also examined the predictive value of other measures (ACT math, SAT math, and high school GPA).
The dataset consisted of all new Washtenaw Community College students who took ALEKS in the 2017 calendar year
(n=1,290). Following the method of recent national studies, we used decision theory (Sawyer, 1989, 1996) to calculate
predicted probability of success or non-success in college level math courses. Predicted accuracy rate is the extent that
the placement test accurately assigns students to the correct course level. Accuracy rates using the criterion of C or
higher as success were low. This was primarily due to underplacement. Optimal cut scores were calculated that would
increase accuracy rates. It was also found that high school GPA was a better predictor of math course grade, first
semester college GPA, and first semester credits earned than ALEKS, ACT Math, and SAT Math scores.
As institutional researchers, we are used to seeing data in tables, charts, and graphs, but not all audiences absorb information in the same way. Increasingly for many, bite sized data points are preferred. However, when information is trimmed down, data points can lose context. That’s where infographics and other forms of data visualization come in as a tool to visually communicate complex data that can tell a story (and sometimes a story within a story). This session will show how to use tools readily available to all institutional researchers (Excel and Word) to improve how IR offices communicate and relay data. This session provides examples published by Michigan State University’s Institutional Studies office and the thoughts, tools, process, and shift in mindset that went into their creation and use.
Taking advantage of the R programming language workshop at MI/AIR 2017 and some subsequent training, we have used R to simplify and automate (and make more reliable) some processes presented previously at MI/AIR. One was a method to calculate the incremental cost or benefit of running an undersized section, to aid in decision-making at the class cancellation meeting. Another was to retrieve grade book data from our Brightspace LMS and to use those data for student outcome assessment. It will be shown how R can perform the calculations more reliably and efficiently than relying completely on Excel. R also provides a higher degree of flexibility to change input parameters. Also planned is a procedure using R to automate and streamline the calculation and submission of Perkins Core Indicators.
Within research in higher education, we often learn about different ways to conduct analyses to study certain populations. However, a question begs to be answered about how applicable or valid these studies are if applied at our own institution using the same methodology. Simons (2013) states that reproducibility is the cornerstone of science and if an effect is reliable, any competent researcher should be able to obtain it when using the same procedures. That is the premise for this presentation as Saginaw Valley State University looked to replicate a study done by Oakland University using logistic regression to estimate the impact that unmet financial need has on student retention rates. The study will be re-visited, comparing results, methods, and outcomes across both of the studies. The presentation will end with a brief discussion on the reproducibility crisis in psychology and medicine, how this crisis impacts research within IR, and practical tips on how to make your own research more reproducible. References: Simons, D. J. (2013). The value of direct replication. Perspectives on psychological science. 9(1) pp. 76-80.
We all dutifully submit data through IPEDS and other NCES studies, but don’t always have the time to follow through to see where the data become available to the public. Where will Outcome Measures show up? How is College Navigator updated? What data does the College Scorecard use? What are the NCES tools that will help me provide insightful data to my institution? This presentation will provide an overview of of the connections between data submissions and the resulting data tools.
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