Quantitative Literacy Assessment At Kennedy King College Fall 2013 DRAFT - FOR DISCUSSION ONLY 1 Prepared by Robert Rollings, spring 2014

DRAFT - FOR DISCUSSION ONLY 2 Quantitative Literacy Assessment 1.Demonstrate understanding of mathematical processes by applying to real world phenomenon through engage in critical literacy 2.Apply mathematical exposition, including descriptions of algorithms and derivations of formulas, presented either orally or in writing 3.Determine whether a theorem or definition applies to a given situation, and use it appropriately if it applies 4.Analyze mathematical models in written language, in symbolic form, in graphic form, and interpret the solutions In fall 2013, 567 KKC students participated in an assessment of success in the following objectives: The assessment consisted of 11 questions concerning a student’s math history and demographics, 4 questions concerning attitudes toward math, and 10 math problems designed to test the above learning outcomes. Following a presentation of raw survey results, this report will examine correlations to determine which variables (if any) best predict student performance.

DRAFT - FOR DISCUSSION ONLY 3 Demographics Survey respondents were reasonably representative of the student body as a whole, except for a disproportionate inclusion of full-time students.

DRAFT - FOR DISCUSSION ONLY 4 Attitudes toward Math Students broadly agreed with the value of math, but they did not agree as strongly with its value for life decisions or for learning in other subjects as they agreed with its necessity for their careers.

DRAFT - FOR DISCUSSION ONLY 5 Students overall appear to have found the math assessment quite challenging. The top score of all 567 respondents was a 93%, and the average overall score was 36% The ten math problems addressed a varying set of the four SLOs, with all questions addressing SLO 1. Average scores on the math assessment, divided by learning objectives, are as follows: Standard Deviation in Percentage Points 17% 15% 19% Assessment Results These low-sounding numbers do not necessarily mean that students perform poorly at these skills; such an assessment is impossible without some manner of benchmark for comparison. However, we can say that our students on the whole performed better at applying theorems to a given situation than at mathematical exposition.

DRAFT - FOR DISCUSSION ONLY 6 With which variables did student success correlate? Women slightly outperformed men (with 37% versus 35% average success). Older students slightly outperformed younger students. Students in math-heavy majors (measured roughly on a scale of 1-10) outperformed students in less math-heavy majors. Students who believed that math helps them make intelligent decisions in life outperformed students who did not—and by a more significant margin than agreement with the questions concerning careers, learning, or problem strategies (p<.0002). The best predictor of a high score was math enrollment or eligibility; the direct correlation had a p< and an R of.043 in a linear regression. In other words, students enrolled or eligible in higher math classes scored better on the assessment. This obvious-sounding point becomes more telling in light of what is not correlated: number of credit hours and number of math classes taken at KKC. No statistically significant relationship exists between having taken classes (or math classes specifically) at KKC and succeeding on this assessment.

DRAFT - FOR DISCUSSION ONLY 7 This presentation is currently a work in progress. How can Kennedy King and its math classes teach the practical reasoning skills relevant to this assessment?

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