There was wide participation in the fall implementation of the Common Math Assignment, and hundreds of students read the article about regional distribution of wealth. Many students discussed the article and the math problems with family and friends. Several teachers found inventive ways of working the discussion into their syllabi. Students reported mixed reactions to dredging up math skills that they hadn’t used for a while. The results of the scoring (see Charts 1-7 and Interim Report) provided stimulus to discussion of math pedagogy and curriculum.
Students and teachers alike felt that the ten questions took too long to answer and that the burden of making extra copies for assessment scoring was cumbersome. Controversy arose about the reliability of the answers written outside of class. Locating the work within classrooms would have assured the independent thinking of individual students, while the self-managed homework could be seen as the more natural environment for problem solving. The Student Learning Assessment Team decided that the spring version of the assessment would include fewer questions and that these should be implemented within the controlled environment of the classroom.
Two areas of student weakness were identified in the results of the fall CMA: graphing and math modeling. Math modeling was the lowest (See Charts 1& 3), and also the most complex to evaluate. Graphing was surprisingly low, and more straightforward to explore. The Team decided to focus on examining the nature of the graphing problem.
In addition, students responded poorly or not at all to the open-ended questions which asked them to draw conclusions from the data table. It was decided to offer a more guided question that leading students toward making meaning from data.
The spring implementation, CMA2, was drafted to pursue these inquiries. It included three graphing questions based on problems related to the article and data table and a choice of two questions requiring short paragraph answers about patterns revealed by the data.
The 73 scored samples were rendered fully anonymous and analyzed using an array of relevant academic history categories. Then aggregates were studied in response to several questions. One was how CMA scores correlated with Accuplacer Algebra scores, and this inquiry was hampered by the absence of Accuplacer scores for more than half of the samples. However, with the 31 scores available, the result showed that students who entered at a developmental level scored consistently lower in all categories, though the difference was slightest in the algebra/geometry area. (See Chart 2).
A second inquiry was about how completion of math classes at CCC correlated with CMA scores. The results (see Chart 4) showed a marked improvement in scores among students who had taken Math080 or higher level math. This indicates that Math 046, though essential for progress to the higher levels, is far from adequate as an end point in math study.
A third question focused on the relationship of CMA scores with grades, both in math courses (see Chart 5) and in other courses as reflected in GPA’s (see Chart 6). The results implied a positive correlation between CMA scores and college grades.
A final question was whether students currently enrolled in math classes scored better than students whose math classes were in the past. The results (see Chart 7) corroborated that supposition, though an anomaly in the algebra/geometry category raises further questions about persistence of prior knowledge.
This initial probe of mathematical competencies at CCC confirmed several suppositions:
The probe pointed toward two new conclusions and consequent recommendations: