Analysis of Educational Course Trajectories: The Opportunity to Learn Algebra as a Pathway to Rigorous Mathematics in High School

• Activity Number: 475
• Type: Invited
• Date/Time: Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Social Statistics Section
• Author(s): Reginald Lee*+ and George MacDonald and Gladis Kersaint
• Companies: University of South Florida and University of South Florida and University of South Florida
• Keywords: large scale data ; data analysis ; data cleaning ; data quality ; propensity score matching ; Algebra I

Abstract

Education data analyses are conceptualized with an imperfect understanding of datasets provided by district, state and federal agencies. Cleansing and preparation is necessary before analysis may proceed. Mathematics course pathways were examined in three large datasets to illustrate the intricacies in preparing data. National databases offer opportunities to examine policy questions. State databases provided student transcripts and state assessment results. School district databases offer item information from assessments. The paper offers strategies for preparing these types of databases for analysis using the example of high school algebra course-taking. Conceptual strategies are presented to illustrate the complexity of cleaning, merging and matching variables from multiple sources. The prepared files were used for propensity score matching. Analytic strategies are presented to address the demographics of Algebra 1, student performance, and the opportunity to complete rigorous mathematics courses. Results presented demonstrate the importance of variable selection in making descriptive or inferential statements regarding policy implications or reports on student outcomes.