Quantitative Analysis of OpenStax’ Free, Open-Source Principles of Macroeconomics text

Last fall, I adopted OpenStax’ Principles of Macro text for my course of the same name. I have blogged earlier about the creation of that text. After the semester, I conducted a statistical analysis of student learning in the course as compared to the previous year’s sections when I used a well-known commercial textbook.

I used the same methodology as my earlier analysis comparing my online and face-to-face courses, but added in one more semester for a total of 4 sections and 89 observations.

The model used raw (uncurved) final exam scores as the dependent variable, and the following as explanatory variables:

  • Student GPA (less their grade in my course) — this was to capture some measure of how bright each student was, and to a certain extent, how hard they work.
  • Credit Hours Earned — this was to control for how much experience each student had in university coursework.
  • Gender — the literature says that women do less well in economics than men.
  • Whether the Sections was Honors or Regular—last year I taught both section as face-to-face courses, but one was an honors section that followed a more abstract treatment of the material.
  • Whether the Section was Online or Face-to-Face—last year I taught no online sections, so the Online variable might not have had adequate controls.
  • OpenStax—the treatment variable for the text used in both sections last year.

The results were quite interesting and differed a bit from my earlier study. The most significant determinant of final exam scores remained Cumulative GPA. Credit hours earned was not statistically significant this time. Gender was statistically positive meaning that women scored higher on the final exam. Honors students (or more precisely, students in the honors section) scored significantly higher. This variable had the largest effect size. Online students scored statistically lower. Since this differs from my earlier analysis, I plan to explore this more in the future, but it’s not critical for this analysis. Finally, the OpenStax variable was not statistically different from zero. That is, students using the OpenStax text scored no differently than those using the commercial text.

I’m happy to share the details of the statistical results with anyone who is interested.



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