Does in‐service professional learning for high school economics teachers improve student achievement?

Abstract

Education policy analysts and professional educators have called for more and better professional learning opportunities for in‐service teachers, and for at least 30 years economists called for more content training for high school economics teachers. Using new data from all Georgia high school economics students, we assess the impact of in‐service teacher workshops on the performance of students on a high‐stakes end‐of‐course economics exam. Controlling for student characteristics and teacher fixed effects, we find a positive and significant impact of teacher workshop attendance – once teachers have attended three workshops – on student test scores. Furthermore, the results suggest that in‐service workshops for economics teachers offer a cost‐effective way to provide content training.

Keywords:

• in‐service teacher training
• student achievement

Acknowledgements

This research was partially funded by an Excellence in Economic Education subgrant from the National Council on Economic Education through funding from the United States Department of Education, Office of Innovation. The authors thank the National Council on Economic Education and the Georgia Council on Economic Education for their financial support. They also thank the Georgia Department of Education for its willingness to share its data and human resources. Finally, the authors appreciate the insightful comments of two anonymous referees.

Notes

1. Their sample consists of 100,288 third‐grade through sixth‐grade students.

2. Prior to spring 2004, the economics EOCT was administered to students for purposes of standard setting and was not a high‐stakes examination. Georgia also administers EOCTs in seven other high school subjects.

3. Of the 90 questions, 75 count toward the student's score. Each test also field tests 15 questions that do not count toward the student's score. After norming, 99% of the test scores will fall within the range of 1–99. One percent of the scores will fall in the extreme tails of the distribution.

4. NCE score = 21.06 × z‐score + 50. This positive monotonic transformation of the scale scores of the EOCT allows comparison of examinations across time. Our results are not impacted in any meaningful way by this transformation. The transformation, however, aids in the interpretation of the results.

5. As shown in Table 1, the estimated coefficient on ‘Poor’ is −4.20. The standard deviation of the EOCT score is 20.66, as seen in Appendix 2. Since −4.20 divided by 20.66 is equal to 0.20, we report that being economically disadvantaged reduces expected test scores by 20% of a standard deviation.

6. Since so few of the teachers in our data attend more than three workshops, we do not feel comfortable making strong statements about the effects of attending four or more workshops. In addition, we estimated our equation with a series of dummy variables indicating how many workshops were attended. All of these variables had positive estimated coefficients, but some were not statistically significant – in particular, the dummy variables for two and four workshops, respectively. This lack of significance could be due to small cell sizes.

7. In an earlier version of this paper we reported results that excluded teachers who had workshop experience prior to appearing in our data. In those results, we found an effect of workshops about 50% larger than what is reported here. We believe the results reported here do a better job of controlling for unobserved selection into workshops, and we thank an anonymous referee for the suggestion.