An analysis of economic learning among undergraduates in introductory economics courses in Germany

ABSTRACT

In this article, the authors present the findings of a pretest-posttest measurement of the economic knowledge of students in introductory economics courses in undergraduate study programs in Germany. The responses of 403 students to 14 items selected from the Test of Economic Literacy (Soper and Walstad 1987) were analyzed to identify four types of economic learning: positive, retained, negative, and zero learning. In addition, a survey was conducted to gather data on the students' personal characteristics to determine their effect on the learning process. Retained learning prevailed for most items, followed by zero learning and positive learning. To determine which factors influence beginning students' acquisition of economic knowledge and lead to positive learning, regression analyses were conducted, and the findings are discussed critically.

KEYWORDS:

• Higher education
• learning economics
• pretest-posttest measurement
• students in Germany
• Test of Economic Literacy

JEL CODES:

• A22
• I23

Acknowledgements

The authors thank William B. Walstad for his helpful comments and discussions.

Notes

1. The share of students in an age cohort enrolled in higher education increased from 37 percent in 2007 to 58 percent in 2013 (Federal Ministry of Education and Research 2014).

2. This test has been adapted and administered internationally (Yamaoka et al. 2010).

3. In contrast, Faulk, Srinivasan, and Bingham (2012) and Ballard and Johnson (2004) did not find that learning economics prior to starting studies in higher education influenced students' performance in introductory courses in business and economics in higher education.

4. The German research project was funded by the German Federal Ministry of Education and Research. For more information, see Happ and Zlatkin-Troitschanskaia (2014).

5. We also examined whether certain types of learning were determined by the cognitive levels established by the test developers (Soper and Walstad 1987). There were no systematic influences in this regard. Types of learning and cognitive levels were unrelated.

6. There is no guarantee that items solved correctly on the pretest will be solved correctly on the posttest (see Baddeley, Eysenck, and Anderson 2010). It is important that students be able to apply newly acquired knowledge to previously learned principles.

7. Cohen's d > 0.2 indicates a very weak effect; Cohen's d < 0.2 and > 0.5 indicates a medium effect; and Cohen's d < 0.8 indicates a strong effect.