Classroom learning and achievement: how the complexity of classroom interaction impacts students’ learning

Abstract

Background: Complexity models have provided a suitable framework in various domains to assess students’ educational achievement. Complexity is often used as the analytical focus when regarding learning outcomes, i.e. when analyzing written tests or problem-centered interviews. Numerous studies reveal negative correlations between the complexity of a task and the probability of a student solving it.

Purpose: Thus far, few detailed investigations explore the importance of complexity in actual classroom lessons. Moreover, the few efforts made so far revealed inconsistencies. Hence, the present study sheds light on the influence the complexity of students’ and teachers’ class contributions have on students’ learning outcomes.

Sample: Videos of 10 German 8th grade physics courses covering three consecutive lessons on two topics each (electricity, mechanics) have been analyzed. The sample includes 10 teachers and 290 students.

Design and methods: Students’ and teachers’ verbal contributions were coded manual-based according to the level of complexity. Additionally, pre-post testing of knowledge in electricity and mechanics was applied to assess the students’ learning gain. ANOVA analysis was used to characterize the influence of the complexity on the learning gain.

Results: Results indicate that the mean level of complexity in classroom contributions explains a large portion of variance in post-test results on class level. Despite this overarching trend, taking classroom activities into account as well reveals even more fine-grained patterns, leading to more specific relations between the complexity in the classroom and students’ achievement.

Conclusions: In conclusion, we argue for more reflected teaching approaches intended to gradually increase class complexity to foster students’ level of competency.

Keywords:

• Complexity
• achievement
• learning progress
• video study
• physics education

Acknowledgments

The authors would like to thank Manfred Prenzel, Tina Seidel, and Reinders Duit for letting us reanalyze the videos from the IPN video study (Seidel et al. 2003). Moreover, we are very grateful for content and lexical support by Ilka Parchmann and Cornelia A. Gerigk, respectively. Lastly, we thank our student assistants Bente Hansen, Henrike Rutz, Lars Höft, and Julian Etzel for their intense engagement in this project.

Funding

This work was supported by the German Research Foundation (DFG) [Grant Nr. BE 4703/3].

Notes

1. The German education system comprises three school forms that differentiate between a low (‘‘Hauptschule’’), middle (‘‘Realschule’’), and high (‘‘Gymnasium’’) teaching level. The first two can be counted for a non-academic track, whereas the academic track accounts for the high teaching level (‘Gymnasium’). All classes are independent courses, as biology, chemistry, and physics are usually taught as separate subjects in German secondary schools, not as part of a science course.

2. Trained students coded the data to avoid possible positive bias in data interpretation by the researcher and to ensure objectivity and reliability of the coding process.

3. All calculations were performed with R 3.1.1 for Windows 7 (R Core Team 2013) using the eRm 0.15-1 for Windows 7 package (Mair, Hatzinger, and Maier 2012)