Michael Liebendörfer, Robin Göller, Lara Gildehaus, Jörg Kortemeyer, Rolf Biehler, Reinhard Hochmuth, Laura Ostsieker, Jana Rode, Nicolas Schauer
We analyse the predictive power of learning strategies for engineering students’ performance in mathematics. Learning strategies play an important role in self-regulated learning. Based on a new learning strategy questionnaire that takes into account the specifics of mathematical learning at universities,weinvestigated what were the strategies that correlate with performance and predict future performance.
We present data of a longitudinal study with N = 361 engineering students regressing their performance on students’ use of their learning strategies as well as their prior performance. The results indicate that practicing but not repeating the content and resisting frustration predict students’ performance. We discuss the findings with a specific view on what is tested and why some elaboration strategies might not be rewarded in exams.
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