Details
| Original language | English |
|---|---|
| Pages (from-to) | 1133-1152 |
| Number of pages | 20 |
| Journal | International Journal of Mathematical Education in Science and Technology |
| Volume | 53 |
| Issue number | 5 |
| Early online date | 25 Jan 2022 |
| Publication status | Published - 2022 |
Abstract
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, we investigated 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.
Keywords
- higher education, learning strategies, Mathematics for engineers, students’ performance
ASJC Scopus subject areas
- Mathematics(all)
- Mathematics (miscellaneous)
- Social Sciences(all)
- Education
- Mathematics(all)
- Applied Mathematics
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In: International Journal of Mathematical Education in Science and Technology, Vol. 53, No. 5, 2022, p. 1133-1152.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - The role of learning strategies for performance in mathematics courses for engineers
AU - Liebendörfer, Michael
AU - Göller, Robin
AU - Gildehaus, Lara
AU - Kortemeyer, Jörg
AU - Biehler, Rolf
AU - Hochmuth, Reinhard
AU - Ostsieker, Laura
AU - Rode, Jana
AU - Schaper, Niclas
PY - 2022
Y1 - 2022
N2 - 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, we investigated 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.
AB - 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, we investigated 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.
KW - higher education
KW - learning strategies
KW - Mathematics for engineers
KW - students’ performance
UR - http://www.scopus.com/inward/record.url?scp=85123831175&partnerID=8YFLogxK
U2 - 10.1080/0020739X.2021.2023772
DO - 10.1080/0020739X.2021.2023772
M3 - Article
AN - SCOPUS:85123831175
VL - 53
SP - 1133
EP - 1152
JO - International Journal of Mathematical Education in Science and Technology
JF - International Journal of Mathematical Education in Science and Technology
SN - 0020-739X
IS - 5
ER -