Abstract:We analyse the impact of learning strategies on engineering students' performance in mathematics. Learning strategies play an important role in self-regulated learning and are a possible predictor of student performance. Especially for mathematics-related learning strategies, the question arises how such strategies can be measured and how they relate to mathematics performance. Therefore, we present a new learning strategy questionnaire that takes into account the specifics of mathematical learning at universi… Show more
“…The learning strategy "practicing" affects performance, which is also reported in Liebendörfer et. al.…”
Section: Discussionsupporting
confidence: 68%
“…While there is a positive correlation between domain-specific learning strategies and performance in mathematics, and between elaboration and performance as well, there is a negative correlation between performance in mathematics and rehearsal (Kolter et al, 2018). However, Liebendörfer et. al.…”
Section: Learning Strategies In Mathematics In Higher Educationmentioning
Background
There are different teaching methods and learning content in the academic field of mathematics between school and university. Many students fail in their studies when the proportion of mathematics is high. Additionally, dropout rates, due to mathematical performance, are high. However, there are different strategies used to improve mathematical skills. Based on the process model of self-regulated learning, an analysis of the association between motivational aspects in the pre-action phase as well as seven special cognitive learning strategies for mathematics in the action phase was conducted. The variables were compared with student performance. The study drew on data from 548 retrospective interviews of cooperative students, using a cross-sectional research design.
Results
The analysis via structural equation modeling shows a direct association between motivational aspects, such as academic self-concept and curiosity, and the seven learning strategies in mathematics. Furthermore, there is a direct effect of academic self-concept on performance. However, the learning strategy of practicing was the only variable with associations to performance. Additionally, the indirect effect of curiosity on performance via practicing is analyzed.
Conclusion
It can be seen, that curiosity on its own is not enough to ensure a good level of performance in mathematics. The findings suggest student learning strategies focusing on harnessing their curiosity and on practicing. A high academic self-concept is also relevant to the performance level achieved. Lecturers should create a learning environment to support such student behavior.
“…The learning strategy "practicing" affects performance, which is also reported in Liebendörfer et. al.…”
Section: Discussionsupporting
confidence: 68%
“…While there is a positive correlation between domain-specific learning strategies and performance in mathematics, and between elaboration and performance as well, there is a negative correlation between performance in mathematics and rehearsal (Kolter et al, 2018). However, Liebendörfer et. al.…”
Section: Learning Strategies In Mathematics In Higher Educationmentioning
Background
There are different teaching methods and learning content in the academic field of mathematics between school and university. Many students fail in their studies when the proportion of mathematics is high. Additionally, dropout rates, due to mathematical performance, are high. However, there are different strategies used to improve mathematical skills. Based on the process model of self-regulated learning, an analysis of the association between motivational aspects in the pre-action phase as well as seven special cognitive learning strategies for mathematics in the action phase was conducted. The variables were compared with student performance. The study drew on data from 548 retrospective interviews of cooperative students, using a cross-sectional research design.
Results
The analysis via structural equation modeling shows a direct association between motivational aspects, such as academic self-concept and curiosity, and the seven learning strategies in mathematics. Furthermore, there is a direct effect of academic self-concept on performance. However, the learning strategy of practicing was the only variable with associations to performance. Additionally, the indirect effect of curiosity on performance via practicing is analyzed.
Conclusion
It can be seen, that curiosity on its own is not enough to ensure a good level of performance in mathematics. The findings suggest student learning strategies focusing on harnessing their curiosity and on practicing. A high academic self-concept is also relevant to the performance level achieved. Lecturers should create a learning environment to support such student behavior.
“…Dieses Konzept wird unter anderem genutzt, um Referenzmodelle als Grundlage für Analysen des gelehrten und gelernten Wissens zu formulieren. Im Schule-Hochschule-Übergang kommt (Hochmuth & Peters, 2021;2022). In Forschungen der HDM, die sich der kommunikativen Perspektive der »Commognition Theory« von Sfard (2014) bedienen, liegt der Fokus auf mathematischen Diskursen innerhalb und zwischen verschiedenen Gruppen und insbesondere auf den Verschiebungen von Diskursen und Regeln.…”
Section: Theoretische Ansätze In Der Hochschuldidaktik Mathematikunclassified
Mathematikdidaktische Forschung verortet sich in einem Kontext vielfältiger sog. Bezugswissenschaften: Erkenntnisse, Theorien und Forschungsmethoden aus der Psychologie, der Pädagogik, den Sozialwissenschaften u.a.m. werden angewendet oder adaptiert und so für die Beforschung des Lernens und der Lehre von Mathematik in Schule und Hochschule fruchtbar gemacht. Wie mathematikdidaktische Theorien, die sich in unterschiedlicher Weise der Bezugswissenschaften bedienen, miteinander vernetzt werden können, wurde in den zurückliegenden 15 Jahren intensiv beforscht. Nach einem kurzen Einblick in Arbeitsfelder und theoretische Ansätze der Hochschuldidaktik Mathematik werden unter anderem von Radford (2008) hervorgehobene Herausforderungen an Vernetzungspraktiken aufgegriffen und hinsichtlich offener Forschungsfragen diskutiert.
“…So zeigen beispielsweise in ingenieurmathematischen Veranstaltungen leistungsstarke Studierende hohe Werte in der Anstrengung und bezüglich Übungsstrategien, die oft als Oberflächenstrategien bezeichnet werden, aber eher geringere Werte hinsichtlich Elaborations-und Organisationsstrategien(Liebendörfer et al, 2022).…”
In der Wissenschaft sind Erkenntnisziele, aber auch ein spezieller Weltaufschluss angelegt. Diesen zu vermitteln ist Aufgabe der Wissenschaftsdidaktik. Was aber bedeutet es, Wissenschaft institutionell zu einem Gegenstand des Lehrens und Lernens zu machen? Die Beitragenden des Bandes liefern disziplinübergreifende Antworten auf diese grundlegende Frage und untersuchen aus ihren fachwissenschaftlichen Perspektiven, wie Lehren, Studieren und wissenschaftliches Denken und Handeln disziplinär zusammenhängen. Hochschullehrende sowie praktisch und forschend tätige Personen finden hier leichten Zugang zur Wissenschaftsdidaktik und ihren innovativen Erkenntnispotentialen.
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