Towards learning approaches of engineering students studying mathematics and the validity of approaches and study skill inventory for students

Gizem Intepe*, Irma Hacinliyan, Eti Mizrahi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Educational success is mainly based on the formation of effective learners. Students’ learning is affected by several variables, such as intelligence, motivation, teaching and learning approaches. Research showed that approaches to learning are among one of the most important variables that influence students’ learning quality. They are related to how students experience and organize the subject matter of a learning task. It is important to understand what and how students learn, rather than how much they remember. This paper aims to test the validity of the Turkish version of the Approaches and Study Skill Inventory for Students (ASSIST), which explores the types of learning approaches (deep surface or strategic), applied to the first-year undergraduate engineering students having mathematics as a compulsory course at Istanbul Technical University. Validation has been done by explanatory factor analysis. Afterwards, the relationship between the learning approaches and extracurricular factors is critiqued. For this purpose, the association between the language of the subject (English or Turkish) and the students’ learning approaches are investigated. Similarly, the relationship between learning approaches and parental education level as well as high school type is examined. Correlations between learning approaches conceptions of learning and teaching types are also tested.

Original languageEnglish
Pages (from-to)1000-1014
Number of pages15
JournalInternational Journal of Mathematical Education in Science and Technology
Volume54
Issue number6
DOIs
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • ASSIST
  • factor analysis
  • Learning approaches
  • mathematics education
  • statistical analysis
  • validity

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