546
Views
11
CrossRef citations to date
0
Altmetric
Articles

Extensive knowledge integration strategies in pre-service teachers: the role of perceived instrumentality, motivation, and self-regulation

&
Pages 505-520 | Received 17 Sep 2016, Accepted 16 Sep 2017, Published online: 27 Sep 2017
 

Abstract

This study investigated contributions of pre-service teachers’ endogenous and exogenous instrumentalities, their intrinsic and extrinsic motivations, and their use of self-regulation strategies to explain the extent to which they used strategies to purposefully integrate their knowledge across courses (extensive knowledge integration). With a total of 254 pre-service teachers’ survey-responses, results of a hierarchical multiple regression analysis indicated that their endogenous instrumentality of their current coursework (i.e. seeing their course work as instrumentally connected to their future careers), their use of metacognitive strategies and their use of deeper cognitive learning strategies (e.g. elaboration and critical thinking) contributed to explaining their use of extensive knowledge integration strategies for completing coursework. Our results suggest that to develop pre-service teachers’ teaching expertise, they may need to (a) have a strong understanding that the current course content and their future goals are instrumentally linked, (b) be able to initiate planning and self-monitoring for learning and (c) use strategies for deep learning that integrates their knowledge across courses.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,036.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.