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Theme Issue: ‘affect and beliefs’ within the learning of mathematics

A framework for using learning theories to inform ‘growth mindset’ activities

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Pages 26-43 | Received 27 Aug 2018, Published online: 08 Jan 2019
 

ABSTRACT

The social psychology theory of fixed and growth mindsets offers one reason for observed underachievement in science, technology, engineering and mathematics (STEM), particularly for students who have previously excelled in these disciplines. Fixed mindset beliefs are linked to behaviours that can lead to avoiding challenges and reduced learning, such as concealing a lack of understanding to retain an image of being ‘smart’. The potential impact of a growth mindset on STEM achievement, particularly for minority and low-household-income students, resulted in calls to develop interventions that encourage growth mindsets and discourage fixed mindsets. However, education interventions are influenced by the educator's understanding of how learning occurs. A framework to show how activities based on different learning theories may encourage growth mindsets or (unintentionally) encourage fixed mindsets can guide the developers of growth mindset interventions. We present such a framework in six tables relating to key areas associated with growth and fixed mindsets: dealing with challenges, persistence, effort, praise, the success of others and learning goals. Each table gives examples of learning activities that may encourage growth or fixed mindsets, fitting with each of four key learning theories: behaviourism, constructivism, communities of practice and connectivism.

Acknowledgements

The financial assistance of the National Research Foundation (NRF) and the University of Cape Town towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the authors and are not necessarily to be attributed to the NRF.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Research Foundation: [Grant Number TTK160531166788]; University of Cape Town.

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