Research methods to investigate emotions in independent language learning: a focus on think-aloud verbal protocols

Hurd, Stella (2011). Research methods to investigate emotions in independent language learning: a focus on think-aloud verbal protocols. In: Morrison, Bruce ed. Independent Language Learning: Building on Experience, Seeking New Perspectives. Hong Kong: Hong Kong University Press, pp. 87–100.

DOI: https://doi.org/10.5790/hongkong/9789888083640.003.0007

URL: http://books.google.co.uk/books/p/hkup?id=5ZNwM9xX...

Abstract

Affect as a critical dimension of language learning has been attracting a growing number of researchers as emotions continue to play an increasingly prominent role in theories of learning and language learning (Brown 1994, 2000; Arnold 1999; Oxford 1999; Young 1999; Dewaele 2005; Beard et al. 2007; Putwain 2007; Dewaele et al. 2008). In terms of second language acquisition (SLA), Robinson (2002, 63) reminds us that ‘researchers in the field of language learning have not paid sufficient attention to emotional phenomena’. Scovel (2001, 140) goes further in maintaining that ‘of the five major components of SLA [People, Languages, Attention, Cognition, and Emotion – PLACE] … emotion is the singly most influential’ and that affective variables are still the ‘area that SLA researchers understand the least’.

A consensus is emerging that ‘learning processes cannot be understood without taking emotional and motivational variables into account’ (Gläser-Zikuda and Järvelä 2008), and the increasing number of studies using process models testifies to this view. Such investigations pose, however, considerable challenges in terms of both content and process.
This paper explores the following questions:
• Why investigate emotions in independent language learning?
• Why is it so difficult to investigate emotions?
• Based on the author’s experience, what are the issues involved in using think-aloud verbal protocols as part of a mixed-method approach to investigating emotions?

Viewing alternatives

Metrics

Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions

Item Actions

Export

About

Recommendations