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Understanding machine translation fit for language learning: The mediating effect of machine translation literacy

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Abstract

The use of machine translation has become a topic of debate in language learning, which highlights the need to thoroughly examine the appropriateness and role of machine translation in educational settings. Under the theoretical framework of task-technology fit, this explanatory case study set out to investigate the predictive role of machine translation fit, based on questionnaire responses obtained from a sample of 500 Chinese university EFL learners. Structural Equation Modeling approach was used to address the relationship between machine translation fit and learning performance, as well as the impact of technology and task characteristics on machine translation fit. The mediating role of machine translation literacy was further investigated in these relationships. The results showed that machine translation fit had a significant positive effect on learning performance. Both technology and task characteristics positively impacted machine translation fit. Meanwhile, machine translation literacy mediated the relationship between task characteristics and machine translation fit, but not technology characteristics and machine translation fit. This study has highlighted the significance of machine translation fit for language learning, providing suggestions and implications for integrating machine translation into language instructional practices.

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Data availability

The datasets generated during and/or analyzed during the present study are available from the corresponding author on reasonable request.

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Funding

This study was supported by the Project of Philosophy and Social Science Research in Jiangsu Province (23YYD003), China Postdoctoral Science Foundation (2023M731608), World Language and Cultural Studies Project in China Center for Language Planning and Policy Studies (WYZL2023JS0020) and Excellent Teaching-reform Project at Nan**g Agricultural University (JF202327).

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  1. School of Foreign Studies, Nan**g Agricultural University, No.1\Weigang, Xuanwu District, Nan**g, Jiangsu Province, 210096, China

    Yanxia Yang

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Appendix

Appendix

  • Sample items of the questionnaire.

  • Technology characteristics:

  • It is easy to operate the machine translation system.

  • Task characteristics:

  • I use machine translation to deal with translating tasks.

  • I use machine translation to deal with writing tasks.

  • Machine translation fit:

  • It is helpful to use machine translation in translating tasks.

  • Machine translation literacy:

  • I know the working principles of machine translation systems.

  • I know the text types in which machine translation systems excel.

  • Learning performance:

  • Employing machine translation can be helpful to improve my learning efficiency.

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Yang, Y. Understanding machine translation fit for language learning: The mediating effect of machine translation literacy. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12650-x

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