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Is There an “Expectancy × Value” Effect? Investigating the Impact of Self-Efficacy and Learning Motives on Chinese Undergraduates’ Use of Deep Language Learning Strategies

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Abstract

Drawing from Expectancy-Value Theory, this study explored the extent to which the interaction between learning motives for and self-efficacy in learning English as a foreign language (EFL) predicted deep language learning strategies by involving 693 undergraduates from mainland China in a survey. Stepwise multiple regression indicated that (i) as for the impact on language use strategies, the interaction was significant between self-efficacy and instrumental motives while it was insignificant between self-efficacy and intrinsic motives; (ii) as for the impact on language learning management strategies, the interactions between self-efficacy and two motives were both significant. This study develops existing language learning theories through (i) generating evidence to support the existence of the “Expectancy × Value” interaction in the context of learning EFL, and (ii) revealing the motive-specific and strategy-specific features of the interaction when deep language learning strategies are under investigation. Implications for enhancing students’ deep language learning strategies are discussed.

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Notes

  1. Both regression analysis and SEM analysis can be used to investigate the interaction effects. Compared with regression analysis, SEM analysis is good at controlling errors. However, since SEM needs to estimate both latent variables and errors and the popular estimation methods (such as maximum likelihood and generalised least square) have a higher requirement for the normal distribution of data (Jaccard and Wan 1995), it is better to conduct the SEM when the sample is more diversified so that the data are more possibly distributed normally.

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Zhan, Y., Jiang, Y., Wan, Z.H. et al. Is There an “Expectancy × Value” Effect? Investigating the Impact of Self-Efficacy and Learning Motives on Chinese Undergraduates’ Use of Deep Language Learning Strategies. Asia-Pacific Edu Res 30, 83–94 (2021). https://doi.org/10.1007/s40299-020-00516-y

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