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Providing graduated corrective feedback in an intelligent computer-assisted language learning environment
ReCALL ( IF 4.6 ) Pub Date : 2017-05-24 , DOI: 10.1017/s095834401700012x
Haiyang Ai

Corrective feedback (CF), a response to linguistic errors made by second language (L2) learners, has received extensive scholarly attention in second language acquisition. While much of the previous research in the field has focused on whether CF facilitates or impedes L2 development, few studies have examined the efficacy of gradually modifying the explicitness or specificity of CF as a function of a learner’s response to the feedback. Yet, the type and extent of CF needed by a learner, as suggested by Vygotsky (1978), sheds light on whether a learner is developing his or her abilities in a particular area and the ways in which they do it. This paper reports on a study that explores the design, effectiveness and learners’ perception toward agraduated(Aljaafreh & Lantolf, 1994) approach to CF, i.e., feedback that progresses from very general and implicit to very specific and explicit, in an intelligent computer-assisted language learning (ICALL) environment. The results show that the graduated approach to CF is effective in helping learners to self-identify and self-correct a number of grammatical issues, although an onsite tutor provides necessary remedies when the ICALL system occasionally fails to do its part. Implications for CF research, particularly on the notion of individualized feedback, are also discussed.

中文翻译:

在智能计算机辅助语言学习环境中提供分级纠正反馈

纠正性反馈 (CF) 是对第二语言 (L2) 学习者所犯语言错误的一种反应,在第二语言习得方面受到了广泛的学术关注。虽然该领域以前的许多研究都集中在 CF 是否促进或阻碍 L2 发展,但很少有研究检验根据学习者对反馈的反应逐渐修改 CF 的明确性或特异性的功效。然而,正如 Vygotsky (1978) 所建议的,学习者所需的 CF 的类型和范围揭示了学习者是否正在发展他或她在特定领域的能力以及他们这样做的方式。本文报道了一项研究,该研究探讨了设计、有效性和学习者对毕业(Aljaafreh & Lantolf, 1994) CF 方法,即在智能计算机辅助语言学习 (ICALL) 环境中从非常一般和隐含进展到非常具体和明确的反馈。结果表明,CF 的分级方法在帮助学习者自我识别和自我纠正许多语法问题方面是有效的,尽管当 ICALL 系统偶尔无法发挥作用时,现场导师会提供必要的补救措施。还讨论了对 CF 研究的影响,特别是关于个性化反馈的概念。
更新日期:2017-05-24
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