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Feedback in Intelligent Computer-Assisted Language Learning and Second Language Acquisition: A study of its effect on the acquisition of French past tense aspect using an Intelligent Language Tutoring System

机译:智能计算机辅助语言学习和第二语言习得中的反馈:使用智能语言辅导系统对法语过去式方面习得的影响研究

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摘要

Questions surrounding the impact of feedback in response to learner error areudof interest in the fields of both Second Language Acquisition (SLA) and IntelligentudComputer-Assisted Language Learning (ICALL). Current empirical SLA researchudseeks to ascertain what feedback types have a statistically significant positiveudimpact on the process of acquiring a second language. Similarly, researchudin ICALL focuses on testing Intelligent Language Tutoring Systems (ILTSs) generallyudas well as the effectiveness of the feedback that they deliver. Despite thisudcommon interest in feedback, to date there has been no significant interdisciplinaryudresearch involving the two fields.udThe experiment reported here seeks to bridge this gap. Using a purpose-builtudILTS, we tested the effect of two types of feedback on the acquisition of Frenchudpast tense aspect among anglophone learners. Inspired by previous work in SLA,udExplicit Inductive (EI) and Input Processing (IP) feedback were tested against audcontrol group using a pre test/post test design. The learners completed a transformationudand a grammaticality judgment task. For the transformation, theyudwere presented with texts in the present tense and asked to re-write them in theudpast tense. For the grammaticality judgment, they had to rank the grammaticalityudof each sentence in a set of texts. In response to errors, EI feedback interpretedudthe aspectual meaning of the learners' answer and explicitly told them that itudwas not the most natural according to the context. In order to encourage formmeaningudmapping, IP feedback asked the learners to match their erroneous answerudto its interpretation. Two interpretations were presented: one was the targetudinterpretation and the other matched the learner's answer. Having made theirudchoice, they were then told whether it was correct as well as which interpretationudwas in fact target-like.udThe quantitative evaluation of the effectiveness of the EI and IP feedback wasudnot statistically significant. We argued that this was due to a combined effect ofudlearner level, target structure and feedback.
机译:在第二语言习得(SLA)和智能 ud计算机辅助语言学习(ICALL)领域中,围绕反馈对学习者错误的影响所引起的疑问已引起人们的关注。当前的经验性SLA研究 udseeks以确定哪些反馈类型对第二语言的获取过程具有统计学上显着的正影响。类似地,研究 udin ICALL重点关注一般情况下对智能语言辅导系统(ILTS)的测试以及它们提供的反馈的有效性。尽管对反馈的兴趣非常普遍,但迄今为止,还没有涉及这两个领域的重要的跨学科 udre研究。 ud此处报道的实验旨在弥合这一差距。使用特制的 udILTS,我们测试了两种类型的反馈对英语学习者中法语 udpast时态方面的获取的影响。受SLA先前工作的启发, udExplicit归纳(EI)和输入处理(IP)反馈是使用前测试/后测试设计针对 udcontrol组进行测试的。学习者完成了转换 udand语法判断任务。为了进行转换,向他们提供了当前时态的文本,并要求将其重新书写为过去时态。为了进行语法判断,他们必须在一组文本中对每个句子的语法 ud进行排名。针对错误,EI反馈会解释学习者答案的侧面意义,并明确告诉他们,根据上下文,这不是最自然的答案。为了鼓励形式含义 udmapping,IP反馈要求学习者将其错误答案 udd与它的解释相匹配。提出了两种解释:一种是目标 ud解释,另一种与学习者的答案相符。做出选择后,他们会被告知是否正确,以及哪种解释实际上是类似目标的。 ud对EI和IP反馈有效性的定量评估在统计学上没有显着意义。我们认为这是由于 udlearner级别,目标结构和反馈共同作用的结果。

著录项

  • 作者

    Hanson Ruth Mary;

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  • 年度 2008
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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