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The impact of automated feedback on L2 learners' written causal explanations

机译:自动反馈对二语学习者书面因果解释的影响

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Even though current technologies allow for automated feedback, evaluating content and generating discourse-specific feedback is still a challenge for automated systems, which explains the gap in research investigating the effect of such feedback. This study explores the impact of automated formative feedback on the improvement of English as a second language (ESL) learners' written causal explanations within two cause-and-effect essays and across pre- and post-tests. Pre- and post-test drafts, feedback reports for first and revised drafts from the automated writing evaluation system, and screen-capturing videos collected from 31 students enrolled in two sections of an advanced-low-level academic writing class were analyzed through descriptive statistics and the Wilcoxon signed-rank test. Findings revealed statistically significant changes in learners' causal explanations within one cause-and-effect essay while no significant improvement was observed across pre- and post-tests. The findings of this study offer not only insights into how to further improve automated discourse-specific feedback but also pedagogical implications for better learning outcomes.
机译:即使当前的技术允许自动反馈,但是评估内容并生成特定于语篇的反馈仍然是自动化系统面临的挑战,这解释了研究此类反馈的影响的研究差距。这项研究探讨了自动形成反馈对英语作为第二语言(ESL)学习者书面因果解释的改进的影响,包括两个因果文章以及测试前后。通过描述性统计数据分析了测试前和测试后的草稿,来自自动写作评估系统的初稿和修订稿的反馈报告,以及从参加高中低水平学术写作班两个部分的31名学生那里收集的截屏视频和Wilcoxon等级检验。结果显示,在一项因果论文中,学习者的因果解释在统计学上有显着变化,而在测试前后,则没有发现显着改善。这项研究的发现不仅提供了关于如何进一步改善特定于语篇的自动反馈的见解,而且还为更好的学习成果提供了教学意义。

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