通过纵向诊断分类模型来说明写作技能增长的教学说明
Hamdollah Ravand1, Farshad Effatpanah2, Olga Kunina-Habenicht2
1English Department, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran.
Frontiers in psychology
|January 30, 2025
概括
这项研究使用增长诊断分类模型 (DCM) 来追踪L2写作技能的发展. 同行反对内容,组织,语法和词汇的写作轨迹的影响很小.
科学领域:
- 获得第二语言的学习.
- 教育心理学教育心理学
- 心理测量 心理测量 心理测量
背景情况:
- 诊断分类模型 (DCM) 越来越多地用于横截面研究.
- 对L2技能发展的纵向分析需要专门的模型.
- 增长的DCM提供了一个框架来分析随着时间的推移的技能变化.
研究的目的:
- 证明纵向DCM的应用,以分析L2写作技能的增长.
- 调查同行反对L2写作发展轨迹的影响.
- 为展示用于纵向DCM分析的TDCM包.
主要方法:
- 在三个时间点中利用了200名L2学习者的写作数据 (100个同行反,100个没有反).
- 使用TDCM套件应用了纵向DCM.
- 在四个写作子技能中分析了成长轨迹:内容,组织,语法和词汇.
主要成果:
- 两组人都在语法和词汇方面表现出类似的V形增长.
- 在两组中,组织和内容都观察到一致的反转V形模式.
- 在同行反和没有反组之间发现了微小的差异.
结论:
- 增长的DCM有效地模拟了随着时间的推移L2写作技能的发展.
- 同行反似乎对L2写作技能轨迹的影响有限.
- 社会动态可能会影响在L2写作环境中同行反的有效性.
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