学生教师复杂专业知识自主学习的建模:基于有声思考协议的序列聚类分析

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Lingyun Huang , Ying Zhan , Shen Ba
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引用次数: 0

摘要

关于学生教师自我调节学习(SRL)与技术教学内容知识(TPACK)发展之间的正向关系,已有很多讨论。本研究延续了这一说法,并采用先进的分析方法来解释SRL如何影响TPACK学习。39名参与者在学习TPACK时,通过使用基于计算机的学习环境nBrowser设计注入技术的课程,收集并转录了他们的有声思考协议。基于模型,从参与者的有声思考协议中检索到9个关键的SRL事件,并通过顺序聚类分析进行分析。结果显示,两个SRL组表现出不同的自我调节序列模式。其中一组具有较短的序列长度,主要从事精加工活动(低SRL组),而另一组具有较长的序列长度,从事多种SRL活动(高调节组)。关于课程计划质量所表明的TPACK表现,结果显示高srl组的参与者表现优于低srl组的参与者。研究结果与先前的证据一致,并为实践者提供了关于实习教师自我调节轨迹重要性的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling student teachers’ self-regulated learning of complex professional knowledge: A sequential and clustering analysis with think-aloud protocols
There has been much discussion regarding the positive relationship between self-regulated learning (SRL) and technological pedagogical content knowledge (TPACK) development for student teachers. This study continued this claim and adopted advanced analytical methods to explain how SRL influences TPACK learning. Think-aloud protocols from 39 participants were collected and transcribed when they were learning TPACK by designing technology-infused lessons with nBrowser, a computer-based learning environment. Based on models, nine critical SRL events were retrieved from participants‘ think-aloud protocols and analyzed through sequential clustering analysis. The results show two SRL groups indicating distinct self-regulatory sequential patterns. One group had a shorter sequence length and dominantly enacted elaboration activities (Low-SRL group), while the other had longer sequence lengths and engaged in diverse SRL activities (High-regulation group). Relating to TPACK performance indicated by the quality of lesson plans, the results reveal that the participants in the High-SRL group outperformed their counterparts in the Low-SRL group. The findings are consistent with previous evidence and provide implications for practitioners about the importance of student teachers’ self-regulation trajectories.
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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