Analyzing collaborative learning : Multiple approaches to understanding processes and outcomes
Analyzing collaborative learning : Multiple approaches to understanding processes and outcomes
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分析协作学习：理解过程和结果的多种方法
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
Ellina Chernobilsky
中科院分区：
文献类型：
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作者：
C. Hmelo‐Silver;Ellina Chernobilsky
重要的是要从多个角度来考虑协作过程，因为协作学习环境是复杂的，通常需要多种方法来理解它们的不同方面(Hmelo-Silver，2003)。协作学习是各种学科的研究对象，如发展心理学(如社会认知冲突)、社会心理学(个人知觉、动机、群体过程)、社会学(地位、权力和权威)、认知心理学(学习如何发生、学习结果)和社会文化视角(文化对互动的影响、学习的中介)。这些不同的观点表明，需要各种方法工具来理解协作交互。本次研讨会中的每篇论文都探讨了检验协作交互质量的一种或多种方法。讨论将集中于对协作工作进行良好分析的标准以及各种方法的优点和局限性。协作学习环境是复杂的野兽，通常需要多种方法来理解交互作用(Hmelo-Silver，2003)。就像Rummel&Spada，2004，我们认为从多个角度考虑协作过程很重要。协作学习是各种学科的研究对象，如发展心理学(如社会认知冲突)、社会心理学(个人知觉、动机、群体过程)、社会学(地位、权力和权威)、认知心理学(学习如何发生、学习结果)和社会文化视角(文化对互动的影响、学习的中介)。这些不同的观点表明，需要各种方法工具来理解协作交互。我们考虑使用方法学工具来检查过程的质量和相互作用的轨迹。分析数据的两种常用方法是对个别学习者的陈述进行分类，并对成绩单进行描述性、定性分析。使用第一种方法的研究人员使用了一系列不同的方法来对个别学生的陈述进行分类，从对个别学生使用的认知策略(如阐述或解释)进行分类(Webb&Farivar，2000)到对给予或接受帮助等动作进行分类。这一一般方法提供了关于个人在群体中的表现的信息，但没有提供群体话语的整体结构或流动的图景，也没有提供个体如何对这种整体结构或流动做出贡献的图景。使用第二种更具描述性的方法的研究人员提供了丰富的互动图景，但这种方法不太适合在不同的群体或讨论中进行系统比较。本次研讨会中的每篇论文都探讨了检验协作交互质量的一种或多种方法。Chin讨论了分析议论文的五种不同方法，指出了每种方法对语篇质量的定性和定量理解的优势和局限性。O‘Donnell研究了如何根据个人在对话中对他人的影响来追踪他们的贡献。Hmelo-Silver、Chernobilsky和Mastov讨论了有助于解释复杂协作学习环境的表示法。Erkens和Janssen讨论了如何通过可靠和有效的自动编码机制使对话行为的编码更加容易处理。布里吉德·巴伦将对这些陈述发表评论。小组成员和讨论者之间的讨论将侧重于对协作工作进行良好分析的标准。考察我们集体用来检查群体互动质量的方法的范围，我们将讨论成功捕捉群体互动的丰富性的方法学工具应该满足的标准，以及不同方法的局限性。
It is important to consider collaborative processes from multiple perspectives because collaborative learning environments are complex, often requiring multiple methodological approaches to understand their different aspects (Hmelo-Silver, 2003). Collaborative learning is the subject of study in a wide variety of disciplines such as developmental psychology (e.g., sociocognitive conflict), social psychology (person perception, motivation, group processes), sociology (status, power and authority), cognitive psychology (how learning occurs, learning outcomes) and sociocultural perspectives (cultural influence on interaction, mediation of learning). These different perspectives suggest that a variety of methodological tools are needed to understand collaborative interactions. Each of the papers in this symposium explores one or more methods for examining the quality of collaborative interactions. The discussion will focus on criteria for good analyses of collaborative work as well as strengths and limitations of various methods. Collaborative learning environments are complex beasts, often requiring multiple methodological approaches to understanding interactions (Hmelo-Silver, 2003). Like Rummel & Spada, 2004, we argue that it is important to consider collaborative processes from multiple perspectives. Collaborative learning is the subject of study in a wide variety of disciplines such as developmental psychology (e.g., socio-cognitive conflict), social psychology (person perception, motivation, group processes), sociology (status, power and authority), cognitive psychology (how learning occurs, learning outcomes) and sociocultural perspectives (cultural influence on interaction, mediation of learning). These different perspectives suggest that a variety of methodological tools are needed to understand collaborative interactions. We consider methodological tools that examine the quality of processes and trajectories of interactions. Two commonly used approaches for analyzing data are to classify individual learners’ statements and to provide descriptive, qualitative analyses of transcripts. Researchers using the first approach have used a diverse range of approaches to classifying individual students’ statements, ranging from classifying cognitive strategies (such as elaboration or explanation) used by individual students (Webb & Farivar, 2000) to classifying moves such as giving or receiving help. This general approach provides information about individuals’ performance within groups but does not provide a picture of the overall structure or flow of the group discourse or how individuals contribute to this overall structure or flow. Researchers using the second, more descriptive approach have provided rich pictures of interactions, but this is not a method that is well suited for making systematic comparisons across different groups or discussions. Each of the papers in this symposium explores one or more methods for examining the quality of collaborative interactions. Chinn discusses five different approaches to analyzing argumentative discourse, noting the strengths and limitations of each approach for generating both qualitative and quantitative understandings of discourse quality. O’Donnell examines how individual contributions during dialogue can be traced in terms of their influence on others. Hmelo-Silver, Chernobilsky, and Mastov discuss representations that can aid in the interpretation of complex collaborative learning environments. Erkens and Janssen discuss how the coding of dialogue acts can be made more tractable through reliable and valid automated coding mechanisms. Brigid Barron will comment on the presentations. The discussions among panelists and the discussant will include a focus on criteria for good analyses of collaborative work. Examining the range of methods that we have collectively used to examine the quality of group interactions, we will discuss criteria that should be met by methodological tools that succeed at capturing the richness of group interaction and the limitations of the different approaches.
DOI：
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发表时间：
1996-11
期刊：
The Journal of chemical physics
影响因子：
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作者：
M. Cole
通讯作者：
M. Cole