协作质量核心维度关系的确定:一种多维标度方法

Georgios Kahrimanis, Irene-Angelica Chounta, N. Avouris
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引用次数: 1

摘要

计算机支持的协作学习(CSCL)是智能网络和协作系统技术研究和实践中发展最广泛的范例之一。研究领域的跨学科涉及对CSCL分析的几种方法方法的应用,从对小型互动丰富的合作事件的深层次定性分析,到对适当分类的互动事件的定量测量,这些事件被用作合作在某些方面成功的指标[1]。本文采用了CSCL分析的另一种方法,旨在利用这些不同方法趋势的一些期望属性,包括使用评估协作质量的评级方案[2,3]。在定义了一组涵盖协作的最重要方面的维度之后,它使用经过适当训练的人类代理为每个维度分配协作质量评级,基于他们对协作的实质性方面的评估,这些方面不容易正式确定。这里研究的活动涉及228个协作双元,使用synnergo工具同步完成计算机科学问题解决任务[4]。在此大型数据集的基础上,基于使用多维尺度技术统计阐述的协作质量评级,在实证基础上揭示了协作质量维度之间的关系[5,6,7,8,9,10,11]。得到的结果与所使用的额定值方案的初始设计一致,并进一步细化了它所定义的尺寸之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determining Relations Between Core Dimenisons of Collaboration Quality: A Multidimensional Scaling Approach
Computer Supported Collaborative Learning (CSCL) constitutes one of the most extensively developed paradigms of research and practice in intelligent networking and collaborative systems technology. Interdisciplinarity in the research field involves the application of several methodological approaches towards analysis of CSCL that range from deep-level qualitative analyses of small interaction-rich episodes of collaboration, to quantitative measures of suitably categorized events of interaction that are used as indicators of the success of collaboration in some of its facets [1]. This article adopts an alternative approach to CSCL analysis that aims at taking advantage of some desired properties of each of these diverse methodological trends, involving the use of a rating scheme for the assessment of collaboration quality [2,3]. After defining a set of dimensions that cover the most important aspects of collaboration, it employs appropriately trained human agents to assign ratings of collaboration quality to each dimension, basing their assessments on substantial aspects of collaboration that are not easily formal sable. The activities studied here regard 228 collaborating dyads, working synchronously on a computer science problem-solving task with the use of the Synergo tool [4]. Based on this large dataset, relations between dimensions of collaboration quality are unraveled on empirical grounds, based on the ratings of collaboration quality that were elaborated statistically using a multidimensional scaling technique [5,6,7,8,9,10,11]. Results obtained are in accordance with the initial design of the rating scheme used, and further particularize the relations between the dimensions it defines.
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