学习理论在计算机教育研究中的应用及其关系

IF 3.2 3区 工程技术 Q1 EDUCATION, SCIENTIFIC DISCIPLINES ACM Transactions on Computing Education Pub Date : 2022-12-29 DOI:https://dl.acm.org/doi/10.1145/3487056
Claudia Szabo, Judy Sheard
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引用次数: 0

摘要

在研究和实践中使用既定的和学科特定的理论是一个学科成熟的标志。随着计算机教育研究作为一门相对年轻的学科,最近人们对研究可能被证明是该领域工作基础的理论产生了兴趣,其中包括学科特定的理论和来自其他学科的许多理论。研究人员面临的挑战是识别和选择为他们的工作提供最佳基础的理论。学习是一个复杂和多方面的过程,因此,大量的理论可能适用于一个研究问题。了解可能的候选理论,了解它们之间的关系和潜在的适用性,无论是单独的还是作为一个理论群体,对于为研究人员和实践者提供一个全面的基础是很重要的。在这项工作中,我们研究了计算机教育研究和实践的基础学习理论之间的基本联系。我们建立了84个学习理论及其来源和有影响力的论文的综合列表,这些论文是在研究界介绍或传播特定理论的论文。使用Scopus、ACM数字图书馆和Google Scholar,我们确定了引用这些学习理论的论文。随后,我们考虑了这些理论的所有可能组合,并建立了引用每个组合的论文集。在这个学习理论连接的加权图上,我们进行了社区分析,以确定紧密联系的学习理论组。我们发现,大多数计算教育学习理论与许多更广泛的学习理论密切相关,形成了一个由17个学习理论组成的独立集群。我们建立了理论关系的分类,以确定学习理论之间的联系深度。在分析的294个链接中,我们发现32个链接存在深度关联。这表明,虽然计算教育研究界意识到大量的学习理论,但仍需要更好地了解学习理论是如何联系起来的,以及如何将它们结合起来使用,以使计算教育研究和实践受益。
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Learning Theories Use and Relationships in Computing Education Research

The use of established and discipline-specific theories within research and practice is an indication of the maturity of a discipline. With computing education research as a relatively young discipline, there has been recent interest in investigating theories that may prove foundational to work in this area, with discipline-specific theories and many theories from other disciplines emerging as relevant. A challenge for the researcher is to identify and select the theories that provide the best foundation for their work. Learning is a complex and multi-faceted process and, as such, a plethora of theories are potentially applicable to a research problem. Knowing the possible candidate theories and understanding their relationships and potential applicability, both individually or as a community of theories, is important to provide a comprehensive grounding for researchers and practitioners alike.

In this work, we investigate the fundamental connections between learning theories foundational to research and practice in computing education. We build a comprehensive list of 84 learning theories and their source and influential papers, which are the papers that introduce or propagate specific theories within the research community. Using Scopus, ACM Digital Library, and Google Scholar, we identify the papers that cite these learning theories. We subsequently consider all possible pairs of these theories and build the set of papers that cite each pair. On this weighted graph of learning theory connections, we perform a community analysis to identify groups of closely linked learning theories. We find that most of the computing education learning theories are closely linked with a number of broader learning theories, forming a separate cluster of 17 learning theories. We build a taxonomy of theory relationships to identify the depth of connections between learning theories. Of the 294 analysed links, we find deep connections in 32 links. This indicates that while the computing education research community is aware of a large number of learning theories, there is still a need to better understand how learning theories are connected and how they can be used together to benefit computing education research and practice.

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来源期刊
ACM Transactions on Computing Education
ACM Transactions on Computing Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
6.50
自引率
16.70%
发文量
66
期刊介绍: ACM Transactions on Computing Education (TOCE) (formerly named JERIC, Journal on Educational Resources in Computing) covers diverse aspects of computing education: traditional computer science, computer engineering, information technology, and informatics; emerging aspects of computing; and applications of computing to other disciplines. The common characteristics shared by these papers are a scholarly approach to teaching and learning, a broad appeal to educational practitioners, and a clear connection to student learning.
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