Artificial Intelligence and Computer-Supported Collaborative Learning in Programming: A Systematic Mapping Study

Tecnura Pub Date : 2023-01-01 DOI:10.14483/22487638.19637
Carlos Giovanny Hidalgo Suarez, V. Bucheli-Guerrero, H. Ordóñez-Eraso
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引用次数: 0

Abstract

Objective: The Computer-Supported Collaborative Learning (CSCL) approach integrates artificial intelligence (AI) to enhance the learning process through collaboration and information and communication technologies (ICTs). In this sense, innovative and effective strategies could be designed for learning computer programming. This paper presents a systematic mapping study from 2009 to 2021, which shows how the integration of CSCL and AI supports the learning process in programming courses. Methodology: This study was conducted by reviewing data from different bibliographic sources such as Scopus, Web of Science (WoS), ScienceDirect, and repositories of the GitHub platform. It employs a quantitative methodological approach, where the results are represented through technological maps that show the following aspects: i) the programming languages used for CSCL and AI software development; ii) CSCL software technology and the evolution of AI; and iii) the ACM classifications, research topics, artificial intelligence techniques, and CSCL strategies. Results: The results of this research help to understand the benefits and challenges of using the CSCL and AI approach for learning computer programming, identifying some strategies and tools to improve the process in programming courses (e.g., the implementation of the CSCL approach strategies used to form groups, others to evaluate, and others to provide feedback); as well as to control the process and measure student results, using virtual judges for automatic code evaluation, profile identification, code analysis, teacher simulation, active learning activities, and interactive environments, among others. However, for each process, there are still open research questions. Conclusions: This work discusses the integration of CSCL and AI to enhance learning in programming courses and how it supports students' education process. No model integrates the CSCL approach with AI techniques, which allows implementing learning activities and, at the same time, observing and analyzing the evolution of the system and how its users (students) improve their learning skills with regard to programming. In addition, the different tools found in this paper could be explored by professors and institutions, or new technologies could be developed from them.
程序设计中的人工智能和计算机支持的协作学习:一个系统的映射研究
目标:计算机支持的协作学习(CSCL)方法集成了人工智能(AI),通过协作和信息通信技术(ICT)来增强学习过程。从这个意义上讲,可以为学习计算机程序设计创新和有效的策略。本文从2009年到2021年进行了一项系统的映射研究,展示了CSCL和人工智能的集成如何支持编程课程的学习过程。方法:本研究通过审查Scopus、Web of Science(WoS)、ScienceDirect和GitHub平台存储库等不同书目来源的数据进行。它采用了定量的方法论方法,通过技术图来表示结果,技术图显示了以下方面:一)用于CSCL和人工智能软件开发的编程语言;ii)CSCL软件技术和人工智能的发展;以及iii)ACM分类、研究主题、人工智能技术和CSCL策略。结果:本研究的结果有助于理解使用CSCL和人工智能方法学习计算机编程的好处和挑战,确定一些策略和工具来改进编程课程中的过程(例如,CSCL方法策略的实施,用于组建小组,其他用于评估,其他用于提供反馈);以及控制过程和测量学生成绩,使用虚拟法官进行自动代码评估、档案识别、代码分析、教师模拟、主动学习活动和互动环境等。然而,对于每一个过程,仍然存在着悬而未决的研究问题。结论:这项工作讨论了CSCL和人工智能的结合,以增强编程课程的学习,以及它如何支持学生的教育过程。没有任何模型将CSCL方法与人工智能技术相结合,从而实现学习活动,同时观察和分析系统的演变,以及用户(学生)如何提高编程学习技能。此外,教授和机构可以探索本文中发现的不同工具,也可以从中开发新技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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