An Empirical Study on Factors related to Distributed Pair Programming

Author:

Tsompanoudi DespinaORCID,Satratzemi MayaORCID,Xinogalos SteliosORCID,Karamitopoulos LeonidasORCID

Abstract

This paper reports students’ perceptions and experiences attending an object-oriented programming course in which they developed software using the Distributed Pair Programming (DPP) technique. Pair programming (PP) is typically performed on one computer, involving two programmers working collaboratively on the same code or algorithm. DPP on the other hand is performed remotely allowing programmers to collaborate from separate locations. PP started in the software industry as a powerful way to train programmers and to improve software quality. Research has shown that PP (and DPP) is also a successful approach to teach programming in academic programming courses. The main focus of PP and DPP research was PP’s effectiveness with respect to student performance and code quality, the investigation of best team formation strategies and studies of students’ attitudes. There are still limited studies concerning relationships between performance, attitudes and other critical factors. We have selected some of the most common factors which can be found in the literature: academic performance, programming experience, student confidence, feelgood factor, partner compatibility and implementation time. The main goal of this study was to investigate correlations between these attributes, while DPP was used as the main programming technique.

Publisher

International Association of Online Engineering (IAOE)

Subject

General Engineering,Education

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The effects of online peer-facilitated learning and distributed pair programming on students’ learning;Computers & Education;2023-10

2. Structuring Collaboration in Programming Through Personal-Spaces;Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19

3. Distributed Pair Programming in Higher Education: A Systematic Literature Review;Journal of Educational Computing Research;2022-09-20

4. Empirical research on pair programming in higher education: a literature review;Computer Science Education;2022-03-06

5. The Effect of Pair Programming on Code Maintainability;Collaboration Technologies and Social Computing;2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3