Effectiveness Of Pair Programming Research Articles

Effect of Knowledge-Based Team Composition on Effectiveness of Pair Programming

Over years variety of tools has been used in the class room to support student learning. Among them, pair programming is trending as a pedagogical tool for programming courses in higher education. Implementation of pair programming is inadequate, choosing the right factors for successful adoption of this method is vital. This study aims at investigating the effect of knowledge-based team composition on effectiveness of pair programming. First year students following HNDIT at ATI Gampaha in the academic year 2020 had participated for the experiment. Data was collected using four instruments. The final exam scores, assignment scores, questionnaire, code quality. Mann Whitney U test is used to analyze assignment score and exam score and the code quality was determined by the defect density. The results revealed that students who had paired performed better in the assignments and they had graded better in the final exam as well. Knowledge based pair programming has positively affected code quality also. Further it reports willingness among students to use pair programming in the academic field when they are paired in a compatible way. Thus, it can be concluded that knowledge based team composition has positively affected to pair programming. These results are consistent with those of other studies that have done on the same topic.

Collaborative dialogue patterns of pair programming and their impact on programming self‐efficacy and coding performance

AbstractThe purpose of this study was to investigate the collaborative dialogue patterns of pair programming and their impact on programming self‐efficacy and coding performance for both slow‐ and fast‐paced students. Forty‐six postgraduate students participated in the study. The students were asked to solve programming problems in pairs; those pairs' conversations were recorded when they worked on their tasks. Data analysis methods, including lag sequential analysis, cluster analysis and paired t‐test, were employed, and the results showed that (1) four collaborative dialogue patterns emerged: Lecture, Guide, Question and Answer (Q&A), and Inquiry patterns; (2) Guide and Inquiry patterns significantly increased programming self‐efficacy for both fast‐ and slow‐paced students while Lecture and Q&A patterns significantly increased programming self‐efficacy for slow‐paced students but not for fast‐paced students; (3) Guide and Inquiry patterns played a significant role in improving coding performance for slow‐paced students. The study reveals a complex relationship between collaborative dialogue patterns with programming self‐efficacy and coding performance, critically affecting students' pair programming quality. Further details of the findings are also discussed. Practitioner notesWhat is already known about this topic Pair programming is promising in promoting problem solving and knowledge transfer and is widely used in programming education. There are different patterns observed in the pair programming process. Collaborative dialogue patterns found in “expert‐novice” pair programming were derived from a single programming task. What this paper adds Four collaborative dialogue patterns of pair programming emerged by increasing the different tasks and experiment duration and expanding the sample size, which further verified the stability of the similar patterns in previous studies. Four collaborative dialogue patterns showed different significant impacts on different students' programming self‐efficacy and coding performance. This study presents the finer‐grained characteristics of collaborative interaction in programmer pairs and contributes to the explanation regarding the different effects of pair programming reported in previous studies. Implications for practice and/or policy Four collaborative dialogue patterns can help the teachers understand the collaborative process of pair programming between fast‐ and slow‐paced students. The collaborative dialogue patterns can be used to formulate effective intervention strategies to stimulate the process of collaboration in pairs and applied in future programming education to provide a new path for cultivating and promoting students' programming abilities. It is worth further investigating the impact of collaborative dialogue patterns on students' computational thinking.

Three Contrasting Pairs’ Collaborative Programming Processes in China’s Secondary Education

Pair programming is a collaborative learning mode to foster novice learners’ computer programming. Previous empirical research has reported contrasting conclusions about the effect of pair programming on student learning. To further understand students’ pair programming, this study uses a mixed method to analyze three contrasting pairs’ collaborative behaviors, discourses, and perceptions from a multi-dimensional perspective. The analysis results show that the high-ranked student pair is characterized as the interactive, socially-supportive, and goal-oriented pair; the middle-ranked student pair is characterized as the highly-interactive, socially-supportive, and process-oriented pair; and the low-ranked student pair is characterized as the lowly-interactive, socially-unsupportive, and programming-distracted pair. The research reveals complex relations between collaborative behaviors, discourses, and performances, which have critical influences on students’ pair programming quality. Based on the results, this research proposes pedagogical, analytical, and theoretical implications for future instructional design, learning analytics, and empirical research of collaborative programming.

Exploring pair programming beyond computer science: a case study in its use in data science/data engineering

While pair programming has been studied extensively when teaching computer science students, very little has been reported with respect to pair programming in a broader context. To help address this gap, this paper reports on a case study evaluating the effectiveness of pair programming within a data science course. Our findings show that pair programming can be useful for teaching data science students. In addition, while the driver role was similar to what has been described within a software development context, we note that the navigator role had an expanded set of responsibilities, which we termed researcher activities. Further research is required to explore if pair programming is also useful in other engineering domains and if the expanded navigator role is applicable in domains beyond data science/data engineering.

Long Term Effects of Pair Programming

Contribution: This paper provides evidence for the benefits of pair programming early in the curriculum on student performance later in the curriculum. It also confirms the short term benefits of partnerships at scale. Background: Engineers often work in teams, both in industry and in academia. Previous work has shown that partnered programming yields higher student performance during the course in which students partner. Research Questions: This paper investigates the long term effects of early curriculum pair programming on student performance in a following course. Specifically, do student partnerships impact long-term student performance in a later course? Are previously observed effects of partner programming robust to a larger sample size? Methodology: This quantitative analysis examines 2468 students in an introductory computer science sequence at a large, public research institution. The data set comprises two academic years and includes partnership participation, project and exam scores, withdraw rates, time between courses, GPA, and gender. Findings: A positive relationship is observed between partnering in an introductory course, and higher project scores in a future course, where all students worked alone ( $N = 1003$ ). Students with the lowest GPAs experienced the greatest benefits. Additionally, results with a large population of students confirm the observations of previous research, showing that partnerships are associated with an overall positive grade impact during the course in which the partnership takes place ( $N = 2468$ ).

대학 프로그래밍 입문 수업에서 짝 프로그래밍의 효과 : 학습성과와 학생 만족도 측면에서

대학 프로그래밍 입문 수업에서 짝 프로그래밍의 효과 : 학습성과와 학생 만족도 측면에서

A Meta-Analysis of Pair-Programming in Computer Programming Courses

Several experiments on the effects of pair programming versus solo programming in the context of education have been reported in the research literature. We present a meta-analysis of these studies that accounted for 18 manuscripts with 28 independent effect sizes in the domains of programming assignments, exams, passing rates, and affective measures. In total, our sample accounts for N = 3,308 students either using pair programming as a treatment variable or using traditional solo programming in the context of a computing course. Our findings suggest positive results in favor of pair programming in three of four domains with exception to affective measures. We provide a comprehensive review of our results and discuss our findings.

Learning motivation and retention effects of pair programming in data structures courses

Learning motivation and retention effects of pair programming in data structures courses

The Effectiveness of Pair Programming: Software Professionals' Perceptions

Researchers surveyed software professionals on their views regarding the effectiveness of pair programming compared to traditional solo programming. The survey produced three main findings. First, the respondents believed that project complexity and pair composition (the individual programmers' expertise and pair-programming experience) affect pair programming's effectiveness in terms of the effort, defect rate, knowledge transfer, and overall project cost. Second, respondents with pair-programming experience viewed pair programming more positively than those without it. Finally, the more pair-programming experience the respondents had, the more favorably they viewed pair programming.

짝 프로그래밍 학습방법이 창의적 문제해결력과 효율성에 미치는 영향

짝 프로그래밍 학습방법이 창의적 문제해결력과 효율성에 미치는 영향

Analysis of pair Programming Effectiveness in Academic Environment

Analysis of pair Programming Effectiveness in Academic Environment

Investigating the effects of personality traits on pair programming in a higher education setting through a family of experiments

Evidence from our systematic literature review revealed numerous inconsistencies in findings from the Pair Programming (PP) literature regarding the effects of personality on PP's effectiveness as ...

Empirical Studies of Pair Programming for CS/SE Teaching in Higher Education: A Systematic Literature Review

The objective of this paper is to present the current evidence relative to the effectiveness of pair programming (PP) as a pedagogical tool in higher education CS/SE courses. We performed a systematic literature review (SLR) of empirical studies that investigated factors affecting the effectiveness of PP for CS/SE students and studies that measured the effectiveness of PP for CS/SE students. Seventy-four papers were used in our synthesis of evidence, and 14 compatibility factors that can potentially affect PP's effectiveness as a pedagogical tool were identified. Results showed that students' skill level was the factor that affected PP's effectiveness the most. The most common measure used to gauge PP's effectiveness was time spent on programming. In addition, students' satisfaction when using PP was overall higher than when working solo. Our meta-analyses showed that PP was effective in improving students' grades on assignments. Finally, in the studies that used quality as a measure of effectiveness, the number of test cases succeeded, academic performance, and expert opinion were the quality measures mostly applied. The results of this SLR show two clear gaps in this research field: 1) a lack of studies focusing on pair compatibility factors aimed at making PP an effective pedagogical tool and 2) a lack of studies investigating PP for software design/modeling tasks in conjunction with programming tasks.

The Case for Pair Programming in the Computer Science Classroom

Previous studies indicate that the use of pair programming has beneficial effects on student learning. In this article, we present a controlled study that directly measured students’ acquisition of individual programming skills using laboratory practica (in which students programmed individually under exam conditions). Additionally, we analyzed other measures of student performance, attitudes, and retention. Our results provide direct evidence that pair programming improves the individual programming skills of lower SAT students, and that students who pair program are more confident in their work and are more likely to successfully complete the course. Results from the four other major studies of the effects of pair programming are reviewed and compared with those presented here in order to draw broader conclusions.

Assessing the effectiveness of distributed pair programming for an online informatics curriculum

Studies have shown that distributed pair programming improves student performance and retention in online computer science (CS) courses. However, as online CS courses become more commonly offered in computer science and Informatics departments around the country, it is imperative that distributed pair programming becomes as effective as when performed in co-located spaces such as computer labs. The present study identifies a disparity in student attitudes towards pair programming in co-located versus online environments. This study identifies several qualitative measures that can impact the pedagogical advantages of pair programming when implemented into an existing online computer science curriculum. This on-going study focuses on the online Informatics curriculum at Indiana University Bloomington and Indiana University Purdue University Indianapolis. Begun in Spring 2009, the research focuses on student experiences and perceptions of pair programming, and utilizes both quantitative and qualitative assessment methods. In order to improve the effectiveness of distributed pair programming, it is crucial to properly assess teaching and learning practices that will improve student engagement and motivation in distributed pair programming exercises. Student experience surveys, using a modified Likert scale, demonstrate that student-centered perceptions of the ease and effectiveness of pair programming differs significantly between co-located and online activities. This paper identifies several key areas where there is a noticeable variance between co-located and online pair programming experiences, and argues that addressing and improving these key areas will be vital for the successful implementation and sustainability of distributed pair programming efforts.

Simulation in Software Engineering with System Dynamics: A Case Study

There are many complexities including dynamic behavior and feedback mechanism as well as various interacting factors in the practical software development. Software Engineering education is facing difficulties because students have limited engineering experience and they can hardly understand typical phenomena occurring in software projects. System Dynamics is a continuous modeling method describing the interaction between project factors. It forces one to consider system behavior in global view. The simulation models encapsulate collective knowledge of software engineering fields. They support the training that the students can interact with to practice project control, which will help students understand the key factors and behaviors in complex scenarios. In this paper, Brooks’ Law and the effects of Pair Programming in eXtreme Programming (XP) were used as case study to demonstrate the basic concepts, analysis and modeling processes of system dynamics. The simulation results show the advantages of the approach. Finally, the uses of system dynamics approach in critical areas of software engineering are presented.

Are Two Heads Better than One? On the Effectiveness of Pair Programming

Pair programming is a collaborative approach that makes working in pairs rather than individually the primary work style for code development. Because PP is a radically different approach than many developers are used to, can be hard to predict the effects when a team switches to PP. Because projects focus on different things, this article concentrates on understanding general aspects related to effectiveness, specifically project duration, effort, and quality. Not unexpectedly, our meta-analysis showed that the question of whether two heads are better than one isn't precise enough to be meaningful. Given the evidence, the best answer is it depends - on both the programmer's expertise and the complexity of the system and tasks to be solved. Two heads are better than one for achieving correctness on highly complex programming tasks. They might also have a time gain on simpler tasks. Additional studies would be useful. For example, further investigation is clearly needed into the interaction of complexity and programmer experience and how they affect the appropriateness of a PP approach; our current understanding of this phenomenon rests chiefly on a single (although large) study. Only by understanding what makes pairs work and what makes them less efficient can we take steps to provide beneficial work conditions, to avoid detrimental conditions, and to avoid pairing altogether when conditions are detrimental. With the right cooks and the right combination of ingredients, the broth has the potential to be very good indeed.

HOW DISTRIBUTION AFFECTS THE SUCCESS OF PAIR PROGRAMMING

Recent experiments demonstrated the effectiveness of pair programming in terms of quality and productivity. Growing interest towards global software development is fostering the design of suitable methods and tools for distributing software processes, at any level of detail, from entire subprocesses up to a single activity. Consequently, people placed in different locations could also share programming tasks and related practices, such as pair programming. Unfortunately, distribution might seriously compromise the success of pair programming, due to communication and collaboration issues. We have performed an experiment in order to investigate the impact of distribution on pair programming when performing maintenance tasks. An interesting conjecture stems from the experiment: under certain conditions, distributed pair's components tend to dismiss from each other, stopping the collaborative work. This can be a very expensive risk factor to keep into account when planning tasks of distributed pair programming.

The Effects of Pair Programming on Learning Efficiency in Short Programming Assignments

Pair programming is one of the important practices of a lightweight development methodology namely eXtreme Programming (XP). It emphasizes the practice of two persons work- ing together at a single computer terminal, to design, code and test computer programs. The effects of pair programming on software development in industrial organizations were studied and it was found that pair programming increases the productivity by 15%. This evidence created an interest in amongst community of computer science educators to apply pair programming in educational settings. We have conducted an experiment with the students of computer science courses to compare the learning efficiency of students when they adopt pair programming with that of students using tradi- tional method to do laboratory exercises of short duration. The learning efficiency was measured by evaluating design documents, completion time, and marks obtained in a written test that was con- ducted after every exercise. Our research confirms that the adoption of pair programming improves the design ability, reduces time taken to do a laboratory exercise and increases the knowledge and programming skill.