Random and systematic errors in pairwise computer programming: A systematic review

Authors

DOI:

https://doi.org/10.4108/eetsis.vi.3377

Keywords:

Computer programming, higher education, artificial intelligence, big data

Abstract

In this article, a systematic review is carried out to identify random and systematic errors in studies on computer programming in pairs in higher education students. Methodologically, we applied the fundamentals of the PRISMA statement. One thousand one hundred eighty articles were selected from the Scopus, Web of Science, and IEEE Xplore databases. After a filtering process, the final sample was 23 23 articles. The results showed that couple programming has positive effects. The existence of both random and systematic errors was observed, which questions the internal and external validity. Further research is needed to establish the benefits of couple programming more precisely.

References

Sibarani EM, Scerri S, Morales C, Auer S, Collarana D. Ontology-guided Job Market Demand Analysis: A Cross-Sectional Study for the Data Science field. Proceedings of the 13th International Conference on Semantic Systems, New York, NY, USA: Association for Computing Machinery; 2017, p. 25–32. https://doi.org/10.1145/3132218.3132228.

Prüfer J, Prüfer P. Data science for entrepreneurship research: studying demand dynamics for entrepreneurial skills in the Netherlands. Small Bus Econ 2020;55:651–72. https://doi.org/10.1007/s11187-019-00208-y.

Moreno MCC, Castro GLG. Unveiling Public Information in the Metaverse and AI Era: Challenges and Opportunities. Metaverse Basic and Applied Research 2023;2:35. https://doi.org/10.56294/mr202335.

Lali K, Chakor A. Improving the Security and Reliability of a Quality Marketing Information System: A Priority Prerequisite for Good Strategic Management of a Successful Entrepreneurial Project. Data & Metadata 2023;2:40. https://doi.org/10.56294/dm202340.

Verdesoto GJZ, Soto IBR, Alfaro AC. Contributions of neurosciences, neuromarketing and learning processes in innovation. Salud, Ciencia y Tecnología 2023;3:396–396. https://doi.org/10.56294/saludcyt2023396.

Woszczynski AB, Guthrie TC, Shade S. Personality and programming. Journal of Information Systems Education 2005;16:293.

Tobón AB. Diagnóstico de los estudiantes de ingeniería en diseño de entretenimiento digital para facilitar el aprendizaje de los fundamentos de programación. Actas de Diseño 2021.

Gonzalez-Argote D. Thematic Specialization of Institutions with Academic Programs in the Field of Data Science. Data & Metadata 2023;2:24–24. https://doi.org/10.56294/dm202324.

Watson C, Li FWB. Failure rates in introductory programming revisited. Proceedings of the 2014 conference on Innovation & technology in computer science education, New York, NY, USA: Association for Computing Machinery; 2014, p. 39–44. https://doi.org/10.1145/2591708.2591749.

Compañ-Rosique P, Molina-Carmona R, Satorre-Cuerda R. Effects of Teaching Methodology on the Students’ Academic Performance in an Introductory Course of Programming. In: Zaphiris P, Ioannou A, editors. Learning and Collaboration Technologies. Designing Learning Experiences, Cham: Springer International Publishing; 2019, p. 332–45. https://doi.org/10.1007/978-3-030-21814-0_25.

Gonzalez-Argote D. Immersive environments, Metaverse and the key challenges in programming. Metaverse Basic and Applied Research 2022;1:6. https://doi.org/10.56294/mr20226.

Tiwari P, Chaudhary S, Majhi D, Mukherjee B. Comparing research trends through author-provided keywords with machine extracted terms: A ML algorithm approach using publications data on neurological disorders. Iberoamerican Journal of Science Measurement and Communication 2023;3. https://doi.org/10.47909/ijsmc.36.

Miceli JE, Castro M, Cordova DD. When links build networks: brief history about the Antropocaos Group. AWARI 2020;1:e013–e013. https://doi.org/10.47909/awari.61.

Zaina RZ, Ramos VFC, Araujo GM de. Automated triage of financial intelligence reports. Advanced Notes in Information Science 2022;2:24–33. https://doi.org/10.47909/anis.978-9916-9760-3-6.115.

Martínez R. Tipos de Métricas de calidad para validar datasets gubernamentales Argentinos. Revista Abierta de Informática Aplicada 2022;6:40–53. https://doi.org/10.59471/raia20224.

Contreras DEÁ, Pérez CMD, Morales RH. Factores académicos asociados al proceso de investigación formativa en las instituciones educativas del sector oficial de Sincelejo, Sucre. Región Científica 2023;2:202319–202319. https://doi.org/10.58763/rc202319.

Sánchez RM. Transformando la educación online: el impacto de la gamificación en la formación del profesorado en un entorno universitario. Metaverse Basic and Applied Research 2023;2:47. https://doi.org/10.56294/mr202347.

Fitzpatrick B, Collins-Sussman B. Team Geek: A Software Developer’s Guide to Working Well with Others. O’Reilly Media, Inc.; 2012.

Adeliyi A, Wermelinger M, Kear K, Rosewell J. Investigating Remote Pair Programming In Part-Time Distance Education. Proceedings of the 2021 Conference on United Kingdom & Ireland Computing Education Research, New York, NY, USA: Association for Computing Machinery; 2021, p. 1–7. https://doi.org/10.1145/3481282.3481290.

Andrade-Girón D, Carreño-Cisneros E, Mejía-Dominguez C, Marín-Rodriguez W, Villarreal-Torres H. Comparison of Machine Learning Algorithms for Predicting Patients with Suspected COVID-19. Salud, Ciencia y Tecnología 2023;3:336–336. https://doi.org/10.56294/saludcyt2023336.

Benadé T, Liebenberg J. Pair Programming as a Learning Method Beyond the Context of Programming. Proceedings of the 6th Computer Science Education Research Conference, New York, NY, USA: Association for Computing Machinery; 2017, p. 48–55. https://doi.org/10.1145/3162087.3162098.

Denner J, Werner L, Campe S, Ortiz E. Pair Programming: Under What Conditions Is It Advantageous for Middle School Students? Journal of Research on Technology in Education 2014;46:277–96. https://doi.org/10.1080/15391523.2014.888272.

Isong B, Moemi T, Dladlu N, Motlhabane N, Ifeoma O, Gasela N. Empirical Confirmation of Pair Programming Effectiveness in the Teaching of Computer Programming. 2016 International Conference on Computational Science and Computational Intelligence (CSCI), 2016, p. 276–81. https://doi.org/10.1109/CSCI.2016.0060.

Nawrocki J, Wojciechowski A. Experimental evaluation of pair programming. European Software Control and Metrics (Escom) 2001:99–101.

Vanoy RJA. STEM Education as a Teaching Method for the Development of XXI Century Competencies. Metaverse Basic and Applied Research 2022;1:21. https://doi.org/10.56294/mr202221.

Parrish A, Smith R, Hale D, Hale J. A field study of developer pairs: productivity impacts and implications. IEEE Software 2004;21:76–9. https://doi.org/10.1109/MS.2004.1331306.

Arévalo YB, García MB. Scientific production on dialogical pedagogy: a bibliometric analysis. Data & Metadata 2023;2:7. https://doi.org/10.56294/dm20237.

Soto IBR, Marín-Rodriguez WJ, Baldeos-Ardían LA, Líoo-Jordán F de M, Villanueva-Cadenas DI, Soledispa-Cañarte BJ, et al. Teacher training, work, profession in the pandemic and post-pandemic context. Salud, Ciencia y Tecnología 2023;3:338–338. https://doi.org/10.56294/saludcyt2023338.

Júnior EM da S, Dutra ML. A roadmap toward the automatic composition of systematic literature reviews. Iberoamerican Journal of Science Measurement and Communication 2021;1:1–22. https://doi.org/10.47909/ijsmc.52.

Pallás JMA, Villa JJ. Métodos de investigación clínica y epidemiológica. Elsevier España; 2004.

Machuca-Contreras F, Canova-Barrios C, Castro MF. Una aproximación a los conceptos de innovación radical, incremental y disruptiva en las organizaciones. Región Científica 2023;2:202324–202324. https://doi.org/10.58763/rc202324.

Salleh N, Mendes E, Grundy J. The effects of openness to experience on pair programming in a higher education context. 2011 24th IEEE-CS Conference on Software Engineering Education and Training (CSEE&T), 2011, p. 149–58. https://doi.org/10.1109/CSEET.2011.5876082.

Salleh N, Mendes E, Grundy J, Burch GStJ. An empirical study of the effects of personality in pair programming using the five-factor model. 2009 3rd International Symposium on Empirical Software Engineering and Measurement, 2009, p. 214–25. https://doi.org/10.1109/ESEM.2009.5315997.

Cano CAG, Castillo VS, Gallego TAC. Mapping the Landscape of Netnographic Research: A Bibliometric Study of Social Interactions and Digital Culture. Data & Metadata 2023;2:25. https://doi.org/10.56294/dm202325.

Satratzemi M, Stelios X, Tsompanoudi D. Distributed Pair Programming in Higher Education: A Systematic Literature Review. Journal of Educational Computing Research 2023;61:546–77. https://doi.org/10.1177/07356331221122884.

Xu F, Correia A-P. Adopting distributed pair programming as an effective team learning activity: a systematic review. J Comput High Educ 2023. https://doi.org/10.1007/s12528-023-09356-3.

Sánchez Meca J. Cómo realizar una revisión sistemática y un meta-análisis. Aula abierta 2010.

Sánchez Serrano S, Pedraza Navarro I, Donoso González M. ¿Cómo hacer una revisión sistemática siguiendo el protocolo PRISMA?: Usos y estrategias fundamentales para su aplicación en el ámbito educativo a través de un caso práctico. Bordón: Revista de pedagogía 2022;74:51–66.

39. Alexander PA. Methodological Guidance Paper: The Art and Science of Quality Systematic Reviews. Review of Educational Research 2020;90:6–23. https://doi.org/10.3102/0034654319854352.

Pigott TD, Polanin JR. Methodological Guidance Paper: High-Quality Meta-Analysis in a Systematic Review. Review of Educational Research 2020;90:24–46. https://doi.org/10.3102/0034654319877153.

Stern C, Lizarondo L, Carrier J, Godfrey C, Rieger K, Salmond S, et al. Methodological guidance for the conduct of mixed methods systematic reviews. JBI Evidence Synthesis 2020;18:2108. https://doi.org/10.11124/JBISRIR-D-19-00169.

Rodríguez FJ, Price KM, Boyer KE. Exploring the Pair Programming Process: Characteristics of Effective Collaboration. Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, New York, NY, USA: Association for Computing Machinery; 2017, p. 507–12. https://doi.org/10.1145/3017680.3017748.

Demir E, Bilgin MH, Karabulut G, Doker AC. The relationship between cryptocurrencies and COVID-19 pandemic. Eurasian Econ Rev 2020;10:349–60. https://doi.org/10.1007/s40822-020-00154-1.

Beasley ZJ, Johnson AR. The Impact of Remote Pair Programming in an Upper-Level CS Course. Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 1, New York, NY, USA: Association for Computing Machinery; 2022, p. 235–40. https://doi.org/10.1145/3502718.3524772.

Domino MA, Collins RW, Hevner AR. Controlled experimentation on adaptations of pair programming. Inf Technol Manage 2007;8:297–312. https://doi.org/10.1007/s10799-007-0016-8.

Ghobadi S, Campbell J, Clegg S. Pair programming teams and high-quality knowledge sharing: A comparative study of coopetitive reward structures. Inf Syst Front 2017;19:397–409. https://doi.org/10.1007/s10796-015-9603-0.

Gold-Veerkamp C, Klopp M, Abke J. Pair Programming as a Didactical Approach in Higher Education and its Evaluation. 2019 IEEE Global Engineering Education Conference (EDUCON), 2019, p. 1055–62. https://doi.org/10.1109/EDUCON.2019.8725150.

Zacharis N. Evaluating the Effects of Virtual Pair Programming on Studentsâ?? Achievement and Satisfaction. International Journal of Emerging Technologies in Learning (IJET) 2009;4:34–9.

Tsompanoudi D, Satratzemi M, Xinogalos S. Distributed pair programming using collaboration scripts: An educational system and initial results. Informatics in Education 2015;14:291–314.

Kavitha RK, Ahmed MSI. Knowledge sharing through pair programming in learning environments: An empirical study. Educ Inf Technol 2015;20:319–33. https://doi.org/10.1007/s10639-013-9285-5.

McDowell C, Werner L, Bullock H, Fernald J. The effects of pair-programming on performance in an introductory programming course. Proceedings of the 33rd SIGCSE technical symposium on Computer science education, New York, NY, USA: Association for Computing Machinery; 2002, p. 38–42. https://doi.org/10.1145/563340.563353.

Ummadi S, Shravani B, Rao NR, Reddy MS, Sanjeev B. Overview on controlled release dosage form. System 2013;7:51–60.

Sfetsos P, Stamelos I, Angelis L, Deligiannis I. An experimental investigation of personality types impact on pair effectiveness in pair programming. Empir Software Eng 2009;14:187–226. https://doi.org/10.1007/s10664-008-9093-5.

Sison R. Investigating the Effect of Pair Programming and Software Size on Software Quality and Programmer Productivity. 2009 16th Asia-Pacific Software Engineering Conference, 2009, p. 187–93. https://doi.org/10.1109/APSEC.2009.71.

Xinogalos S, Satratzemi M, Chatzigeorgiou A, Tsompanoudi D. Student perceptions on the benefits and shortcomings of distributed pair programming assignments. 2017 IEEE Global Engineering Education Conference (EDUCON), 2017, p. 1513–21. https://doi.org/10.1109/EDUCON.2017.7943050.

Zacharis NZ. Measuring the Effects of Virtual Pair Programming in an Introductory Programming Java Course. IEEE Transactions on Education 2011;54:168–70. https://doi.org/10.1109/TE.2010.2048328.

Smith MO, Giugliano A, DeOrio A. Long Term Effects of Pair Programming. IEEE Transactions on Education 2018;61:187–94. https://doi.org/10.1109/TE.2017.2773024.

Han K-W, Lee E, Lee Y. The Impact of a Peer-Learning Agent Based on Pair Programming in a Programming Course. IEEE Transactions on Education 2010;53:318–27. https://doi.org/10.1109/TE.2009.2019121.

Vanhanen J, Lassenius C. Effects of pair programming at the development team level: an experiment. 2005 International Symposium on Empirical Software Engineering, 2005., 2005, p. 10 pp.-. https://doi.org/10.1109/ISESE.2005.1541842.

Swamidurai R, Dennis B, Kannan U. Investigating the impact of peer code review and pair programming on test-driven development. IEEE SOUTHEASTCON 2014, 2014, p. 1–5. https://doi.org/10.1109/SECON.2014.6950664.

Demir Ö, Seferoglu SS. The Effect of Determining Pair Programming Groups According to Various Individual Difference Variables on Group Compatibility, Flow, and Coding Performance. Journal of Educational Computing Research 2021;59:41–70. https://doi.org/10.1177/0735633120949787.

Saltz JS, Shamshurin I. Does pair programming work in a data science context? An initial case study. 2017 IEEE International Conference on Big Data (Big Data), 2017, p. 2348–54. https://doi.org/10.1109/BigData.2017.8258189.

Gehringer EF. A pair-programming experiment in a non-programming course. Companion of the 18th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications, New York, NY, USA: Association for Computing Machinery; 2003, p. 187–90. https://doi.org/10.1145/949344.949397.

Williams L, McCrickard DS, Layman L, Hussein K. Eleven Guidelines for Implementing Pair Programming in the Classroom. Agile 2008 Conference, 2008, p. 445–52. https://doi.org/10.1109/Agile.2008.12.

Mascarenhas HAD, Dias TMR. Academic education data as a source for analysis of the migration process for training. Advanced Notes in Information Science 2022;2:53–62. https://doi.org/10.47909/anis.978-9916-9760-3-6.91.

Subbarayan S, Gunaseelan HG. A Review of Data and Document Clustering pertaining to various Distance Measures. Salud, Ciencia y Tecnología 2022;2:194–194. https://doi.org/10.56294/saludcyt2022194.

Mascarenhas HAD, Dias TMR, Dias PM. Adoption of Network Analysis Techniques to Understand the Training Process in Brazil. AWARI 2020;1:e004–e004. https://doi.org/10.47909/awari.63.

Martins DL. Data science teaching and learning models: focus on the Information Science area. Advanced Notes in Information Science 2022;2:140–8. https://doi.org/10.47909/anis.978-9916-9760-3-6.100.

Bennedsen J, Caspersen ME. Failure rates in introductory programming. SIGCSE Bull 2007;39:32–6. https://doi.org/10.1145/1272848.1272879.

Takaki P, Dutra M. Data science in education: interdisciplinary contributions. Advanced Notes in Information Science 2022;2:149–60. https://doi.org/10.47909/anis.978-9916-9760-3-6.94.

Espinoza ELO, Ayala ACN, Yovera SER y, Soto FGC, Vilela AJM. Design Thinking como herramienta para fomentar la innovación y el emprendimiento. Salud, Ciencia y Tecnología 2023;3:368–368. https://doi.org/10.56294/saludcyt2023368.

Campbell DT, Stanley JC. Experimental and Quasi-Experimental Designs for Research. Ravenio Books; 2015.

Fernández P, Vallejo G, Livacic-Rojas P, Tuero E. Validez Estructurada para una investigación cuasi-experimental de calidad. Se cumplen 50 años de la presentación en sociedad de los diseños cuasi-experimentales. Anales de Psicología / Annals of Psychology 2014;30:756–71. https://doi.org/10.6018/analesps.30.2.166911.

Larrosa JMC, Galgano F, Gutiérrez E. Kinship network evolution in Argentina. An exploration based on online data. AWARI 2022;3. https://doi.org/10.47909/awari.150.

Downloads

Published

23-05-2023

How to Cite

1.
Girón DA, Rosas JS, Marín-Rodriguez W, Cisneros EC, Diaz-Ronceros E, Villarreal-Torres H. Random and systematic errors in pairwise computer programming: A systematic review. EAI Endorsed Scal Inf Syst [Internet]. 2023 May 23 [cited 2024 May 6];10(4):e22. Available from: https://publications.eai.eu/index.php/sis/article/view/3377

Most read articles by the same author(s)