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

Salleh, Norsaremah; Mendes, Emilia; Grundy, John

doi:10.1007/s10664-012-9238-4

Cited by 70 publications

(41 citation statements)

References 89 publications

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“…They did not find evidence for distinguishing the performance of paired students between different levels of either conscientiousness or neuroticism. Additionally, Salleh et al [70] investigated the effects of the FFM traits on PP's effectiveness. More specifically they investigated if differences in Neuroticism, Conscientiousness and Openness levels affected the paired students' academic performance.…”

Section: Studies On Personality and Software Developmentmentioning

confidence: 99%

Personality, emotional intelligence and work preferences in software engineering: An empirical study

Kosti

Feldt

Angelis

2014

Information and Software Technology

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Context: There is an increasing awareness among Software Engineering (SE) researchers and practitioners that more focus is needed on understanding the engineers developing software. Previous studies show significant associations between the personalities of software engineers and their work preferences.Objective: Various studies on personality in SE have found large, small or no effects and there is no consensus on the importance of psychometric measurements in SE. There is also a lack of studies employing other psychometric instruments or using larger datasets. We aim to evaluate our results in a larger sample, with software engineers in an earlier state of their career, using advanced statistics.Method: An operational replication study where extensive psychometric data from 279 master level students have been collected in a SE program at a Swedish University. Personality data based on the Five-Factor Model, Trait Emotional Intelligence Questionnaire and Self-compassion have been collected. Statistical analysis investigated associations between psychometrics and work preferences and the results were compared to our previous findings from 47 SE professionals.Results: Analysis confirms existence of two main clusters of software engineers; one with more "intense" personalities than the other. This corroborates our earlier results on SE professionals. The student data also show similar associations between personalities and work preferences. However, for other associations there are differences due to the different population of subjects. We also found connections between the emotional intelligence and work preferences, while no associations were found for self-compassion. Conclusion:The associations can help managers to predict and adapt projects and tasks to available staff. The results also show that the Emotional Intelligence instrument can be predictive. The research methods and analytical tools we employ can detect subtle associations and reflect differences between different groups and populations and thus can be important tools for future research as well as industrial practice.

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Section: Studies On Personality and Software Developmentmentioning

confidence: 99%

Personality, emotional intelligence and work preferences in software engineering: An empirical study

Kosti

Feldt

Angelis

2014

Information and Software Technology

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“…The study reported that "openness played a significant role in differentiating paired students' academic performance. Students reported that PP not only caused an increase in satisfaction and confidence levels, but also brought enjoyment to the tutorial classes and enhanced students' motivation" (Salleh, Mendes, & Grundy, 2014). Karn and Cowling (2006) looked at enforcing teamwork in online courses to encourage studentto-student interaction and reported that student's anxiety was elevated and that they did not care for teamwork.…”

Section: Literature Reviewmentioning

confidence: 99%

Student Preferences and Performance in Online and Face-to-Face Classes Using Myers-Briggs Indicator: A Longitudinal Quasi-Experimental Study_

Boghikian-Whitby¹,

Mortagy²

2016

InSITE Conference

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This longitudinal, quasi-experimental study investigated students' cognitive personality type using the Myers-Briggs personality Type Indicator (BMTI) in Internet-based Online and Face-toFace (F2F) modalities. A total of 1154 students enrolled in 28 Online and concurrent 32 F2F sections taught over a period of fourteen years. The study measured whether the sample is similar to the national average percentage frequency of all 16 different personality types; whether specific personality type students preferred a specific modality of instructions and if this preference changed over time; whether learning occurred in both class modalities; and whether specific personality type students learned more from a specific modality. Data was analyzed using regression, t-test, frequency, and Chi-Squared. The study concluded that data used in the study was similar to the national statistics; that no major differences in preference occurred over time; and that learning did occur in all modalities, with more statistically significant learning found in the Online modality versus F2F for Sensing, Thinking, and Perceiving types. Finally, Sensing and Thinking (ST) and Sensing and Perceiving (SP) group types learned significantly more in Online modality versus F2F.

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“…The techniques used in these studies, which are very diverse, are the effect of an operationalization of a particular theoretical model that investigates personality [7][8]. There is a need to deepen and replicate research for the population of programmers.…”

Section: A Models Of Personality and Their Operationalization Inmentioning

confidence: 99%

“…PMO is intended for testing many different tools, such as NEO-PI-R, NEO-FFI, and IPIP. NEO-FFI is an instrument which is used in this study due to its reliability and validity and due to its common usage to measure the personality in academic field [28][29]. Careful analysis of the literature allowed to make a decision to input PMO as a theoretical framework, which is operationalized in the form of the NEO-FFI instrument.…”

Section: ) Extraversion (E) Indicatesmentioning

confidence: 99%

Psychosocial Correlates of Software Designers' Professional Aptitude

Suslow¹,

Kowalczyk²,

Statkiewicz³

et al. 2015

ijacsa

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Abstract-This paper presents quantitative results of the first phase of empirical research carried out within the framework of the interdisciplinary project InfoPsycho that was initiated in 2013 at the Koszalin University of Technology and the University of Gdansk. The aim of the study was to identify the personality traits that characterize successful applicants for university studies in the field of software development. Synthetic indicators of quality and performance of their design tasks and exercises were selected as the criteria for candidates' professional skills. To measure personality traits, the NEO-FFI questionnaire was used, based on the five-factor model by Costa and McCrae. Preliminary results show that expected young designers (N=140) score high on neuroticism and introversion as compared with those designers whose design documentation is of poor quality. They also show a high degree of conscientiousness, which can be seen when their performance of exercises and programming tasks is being evaluated.

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

Cited by 70 publications

References 89 publications

Personality, emotional intelligence and work preferences in software engineering: An empirical study

Personality, emotional intelligence and work preferences in software engineering: An empirical study

Student Preferences and Performance in Online and Face-to-Face Classes Using Myers-Briggs Indicator: A Longitudinal Quasi-Experimental Study_

Psychosocial Correlates of Software Designers' Professional Aptitude

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