Analyzing personality types to predict team performance

Omar, Mazni; Syed-Abdullah, Sharifah-Lailee; Hussin, Naimah Mohd

doi:10.1109/cssr.2010.5773856

Cited by 28 publications

(17 citation statements)

References 15 publications

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“…Among these factors, the formation of an unsuitable team was found to have the most impact. 38,39 Based on research by Bell, 40 team composition is a formation of team members according to their contributions in influencing the team processes and outcomes. Bell has also affirmed that the team composition research that has been carried out in past studies can be categorized into 3 types: (1) team member characteristics (eg, member abilities, demographics, personality traits, and number of team members), (2) measurement of team member characteristics, (3) and team composition developed using an analytical perspective.…”

Section: Related Workmentioning

confidence: 99%

Finding an effective classification technique to develop a software team composition model

Gilal

Jaafar

Capretz

et al. 2017

J Software Evolu Process

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Ineffective software team composition has become recognized as a prominent aspect of software project failures. Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection. It is also believed that the technique/s used while developing a model can impact the overall results. Thus, this study aims to (1) discover an effective classification technique to solve the problem and (2) develop a model for composition of the software development team. The model developed was composed of 3 predictors: team role, personality types, and gender variables; it also contained 1 outcome: team performance variable. The techniques used for model development were logistic regression, decision tree, and rough sets theory (RST). Higher prediction accuracy and reduced pattern complexity were the 2 parameters for selecting the effective technique. Based on the results, the Johnson algorithm (JA) of RST appeared to be an effective technique for a team composition model. The study has proposed a set of 24 decision rules for finding effective team members. These rules involve gender classification to highlight the appropriate personality profile for software developers. In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.

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Section: Related Workmentioning

confidence: 99%

Finding an effective classification technique to develop a software team composition model

Gilal

Jaafar

Capretz

et al. 2017

J Software Evolu Process

View full text Add to dashboard Cite

show abstract

“…Empirical data from [15][16][17][18] was used in this study. The data set consists of 120 data sets collected during two comparison studies and one case study conducted in an academic setting, where participants were software engineering (SE) students.…”

Section: Data Collectionmentioning

confidence: 99%

Finding the Effectiveness of Software Team Members Using Decision Tree

Omar

Syed-Abdullah

2015

Pattern Analysis, Intelligent Security and the Internet of Things

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This paper presents steps taken in finding the effectiveness of software team members using decision tree technique. Data sets from software engineering (SE) students were collected to establish pattern relationship among four predictor variables-prior academic achievements, personality types, team personality diversity, and software methodology-as input to determine team effectiveness outcome. There are three main stages involved in this study, which are data collection, data mining using decision tree, and evaluation stage. The results indicate that the decision tree technique is able to predict 69.17 % accuracy. This revealed that the four predictor variables are significant and thus should consider in building a team performance prediction model. Future research will be carried to obtain more data and use a hybrid algorithm to improve the model accuracy. The model could facilitate the educators in developing strategic planning methods in order to improve current curriculum in SE education.

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“…[3] proposes a framework to investigate the relationship personality traits versus software team diversity by using the notion of rough set theory. This study reveals that heterogeneous types of personalities in a software team supports creativity and effective when there are challenging tasks.…”

Section: Table I Dichotomies (The Four Oposite Pairs Of Preferences) mentioning

confidence: 99%

“…However, to improve software productivity, the social aspects such as individuals' compatibility in a team has emerged as a research interest with a focus on personality traits over software team configuration [2], which directly affects the quality of knowledge exchange among the team members. It is therefore not surprising that several researchers in the field of software engineering focus on the effects of personality types on the software development process and organizational performance [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Towards the Understanding and Classification of the Personality Traits of Software Development Practitioners: Situational Context Cards Approach

Yılmaz

O’Connor

2012

2012 38th Euromicro Conference on Software Engineering and Advanced Applications

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Abstract-This study explores the personality traits of software development practitioners by using a classification schema based on the personality traits extended on the Myers-Briggs type indicator (MBTI). To extract the information necessary for understanding and classification of software development personnel, we developed a card game playable with either single or multiple participants. The game consists of seventy cards, which have a keyword and a picture on one side and a hypothetical situation typically encountered in software development landscapes with two different selectable options on the other side. The game master (GM) reads a situation by showing the pictures to participants and elicits the most suitable answer in between two selections. Ultimately, the outcome of the game reveals the personality traits of individuals on a compatible scale with the MBTI. To evaluate our game-based personality identification method, we conduct a case study with sixteen individuals at a university environment in seven group sessions. In light of the experience gained, secondly we refine the questions and test the game on sixty software development personnel selected from a set of team based pairings at a middle size software company. Our preliminary results indicate that there are more individuals in software teams, who may perceive to be extroverted not only in a classroom environment but also in an industrial setting. Moreover, the initial results suggest that our method can be a viable to the classical paper based MBTI tests particularly for managing the workforce in software development projects.

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Analyzing personality types to predict team performance

Cited by 28 publications

References 15 publications

Finding an effective classification technique to develop a software team composition model

Finding an effective classification technique to develop a software team composition model

Finding the Effectiveness of Software Team Members Using Decision Tree

Towards the Understanding and Classification of the Personality Traits of Software Development Practitioners: Situational Context Cards Approach

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