Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Conference Object Citation - Scopus: 7An Exploration of Individual Personality Types in Software Development(Springer Verlag, 2014) O'Connor, R.V.; Clarke, P.; Yilmaz, M.Previous research - using conventional psychometric questionnaires - has highlighted the importance of aligning compatible personality types in software development teams. However, there does not exist a dedicated, robust questionnaire instrument for revealing the pertinent personality types for software development practitioners. This study analyzes the validity and reliability of a 70-item (context dependent) personality-profiling questionnaire particularly developed to assess personality types of software practitioners. A systematic process of validation, using an iterative approach to questionnaire development, was employed. The questions were developed both with a qualitative analysis of interview data, and based on the opinions of expert reviewers who revised the items through a set of examination. To investigate how stable the questions and reproducible the results, we measured test-retest reliability of the instrument, yielding satisfactory results. The present study provided evidence for the construct validity of the instrument. Ultimately, an initial comparison of the results delivered by the instrument demonstrated positive correlations with the findings acquired with well-known personality assessment instrument, i.e. the big five personality questionnaire. © Springer-Verlag Berlin Heidelberg 2014.Conference Object Citation - Scopus: 7A Machine-Based Personality Oriented Team Recommender for Software Development Organizations(Springer Verlag, 2015) Al-Taei, A.; O’Connor, R.V.; Yilmaz, M.Hiring the right person for the right job is always a challenging task in software development landscapes. To bridge this gap, software firms start using psychometric instruments for investigating the personality types of software practitioners. In our previous research, we have developed an MBTI-like instrument to reveal the personality types of software practitioners. This study aims to develop a personality-based team recommender mechanism to improve the effectiveness of software teams. The mechanism is based on predicting the possible patterns of teams using a machine-based classifier. The classifier is trained with empirical data (e.g. personality types, job roles), which was collected from 52 software practitioners working on five different software teams. 12 software practitioners were selected for the testing process who were recommended by the classifier to work for these teams. The preliminary results suggest that a personality-based team recommender system may provide an effective approach as compared with ad-hoc methods of team formation in software development organizations. Ultimately, the overall performance of the proposed classifier was 83.3%. These findings seem acceptable especially for tasks of suggestion where individuals might be able to fit in more than one team. © Springer International Publishing Switzerland 2015.