Links between the personalities, styles and performance in computer programming

There are repetitive patterns in strategies of manipulating source code. For example, modifying source code before acquiring knowledge of how a code works is a depth-first style and reading and understanding before modifying source code is a breadth-first style. To the extent we know there is no study on the influence of personality on them. The objective of this study is to understand the influence of personality on programming styles. We did a correlational study with 65 programmers at the University of Stuttgart. Academic achievement, programming experience, attitude towards programming and five personality factors were measured via self-assessed survey. The programming styles were asked in the survey or mined from the software repositories. Performance in programming was composed of bug-proneness of programmers which was mined from software repositories, the grades they got in a software project course and their estimate of their own programming ability. We did statistical analysis and found that Openness to Experience has a positive association with breadth-first style and Conscientiousness has a positive association with depth-first style. We also found that in addition to having more programming experience and better academic achievement, the styles of working depth-first and saving coarse-grained revisions improve performance in programming.Comment: 27 pages, 6 figure

Modelling human factors in perceptual multimedia quality: On the role of personality and culture

Perception of multimedia quality is shaped by a rich interplay between system, context, and human factors. While system and context factors are widely researched, few studies in this area consider human factors as sources of systematic variance. This paper presents an analysis on the influence of personality (Five-Factor Model) and cultural traits (Hofstede Model) on the perception of multimedia quality. A set of 144 video sequences (from 12 short movie excerpts) were rated by 114 participants from a cross-cultural population, producing 1232 ratings. On this data, three models are compared: a baseline model that only considers system factors; an extended model that includes personality and culture as human factors; and an optimistic model in which each participant is modeled as a random effect. An analysis shows that personality and cultural traits represent 9.3% of the variance attributable to human factors while human factors overall predict an equal or higher proportion of variance compared to system factors. In addition, the quality-enjoyment correlation varied across the movie excerpts. This suggests that human factors play an important role in perceptual multimedia quality, but further research to explore moderation effects and a broader range of human factors is warranted

Identifying entrepreneurial potential? An investigation of the identifiers and features of entrepreneurship

Abstract. The paper reports a study of entrepreneurship potential amongst students at one university using a quantitative instrument to measure three of the most commonly cited predictors: access to entrepreneurial role models; urgency of entrepreneurial intent; and desire for economic autonomy. The paper reports also on qualitative interviews with those identified as most and least likely to become entrepreneurs by the measure. Results suggest that the measure is effective and that there is variation between those most and least likely to become entrepreneurs and commonalities amongst those most likely to become entrepreneurs. Of the three predictors 'desire for economic autonomy' is most influential, but the generation of this 'desire' involves various internal and external influences. Findings are of interest to educators insofar as they might identify the stage of entrepreneurial development of students and develop appropriate pedagogic responses. It has implications also for policy aimed at encouraging entrepreneurship, and entrepreneurship support

Factors Influencing girls\u27 choice of Information Technology careers

Many western nations have experienced declining numbers of women in the information technology (IT) workforce (Trauth, Nielsen, & von Hellens, 2003). Between 1996 and 2002, women in the U.S. IT workforce declined from 41% to 34.9% (ITAA, 2003). This can hamper diversity and reduce the talent pool that can address needs of diverse end-users (Florida & Gates, 2002). Why do women choose IT careers or reject them? Multidisciplinary research on career genderization reveals gender imbalance (Trauth, Nielsen, & von Hellens, 2003). Career decisions against math, science, and technology (MST) are often made as early as age 11 without understanding long-term implications (AAUW, 2000). We examine influences on girls’ choice of IT careers, modeling social, structural, and personal variables that affect IT career choice. Using Ahuja’s (2002) classification of social and structural influences on women’s IT careers, Beise, Myers, VanBrackle, and Chevli-Saroq’s (2003) model of women’s career decisions, and individual differences suggested by Trauth (2002), we extend literature to children and adolescents’ career choices. Social influences bias internal and external gender perceptions and stereotyping, role models, peers, media, and family. Institutional support such as teachers and counselors, access to technology, and same-sex versus coeducational schools are structural influences. While both can influence career decisions, social factors have the most influence on children’s early perceptions. Both factors can introduce gender-stereotyping effects on career choices. Gender stereotyping explains how girls perceive their role in society based on subtle societal cues. It can limit opportunities for both sexes. We also examine personality traits and external influences that make children unique. Their individual differences draw them to activities and content areas such as problem solving and interaction with people. Finally, ethnic culture can exert an influence on social and structural variables. Figure 1 from Adya and Kaiser (2005) presents our career choice model that is discussed in the next section

Women in Power: Examining the Pathway to the Top

As more women begin to enter the upper management ranks of the business world, researchers have recognized several patterns in terms of common factors which influence career paths and choices. Based on this, I conducted a study with the purpose of identifying those influences and traits which women in the field most attributed to their individual success. This information could thereafter be used as a guide for young women such as myself who are about to begin their own career paths within this field. Through the use of survey and individual interview, my findings indicated that individual background, family support, education, and activities were shown to be the most influential aspects of professional development, while key personality traits necessary to success as noted by the participants included a mixture of both individual (self-motivation, perseverance, etc.) and interpersonal (communication, compassion, etc.) abilities. Advice offered by respondents again emphasized the need for individual motivation combined with the strong interpersonal skills which facilitate professional relationships

Emotional Creativity: A Meta-analysis and Integrative Review

Emotional creativity (EC) is a pattern of cognitive abilities and personality traits related to originality and appropriateness in emotional experience. EC has been found to be related to various constructs across different fields of psychology during the past 30 years, but a comprehensive examination of previous research is still lacking. The goal of this review is to explore the reliability of use of the Emotional Creativity Inventory (ECI) across studies, to test gender differences and to compare levels of EC in different countries. Thirty-five empirical studies focused on EC were retrieved and the coefficients required for the meta-analysis extracted. The meta-analysis revealed that women showed significantly higher EC than men (total N = 3,555). The same gender differences were also found when testing scores from three ECI subscales, i.e. emotional novelty, emotional preparedness and emotional effectiveness/authenticity. When comparing EC in 10 different countries (total N = 4,375), several cross-cultural differences were revealed. The Chinese sample showed a significantly lower average ECI total score than all the other countries. Based on the integration of results, the avenues for future research on EC and the breadth of influence of the concept of EC across different fields of psychology are discussed. Keywords: Emotional Creativity, Review, Meta-Analyses, Meta-Analysis, Definition, Emotional Creativity Inventory, ECI, Reliability, Gender Differences, Cross-cultural, Cross-culture, Personality Traits, NEO Personality Inventory, Big Five, Extraversion, Agreeableness, Openness to Experience, Introversion, Neuroticism, Emotions, Creativity, Cognition, Cognitive Abilities, Affect, Fantasy, Coping, Alexithymia, Anhedonia, Self-understanding, Motivation, Creativeness, Innovative Performance, Creative Ability, Artistic Creativity, Creative Thinking. MeSH Headings: Emotions, Creativity, Affect, Affective Symptoms, Gender, Sex, Gender Identity, Cross-Cultural Comparison, Transcultural Studies, Temperament, Extraversion, Neuroticism, Anhedonia, Creativeness, Cognition, Cognitive Function, Artistic Creativity, Creative Ability, Creative Thinkin

Using Learning Analytics to Implement Evidence-Based Interventions to Support Ethnic Minority and International Student Social Integrations

As universities in the UK become increasingly diverse, one common challenge is how best to socially integrate ethnic minority and international students into the classroom and larger campus. Indeed, research currently demonstrates that students most often form social and learning connections with peers from the same ethnicity or culture, despite the benefits of intergroup connections. However, few studies have looked at student social networks to determine how they influence actual behaviours in group learning activities. In this research, Social Network Analysis and Learning Analytics methods will be used to explore the role of social networks in classroom participation and attainment for ethnic minority and international students, highlighting replicable interventions that can help promote social cohesion in the UK