3 resultados para engineering students
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
One of the Psychology challenges, especially among the assessment and educational areas, is to understand and predict individual differences. In this context, this research aimed to verify the personality styles of students with high and low academic performance. The study included 236 university students from Petrolina-PE and Juazeiro-BA campus of the UNIVASF (Universidade Federal do Vale do São Francisco). They were uniformly distributed in four disciplines (medicine, psychology, administration and civil engineering), 10 students from each semester (five highest scores average students and five lowest scores average students) took place of the sample. The Millon Index Personality Styles (MIPS) was applied to analyze the personality/behavioral styles of the students. The MIPS is a 180 dichotomous (true/false) item scale. It was also developed and applied a questionnaire about the students characteristics and their academic information. Descriptive and central tendency statistics analysis (mean, standard deviation, frequency and percentage) were done to provide sample information. Then we performed a Mann-Whitney test in the overall sample and in each course and a factorial ANOVA. The results suggest that the university population is heterogeneous and there are significant differences (p <0.05) between the personality styles of students with high and low academic performance, when analyzing the overall sample and in courses of different areas of knowledge. Students of Medicine who have higher performance as personality styles prevalent the conformism and compliance, while students with lower income in this course, the styles are: innovation and discrepancy. Psychology students with higher income are more systematic and lower income students to score significantly on accommodation. The civil engineering students of the two groups differed only in personality style intuition, being such a style more characteristic of higher income students. Students of Management with higher yield stand out more in the style of the doubt and lower yields in these styles: individual, reflection and discrepancy. This study is correlational, but had an exploratory nature because there are no studies about this relationship in Brazil. Therefore, it provided a better understanding of the action characteristics of students with high and low academic performance. Further studies using the Big Five Personality Factors instruments are required because it is the most used model in understanding the influence of personality on students performance. This way, the relation between personality and academic performance will be better discussed. Otherwise, it will be possible to compare with the existing studies in the area
Resumo:
Soft skills and teamwork practices were identi ed as the main de ciencies of recent graduates in computer courses. This issue led to a realization of a qualitative research aimed at investigating the challenges faced by professors of those courses in conducting, monitoring and assessing collaborative software development projects. Di erent challenges were reported by teachers, including di culties in the assessment of students both in the collective and individual levels. In this context, a quantitative research was conducted with the aim to map soft skill of students to a set of indicators that can be extracted from software repositories using data mining techniques. These indicators are aimed at measuring soft skills, such as teamwork, leadership, problem solving and the pace of communication. Then, a peer assessment approach was applied in a collaborative software development course of the software engineering major at the Federal University of Rio Grande do Norte (UFRN). This research presents a correlation study between the students' soft skills scores and indicators based on mining software repositories. This study contributes: (i) in the presentation of professors' perception of the di culties and opportunities for improving management and monitoring practices in collaborative software development projects; (ii) in investigating relationships between soft skills and activities performed by students using software repositories; (iii) in encouraging the development of soft skills and the use of software repositories among software engineering students; (iv) in contributing to the state of the art of three important areas of software engineering, namely software engineering education, educational data mining and human aspects of software engineering.
Resumo:
Soft skills and teamwork practices were identi ed as the main de ciencies of recent graduates in computer courses. This issue led to a realization of a qualitative research aimed at investigating the challenges faced by professors of those courses in conducting, monitoring and assessing collaborative software development projects. Di erent challenges were reported by teachers, including di culties in the assessment of students both in the collective and individual levels. In this context, a quantitative research was conducted with the aim to map soft skill of students to a set of indicators that can be extracted from software repositories using data mining techniques. These indicators are aimed at measuring soft skills, such as teamwork, leadership, problem solving and the pace of communication. Then, a peer assessment approach was applied in a collaborative software development course of the software engineering major at the Federal University of Rio Grande do Norte (UFRN). This research presents a correlation study between the students' soft skills scores and indicators based on mining software repositories. This study contributes: (i) in the presentation of professors' perception of the di culties and opportunities for improving management and monitoring practices in collaborative software development projects; (ii) in investigating relationships between soft skills and activities performed by students using software repositories; (iii) in encouraging the development of soft skills and the use of software repositories among software engineering students; (iv) in contributing to the state of the art of three important areas of software engineering, namely software engineering education, educational data mining and human aspects of software engineering.