Problem
Research questions and friction points this paper is trying to address.
corporate education
software engineering
training perception
sociodemographic variables
professional trajectory
It's Not About Whom You Train: An Analysis of Corporate Education in Software Engineering
🤖 AI Summary
This study investigates how sociodemographic and occupational variables shape software engineering practitioners’ perceptions of the quality and effectiveness of corporate training programs. Drawing on survey data from 282 Brazilian professionals, the authors conduct non-parametric significance tests to cross-analyze 27 training perception indicators against nine predictor variables. Findings reveal that mandatory participation is the dominant influence on perceived training outcomes, while years of experience exert a nonlinear effect. Senior technical roles exhibit a pronounced gap in soft skills training. Although gender differences do not manifest in training experiences themselves, they are evident in access to training opportunities. Among 243 examined variable combinations, only 35 demonstrate statistical significance, with career-related factors—such as experience, job level, and domain—showing greater explanatory power than personal background characteristics.
📝 Abstract
Context: Corporate education is a strategic investment in the software industry, but little is known about how different professional profiles perceive these initiatives. Objective: To investigate whether sociodemographic and professional variables influence the perception of quality and effectiveness of corporate training in Software Engineering (SE). Method: Non-parametric significance tests were applied to data from a survey with 282 Brazilian professionals, crossing 27 perception items with 9 sociodemographic variables (gender, age, education level, state, experience, professional level, company size, area of work, and nature of participation), totaling 243 combinations. Results: Of the 243 combinations tested, only 35 showed statistical significance. Training mandatoriness was the dominant factor, affecting 24 of 27 items. Length of experience revealed a non-linear descriptive pattern with a low-engagement zone between 3 and 6 years. Differences by area of work indicated an expressive gap in soft skills training for advanced technical roles. Personal profile variables and company size produced no relevant significant differences. Conclusion: Personal profile variables do not determine the perception of quality and effectiveness, while professional trajectory variables (experience, level, area of work) produce localized differences. The voluntariness of participation remains a determining factor, in line with the literature. The absence of gender differences in a sample with 23\% women suggests that barriers operate before training, in access and representation, not during the learning experience.
Innovation
Methods, ideas, or system contributions that make the work stand out.
corporate training
software engineering education
perception analysis
non-parametric testing
professional trajectory
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