Problem
Research questions and friction points this paper is trying to address.
Software Engineering Self-Efficacy
Scale Development
Undergraduate Computing Students
Measurement
Validity and Reliability
Design, development, and preliminary validity and reliability evidence of the Software Engineering Self-Efficacy Scale (SESES)
🤖 AI Summary
This study addresses the absence of dedicated assessment instruments for undergraduate software engineering self-efficacy by developing and validating the Software Engineering Self-Efficacy Scale. Methodologically, a domain-specific model encompassing five dimensions, including requirements analysis and teamwork, was constructed and empirically tested using exploratory factor analysis with principal axis factoring and Promax oblique rotation. Results indicate that the scale identifies five distinct latent factors, collectively accounting for 57% of the total variance, while demonstrating satisfactory reliability and validity metrics. By filling this measurement gap within the specialized domain of software engineering, this research provides a scientifically rigorous and effective instrument for evaluating undergraduate instructional outcomes.
📝 Abstract
The purpose of this research is to design, develop, implement, and provide preliminary validity and reliability evidence of the Software Engineering Self-Efficacy Scale (SESES). Framed by a conceptual framework using guidance in software engineering curriculum and concepts along with the notion of self-efficacy, we generated an initial item pool of n = 87 items to operationalize and measure software engineering self-efficacy among undergraduate computing students. The conceptual framework traces five dimensions: 1) Requirements Engineering, 2) Teamwork and Collaboration, 3) Software Quality Management, 4) Software Design and Architecture, and 5) Software Agile Methodologies. We pilot tested the SESES with n = 527 undergraduate computing students who had completed a software engineering course in the current semester or a previous academic semester. We employed Exploratory Factor Analysis (EFA) with the Principal Axis Factoring method and an oblique (Promax) rotation to examine the underlying structure of the SESES, resulting in the same five internally consistent latent constructs in the conceptual framework with minimal cross-loading and a simple structure in the pattern matrix, explaining approximately 57% of the variability in these data. Our findings suggest that software engineering self-efficacy is a multidimensional construct of five theorized and correlated, yet distinct latent factors. We unpack the limitations and delimitations of the research while exploring undergraduate computing students' software engineering self-efficacy using necessary domain-specific measurements.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Software Engineering Self-Efficacy Scale
Exploratory Factor Analysis
Multidimensional Construct
Scale Development
Undergraduate Computing Education
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