ABSTRACT
This paper looks at how well low-code development works compared to traditional high-code software development for the BSIS students capstone projects. With low-code platforms becoming more popular and important for developers, educators, and organizations, this study compared the two methods based on how fast they are, how easy they are to learn, the quality of the code, how satisfied users are and the ability of learners core programming skills. This comparison will provide justifications for institutions to adopt low-code software development for BSIS student capstone projects. Through the use of surveys and interviews, the researcher will investigate how low-code development will affect the efficiency, flexibility, and quality of software projects in comparison to traditional coding practices. The T-test will be used to evaluate the effectiveness of low-code development in the capstone project by comparing the key performance metrics of the two approaches based on development speed, code quality, user satisfaction, learning curve, and core programming skills.
Keywords: low-code, high-code, capstone-project, programming-skills, development-speed, code-quality, user-satisfaction, learning-curves, core-programming-skills
INTRODUCTION
Low-code development platforms provide significant traction in the software development landscape, where developers can build applications rapidly and experience minimal code, which lessens the complexity of doing long codes using visual interfaces and pre-built components. These platforms contribute to accelerating the development process and reducing the hassle of making complicated codes. However, despite the growing adoption of this approach, the effectiveness of these tools compared to traditional code-based development remains a subject of debate, particularly in the context of education settings such as the capstone project.
The research capstone project is one of the major requirements of BSIS students before they graduate from the said program. Their participation typically brings them experiences in software engineering and offers the opportunity to evaluate the practical application of the development tools. The projects require technical proficiency, creativity, and problem-solving skills, which are important components for the BSIS students to possess. The choice of development approach, even if it is low-code or traditional code-based development, can influence a student’s learning experience and the quality of the final product. By this, it is crucial to justify if the student should adopt this low-code approach to their capstone project without compromising the effectiveness of their learning. This study seeks to evaluate the effectiveness of low-code development versus traditional code-based development in the context of capstone software development projects, based on its development speed, code quality, learning curves, satisfaction and core programming skills. This study aims to provide answers on how these approaches compare in an academic environment by making a statistical analysis using the T-test approach to assess whether significant differences exist between two groups of BSIS students who use low-code platforms versus those who utilize traditional coding methods in their previous System Analysis and Design course.
Hypothesis:
Null Hypothesis (H₀): There is no significant difference in the responses of two groups of the respondents in terms of development speed, learning curves , code quality, user satisfaction, and core programming skills between students using low-code platforms vs. traditional high-coding methods for their SAD project.
Alternative Hypothesis (H₁): There is a significant difference in the responses of two groups of the respondents in terms of development speed, learning curves , code quality, user satisfaction, and core programming skills between students using low-code platforms vs. traditional high-coding methods for their SAD project.
The survey results will give useful information about how well the two development approaches compare in the academic software development project. These results will either support or reject the hypotheses.
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