A guideline for the methodology chapter in computer science dissertations
Marco Araujo

TL;DR
This paper provides a comprehensive guideline for structuring the methodology chapter in computer science dissertations, covering research strategies, philosophies, data collection, analysis, and ethical considerations.
Contribution
It offers an in-depth, structured framework for developing research methodology in computer science dissertations, integrating various research paradigms and ethical standards.
Findings
Detailed overview of research strategies including experiments and surveys.
Explanation of research philosophies like positivism and constructivism.
Guidance on data collection, analysis, and ethical considerations.
Abstract
Rather than simply offering suggestions, this guideline for the methodology chapter in computer science dissertations provides thorough insights on how to develop a strong research methodology within the area of computer science. The method is structured into several parts starting with an overview of research strategies which include experiments, surveys, interviews and case studies. The guide highlights the significance of defining a research philosophy and reasoning by talking about paradigms such as positivism, constructivism and pragmatism. Besides, it reveals the importance of types of research including deductive and inductive methodologies; basic versus applied research approaches. Moreover, this guideline discusses data collection and analysis intricacies that divide data into quantitative and qualitative typologies. It explains different ways in which data can be collected…
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Taxonomy
TopicsTeaching and Learning Programming · Model-Driven Software Engineering Techniques · Software Engineering Techniques and Practices
