SETF: A Structured Engineering Thesis Framework for Artificial Intelligence, Software Engineering, and Robotics

Writing high-quality graduation theses in technical domains such as Artificial Intelligence (AI), Software Engineering (SE), and Robotics requires more than general academic writing skills; it demands structured integration between engineering development and scientific reporting. However, existing academic writing approaches remain largely generic and fail to address domain-specific methodological requirements. To address this gap, this paper introduces the Structured Engineering Thesis Framework (SETF), a domain-aware conceptual framework that formalizes the thesis development lifecycle as an integrated, workflow-driven process. SETF systematically connects problem definition, literature review, methodology design, implementation, evaluation, writing, and revision into a coherent and iterative model that enhances methodological consistency, reproducibility, and clarity. Unlike traditional approaches that treat writing as a post-development activity, SETF redefines thesis preparation as an integral part of the research process. The framework is demonstrated through a case study involving an AI-based chatbot system, illustrating its applicability in real-world academic contexts. SETF is proposed as both a conceptual contribution and a standardized reference model that can be adopted and cited to improve the quality and structure of engineering theses, supporting publication-oriented research in modern engineering education. This work was conducted at Arab International University (AIU), Damascus, Syria.Official website: https://www.aiu.edu.sy