Teaching Practically Relevant Research Problem Formulation in Software Engineering with Lean Research Inception

2026-03-20

AI Summary

This study addresses the persistent gap between software engineering research and industrial practice, which often leaves students struggling to formulate meaningful research questions. It introduces, for the first time, the Lean Research Initiation (LRI) method into software engineering education as a structured approach to guide students in developing research problems aligned with real-world industry needs. A case study conducted at a Brazilian university involved 60 students and 7 instructors in a pedagogical intervention. Results indicate that over 60% of students demonstrated significant improvement in problem articulation, clarity, and contextualization. Furthermore, 57.1% of instructors reported that students’ research questions became notably clearer and more structured, and 85.7% strongly endorsed the LRI approach. This work offers a scalable instructional paradigm for bridging the academia–industry divide in software engineering education.

Technology Category

• Knowledge Representation and Reasoning: Knowledge Engineering
• Application Domains: Software Engineering
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

Abstract

[Background] Well-formulated Software Engineering (SE) research problems are essential for bridging the gap between industry-academia. Lean Research Inception (LRI) aims to support this activity. [Goal] Apply LRI to support SE students in formulating practice-aligned research problems. [Method] We conducted a case study with 60 students and 7 faculty advisors of a Brazilian university. [Results] Students reported benefits in reasoning (60%), clarity and definition (61.7%), contextualization (60%), and communication (50%). Advisors also observed clearer and more structured problems (57.1%) with a high recommendation rate (85.7%). [Conclusion] LRI can be a promising approach to support practice-aligned research problem formulation in SE education.

Problem

• Software Engineering
• Research Problem Formulation
• Industry-Academia Gap
• Practice-Aligned Research
• Lean Research Inception

Innovation

• Lean Research Inception
• research problem formulation
• software engineering education
• industry-academia alignment
• case study