Understanding the challenges and requirements for facilitating iStar learning: An empirical study with iStar learners

Context: As research into the iStar framework continues, more researchers are recognizing its important role in requirements analysis. However, the steep learning curve of the iStar framework hinders widespread adoption in practice. An increasing number of recent studies focus on the practical application of the iStar framework, revealing difficulties in learning and practicing iStar. Objective: This paper aims to investigate and provide a thorough understanding of the challenges faced in learning and practicing the iStar modeling framework, utilizing empirical research and grounded theory. Method: Accordingly, we systematically designed and conducted an empirical study that involved ten iStar learners and three iStar lecturers to discover the difficulties of learning iStar. Utilizing the revised Bloom's taxonomy, we formulated our research questions and, based on the study results, developed a systematic theory about these difficulties. We then elicited a series of requirements to facilitate iStar learning employing Strauss and Corbin's coding paradigm from grounded theory. Furthermore, we implemented and deployed an online prototype tool inspired by this study to provide (semi-)automatic support for iStar learning and practicing. Results: The study identified key difficulties both learners and lecturers face when engaging with the iStar framework. Through grounded theory, we developed a systematic understanding of these challenges and formulated requirements to address them. These requirements were implemented into a prototype tool, aiming to facilitate iStar learning and practice. Conclusions: This paper presents an empirical study involving both beginners and lecturers in iStar modeling, providing valuable insights into the difficulties faced in learning and teaching the iStar framework. By addressing these challenges through derived strategies, proposed requirements, and the developed tool, we aim to ease the learning curve of iStar, thereby promoting its wider adoption in both educational and practical contexts.