SCOPE: A System for Customized and Optimized Project Enhancement for IT Project Management
Received: 5 August 2025 | Revised: 31 August 2025, 11 September 2025, 15 September 2025, and 17 September 2025 | Accepted: 19 September 2025 | Online: 15 October 2025
Corresponding author: Jose Santisteban
Abstract
Project management in the development of Information Technology (IT) solutions faces significant challenges due to the diversity of methodologies available and the complexity of selecting the most appropriate approach for each context. Widely used tools such as Jira, Asana, Trello, Click Up, or Microsoft Project facilitate the planning and tracking of activities but do not offer personalized methodological recommendations. In the academic field, support models have been developed, such as the agile selection model based on decision trees and chatbots, or a conceptual methodology choice model, which provide structured rules and conceptual frameworks to guide the selection process. However, these models remain at the theoretical level and have not been validated in real-world environments. To address this issue, this study proposes SCOPE, a web-based system that uses Generative Artificial Intelligence (GAI) to recommend management methods tailored to the specific characteristics of each project. The solution comprises a conceptual model and technology architecture that integrates modules for authentication, task management, risk management, and intelligent assistance. Validation was performed using the Intraclass Correlation Coefficient (ICC), which yielded an average value of 0.812, indicating a level of concordance ranging from moderate to good with management experts. The System Usability Scale (SUS) also obtained an average score of 87.7. These results demonstrate that SCOPE is a practical and reliable tool to support methodological decision-making in IT projects, with potential applications in real organizational environments.
Keywords:
IT project management, generative artificial intelligence, methodological selection, decision automation, structured promptsDownloads
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Copyright (c) 2025 Camila Samamé, Diego Sapaico, Jose Santisteban
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