This article aims to demonstrate a possible relationship between quantitative methodology and qualitative methodology. It is know the eternal conflict between the two thematic areas; however researchers support a conceptual methodology that links the two methods under a theoretical and conceptual framework designed by the research problem. Research in education cannot ignore the frameworks that outline and contribute increasingly to the quantitative and qualitative approaches in the approximation of the study object. In this article the researchers build a methodological design, providing a comprehensive and coherent strategic framework, based on the epistemological ideals of a conceptual framework, outlining goals and general hypotheses. It is important to see and have a distant view of the near things that are close to us and contain a broad but close view of things. Get an idea and overview through a distant point and get a distance from a particular perspective, is the basis of our methodological research. Considering alternatives and methodology choices, led us to underline the existing advantages and disadvantages of quantitative and qualitative data. The approach itself is pragmatic because some issues that arise can be of quantitative research and other qualitative research. If researchers want to understand how is represented socially and culturally our object of study, they must consider their stories, but also a multifaceted study that requires a statistical understands.

Advanced persistent threats (APTs) pose significant risks to critical systems and infrastructures due to their stealth and persistence. While several studies have reviewed APT characteristics and defense mechanisms, this paper goes further by proposing a hybrid defense framework based on artificial intelligence and game theory. First, a literature review outlines the evolution, methodologies, and known incidents of APTs. Then, a novel conceptual framework is presented, integrating unsupervised anomaly detection (isolation forest) and strategic defense modeling (Stackelberg game). Experimental results on simulated data demonstrate the robustness and scalability of the approach. In addition to reviewing current APT detection techniques, this work presents a defense model that integrates machine learning-based anomaly detection with predictive game-theoretic modeling.