## 2 Literature Review
### Methodologies for Research-Oriented Projects
Action DSR is particularly effective for research-oriented projects that require hands-on testing of consulting frameworks, allowing students and researchers to observe artefact performance in practice and collect data on their effectiveness [13]. This methodology supports iterative feedback from clients and stakeholders, offering rich insights for continuous improvement and making it well suited to projects where practical engagement with stakeholders is essential [14]. By fostering collaboration between researchers and practitioners, Action DSR enhances the relevance and applicability of research outputs in addressing complex, real-world problems [15]. **Action research (AR)** is another methodology that supports iterative refinement through active involvement in real-world contexts, often used to improve practices in educational or organisational settings through cycles of planning, action, observation, and reflection [16]. In the context of cybersecurity consulting, AR allows researchers to work collaboratively with clients to identify challenges and co-develop solutions, ensuring that the developed artefacts are relevant to actual business needs. This approach is particularly useful for artefacts tested in live consulting environments, as it enables adaptive design adjustments in response to immediate feedback from stakeholders. As a widely used research methodology, **Mixed-Methods Research** complements these approaches by integrating qualitative and quantitative data to provide a comprehensive evaluation of artefact performance. For research-oriented projects within the R&D agenda, Mixed-Methods Research enables researchers to capture both measurable outcomes and user perceptions, offering a well-rounded understanding of artefact effectiveness in cybersecurity consulting. While this paper does not report empirical findings, the agenda's structure supports the future collection of both qualitative and quantitative data. For example, qualitative insights may be obtained through student reflection reports, stakeholder interviews, or observations during client simulations. Quantitative data may include metrics such as agent output accuracy, task success rates, or frequency of prompt revisions. These data types are integral to the proposed Mixed-Methods Research approach for evaluating the performance and impact of artefacts developed in Research-Oriented Projects. In summary, while all three methodologies **Reflexive DSR**, **Action DSR**, and **Action Research** support iterative refinement, they differ in their focus and approach. **Action Research** is primarily reflective and seeks to improve practices through participatory cycles, often directly involving practitioners in the research process [16]. **Action DSR**, in contrast, incorporates design principles to create artefacts that address specific problems while also generating theoretical knowledge, blending practical engagement with structured research objectives [13]. **Reflexive DSR** distinguishes itself by prioritising the researcher's continuous self-reflection on their role in shaping outcomes, thus yielding insights into how researcher bias and assumptions may influence Human-AI interactions and artefact performance [17]. A comparison of methodologies for Research-Oriented Projects is provided in Table 2.  
By understanding these distinctions, researchers within the agenda can select methodologies that align with their project goals, whether they seek practical solutions for immediate application or aim to explore the theoretical implications of their design practices. Additionally, the feasibility and design of data collection from various stakeholders, such as designers, developers, end-users, and other stakeholders, play a critical role in choosing an appropriate methodology. The selected approach must support systematic data collection and align with industry and academic requirements, thereby ensuring that insights from the projects contribute meaningfully to both practical and academic objectives.