Knowledge Management Concepts For Training By Project An observation of the case of project management education

Project management education programmes are often proposed in higher education to give students competences in project planning (Gantt’s chart), project organizing, human and technical resource management, quality control and also social competences (collaboration, communication), emotional ones (empathy, consideration of the other, humour, ethics), and organizational ones (leadership, political vision, and so on). This training is often given according a training-by-project type of learning with case studies. This article presents one course characterized by a pedagogical organization based upon Knowledge Management (KM) concepts: knowledge transfer and construction throughout a learning circle and social interactions. The course is supported by a rich and complex tutor organization. We have observed this course by using another KM method inspired from KADS with various return of experience formalized into cards and charts. Our intention is, according to the model of Argyris and Sch"on (Smith, 2001), to gain feedback information about local and global processes and about actors’ experience in order to improve the course. This paper describes precisely the course (pedagogical method and tutor activity) and the KM observation method permitting to identify problem to solve. In our case, we observe problem of pedacogical coordination and skills acquisition. We propose to design a metacognitive tool for tutors and students, usable for improving knowledge construction and learning process organisation

💡 Research Summary

The paper investigates a university‑level project‑management education program that aims to equip students with a wide spectrum of competencies: technical skills such as Gantt‑chart planning, resource allocation, and quality control; social skills like collaboration and communication; emotional skills including empathy, humor, and ethics; and organizational abilities such as leadership and political vision. Traditionally, such programs rely on a “training‑by‑project” approach, using case studies and hands‑on projects to convey knowledge. The authors argue that this conventional model often suffers from poor coordination between content and instructors, ambiguous assessment criteria, and a lack of systematic knowledge construction, which together hinder effective skill acquisition.

To address these shortcomings, the authors redesign the course around Knowledge Management (KM) principles, specifically the concepts of knowledge transfer and knowledge construction within a learning circle. The learning circle consists of five iterative phases: (1) goal setting, (2) knowledge acquisition, (3) knowledge application, (4) feedback and reflection, and (5) readjustment. At each phase, learners interact with a multi‑layered tutor network rather than a single lecturer. The tutor organization includes a principal tutor who oversees the whole curriculum, auxiliary tutors who guide specific tasks, peer tutors who facilitate student‑to‑student review, and external experts who bring industry‑level case material. This structure mirrors KM’s network‑based knowledge sharing, aiming to reduce bottlenecks and enrich the learning experience with diverse perspectives.

For observation and analysis, the authors adopt a method inspired by KADS (Knowledge Acquisition and Documentation Structuring). They capture every activity, participant, objective, output, problem, and feedback on standardized “cards.” These cards are then aggregated into visual charts that map the temporal flow of the course, revealing where coordination failures or knowledge gaps occur. The analysis uncovers two primary issues: (a) misalignment between curriculum content and tutor interpretation, leading to inconsistent assessment, and (b) vague competency metrics that prevent students from accurately gauging their progress. Both problems generate redundancy, omission, and reduced learner motivation.

To mitigate these issues, the authors propose a metacognitive tool designed for both students and tutors. The tool comprises three modules: (i) a learning‑log module where students record activities and insights in real time; (ii) a feedback‑loop module that allows tutors to review logs instantly and provide targeted comments; and (iii) a knowledge‑mapping module that visualizes the learner’s conceptual network, highlighting mastered areas and remaining gaps. By making learners’ meta‑cognitive data visible, the tool operationalizes Argyris and Schön’s double‑loop learning theory: students continuously question and revise their underlying assumptions, while tutors adapt their guidance based on concrete evidence of student cognition. This reduces coordination costs, clarifies assessment criteria, and promotes a more transparent knowledge‑construction process.

The paper concludes with a roadmap for future work. First, empirical validation of the metacognitive tool through longitudinal studies is needed to quantify its impact on competency development. Second, integrating AI‑driven recommendation engines could automate personalized learning pathways and resource suggestions. Third, the authors suggest testing the KM‑based design across other disciplines and educational contexts to assess its generalizability.

In sum, the study demonstrates that embedding Knowledge Management concepts into project‑management education—through a structured learning circle, a sophisticated tutor network, and a metacognitive support system—can substantially improve knowledge transfer, reduce systemic inefficiencies, and enhance the acquisition of both technical and soft skills. This provides a robust, evidence‑based model for redesigning practice‑oriented curricula in higher education.