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AI-Driven Personalisation of Project Management Learning Paths

Fast facts

  • Further publishers

    Muhammad Kemal Rais, Anwesha Mukherjee

  • Publishment

    • 2025
    • Volume 2025 IEEE European Technology and Engineering Management Summit (E-TEMS)
  • Title of the conference proceedings

    2025 IEEE European Technology and Engineering Management Summit (E-TEMS)

  • Organizational unit

  • Subjects

    • Economics in general
  • Publication format

    Conference paper

Quote

Rais, M.K., Mukherjee, A. and Albrecht, J.C., 2025. AI-Driven Personalization of Project Management Learning Paths. In: 2025 IEEE European Technology and Engineering Management Summit (E-TEMS). 2025 IEEE European Technology and Engineering Management Summit. Piscataway, NJ: IEEE, pp.131-136.

Content

This study examines the potential of AI-driven personalized learning paths for project management professionals. With the increasing demand for highly qualified project management experts, this study focuses on how AI technology, such as natural language processing, deep learning, and neural networks can be used to create highly personalized learning paths for project management professionals based on their existing knowledge, skill gaps, and learning preferences and suggest relevant certifications or courses with a focus on improving learning efficiency and effectiveness. Furthermore, this study also investigates how an AI-driven personalized learning path can be used to customise the learning content to meet learners' needs and competencies. It seeks to expand the learner's experience and overall learning success. We conducted ten interviews with key stakeholders, including project managers, project management officers, HR professionals, and certification institution experts, with the objective to explore the practical benefits of AI-driven personalized learning path implementation. The interview findings found that implementing AI-driven solutions could optimise time, targeted skill development, increase motivation and engagement, objective learning paths, personalized feedback, and provide real-time response. This study could assist practitioners and scholars who desire to implement AI-driven solutions as well as provide a foundation for evaluating the potential of AI in education.

Keywords

artificial intelligence

personalized learning path

project management

skill gap

training and development

Notes and references

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