Personalised learning in project management education: Insights from an artificial intelligence-driven chatbot
Helgi Þór Ingason et al.
What the paper says
The increasing complexity of project-based work in contemporary organisations calls for a transformation in how project management is taught. Traditional teaching approaches struggle to support self-directed, context-sensitive, and motivationally engaging learning experiences—skills that are critical for preparing future project leaders. In this context, there is growing interest in the potential of artificial intelligence-powered tools to enhance the quality and adaptability of educating future project managers. This paper explores the application of artificial intelligence-driven chatbots in university-level project management education through the lens of the two-year international project ”XXXX” conducted across four European countries. Using an action design research methodology, the project iteratively developed and tested a chatbot in three versions, progressively integrating feedback from students and educators. The study suggests that artificial intelligence-based chatbots hold significant promise for supporting personalised learning journeys and increasing student motivation; however, their integration requires careful design, ongoing dialogue within the teaching community, and a strong alignment with pedagogical objectives. • AI chatbots enhance student motivation and support tailored learning in project management education. • AI chatbots modernise management education and enrich teachers’ toolkits. • AI chatbots can be valuable tools in blended learning environments. • Continued support and training are critical for the successful adoption and alignment of AI chatbots with teaching styles. • The responsible use of AI chatbots is essential for educators and learners in diverse contexts.
4 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.37 × 0.4 = 0.15 |
| M · momentum | 0.60 × 0.15 = 0.09 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.