P-Cube educational digital game - The Urban Innovation scenario

Giancarlo Vecchi

Teaching Public Administration2025https://doi.org/10.1177/01447394251350663article
AJG 1
Weight
0.37

What the paper says

The objective of the paper is to present the structure and contents of the Urban Innovation scenario, part of the P-Cube educational digital game. The first sections develop the main elements that characterize the debate on the urban and metropolitan areas, from which the P-Cube drew the basis for the development of the game’s missions. These references formed the basis for the identification of themes on which to elaborate the missions of the game and for the search for empirical cases characterized by decision-making processes useful for writing the plot and identifying possible policy entrepreneurs and other actors. The following sections describe the Urban Innovation scenario: the theoretical premises, the objectives, and the main contents of the missions. Particularly, the aim was to introduce an interactive teaching and learning approach, supported by an educational digital game, in university courses as well as post-graduate and training activities. The complete release of the Urban Innovation scenario with its 15 missions has been tested in university and training courses, mostly with international classes, during the period 2021-2024. The results monitored were positive, in terms of increased interaction between students, the development of comparison based on different experiences, and improved learning of concepts.

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https://doi.org/https://doi.org/10.1177/01447394251350663

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@article{giancarlo2025,
  title        = {{P-Cube educational digital game - The Urban Innovation scenario}},
  author       = {Giancarlo Vecchi},
  journal      = {Teaching Public Administration},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/01447394251350663},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 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.