4 Contributo in Atti di Convegno (Proceeding)

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Ritorno ad Alcuino di York: resoconto di un progetto didattico interdisciplinare sulle 'Propositiones ad acuendos iuvenes'

The contribution illustrates the outcomes of an interdisciplinary teaching project that involved students in a second class of a scientific high school in Palermo in s.y. 2018-2019. The activity was coordinated by the teachers of Latin (Prof. Li Causi) and Mathematics (Prof. Modica), and ended with the publication on a web page of the cooperative translation of a group of problems taken from the Propositiones ad acuendos iuvenes of Alcuin of York (735-804 AD), a philosopher and theologian act...

Game Changing Matrix: un approccio innovativo alla progettazione di giochi per il cambiamento

Negli ultimi anni, l’esperienza ludica, sia attraverso giochi analogici che digitali, ha dimostrato di essere un potente strumento per promuovere cambiamenti sociali, comportamentali ed educativi. Nonostante la crescente attenzione a questo tema, manca un consolidamento di metodologie pratiche per la progettazione di tali giochi. Per colmare questo vuoto, il lavoro presenta la Game Changing Matrix, uno strumento innovativo che unisce approcci metodologici già ampiamente utilizzati nel mondo ...

Performative methodologies and transformative learning: a systematic review

Through a review of the literature of the last twenty years, the article explores the use of theatrical performance methodologies. The objectives are the reconstruction and systematization of intervention proposals and survey instruments used to investigate the transformations that have occurred in participants. The purpose is to identify trajectories and research tools capable of recording rational and emotional dimensions, both of which are involved in transformative learning and in perform...

Introducing Intrinsic Motivation in Elastic Decision Transformers

Artificial Intelligence (AI) both in general and in its current predominant version, mostly based on connectionist tenets, lives in the paradox of aiming to reproduce and simulate the workings of an immensely complex system, the biological brain, which are still to a large extent unknown. This gives us latitude for some interesting domain interplay: concepts from the cognitive sciences can be used to improve AI models, while AI can be used in data science mode to analyze cognitive processes i...

Analysing the impact of brain-inspired predictive coding dynamics through gradient based explainability methods

Multiple theories exist for the role of feedback connections in the brain and in the artificial neural networks, but remain untested using modern tools. In this work, we undertake this task by exploring the utility of explainability methods like GradCAMs[1] in investigating bio-inspired recurrent networks–provided with the predify[2] package–that perform hierarchical updates inspired by the predictive coding theory in neuroscience. We report an extensive search with different levels of feedfo...

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