Automated Author Profile
Bonavolontà, Gianmarco

Current S-Index

1.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.8

Average Dataset Index per dataset

Total Datasets

Total datasets for this author

Average FAIR Score

31.7%

Average FAIR Score per dataset

Total Citations

Total citations to the author's datasets

Total Mentions

Total mentions of the author's datasets

S-Index Interpretation

The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.

What it means:

A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
It provides a single number to track your research data impact over time

Current S-Index: 1.6 (sum of 2 datasets Dataset Index scores)

More information here.

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Intelligenza artificiale ed elementi per la progettazione educativa riflessioni pedagogiche (Version: 1.0)

The article explores the Artificial Intelligence (AI) definitions and its significant impact on daily life, drawing attention to the debate on education. The difficulties in defining AI are used to develop a reflection aimed at understanding its role as a meta-technology, through a special-pedagogical view, emphasizing the importance of understanding and including its scope in educational design.

Authors

Bonavolontà, Gianmarco ;
Pagliara, Silvio Marcello

0 Citations0 Mentions50% FAIR1.2 Dataset Index

10.1285/i24995835v2024n20p4January 2024

Nuove tecnologie e Mooc per la formazione, il lavoro e per i Neet (Version: 1.0)

Nowadays, online education can be a new way of achieving and mastering the knowledge and skills required by the changes in today's complex society, which is characterised by increasing uncertainty, further marginalisation and social exclusion as well as inequalities in terms of income, life expectancy and employment opportunities. The present paper aims to offer food for thought on the convergence between the new online learning environments (MOOCs) and the training of the inactive population living in a condition of inequality and social exclusion. The discussion of the topic is not intended to be exhaustive but to stimulate and open a broader debate.