Home » Publication » 24288

Dettaglio pubblicazione

2021, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Pages 350-356 (volume: 12677)

Using Graph Embedding to Monitor Communities of Learners (04b Atto di convegno in volume)

Gasparetti F., Sciarrone F., Temperini M.

How to keep track of the learning process of a community of learners is a problem whose resolution requires accurate assessment tools and appropriate teaching and learning strategies. Peer Assessment is a standard didactic strategy which requires students in a course to correct their peers’ assignments. Since the representation of a community, even a large one, of students, is based on directed graphs, it is difficult to follow its whole dynamics. In this paper, we investigate the possibility of using two machine learning techniques: Graph Embeddings, and Principal Component Analysis, to represent a students’ communities by points in a 2D space, in order to have valuable and understandable information on the dynamics of the group. For this purpose we present a case study based on three real Peer Assessment sessions. The first results are encouraging.
ISBN: 978-3-030-80420-6; 978-3-030-80421-3
Gruppo di ricerca: Human-Computer Interaction
© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma