Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/13326
Title: | Towards persuasive sociometric technologies for inclusive educational settings | Authors: | Lyra, Olga Karapanos, Evangelos Gouveia, Rúben Barreto, Mary L. Nisi, Valentina Nunes, Nuno J. Zimmerman, John Forlizzi, Jodi |
Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences | Keywords: | Persuasive sociometric technologies;Social inclusion | Issue Date: | Sep-2013 | Source: | Biannual Conference of the Italian Chapter of SIGCHI, 2013, 16 - 20 September, Trento, Italy | Conference: | Biannual Conference of the Italian Chapter of SIGCHI | Abstract: | With an increasing interest in the social inclusion of children in schools, HCI researchers have proposed technologies that support children at risk of social exclusion in their interactions with peers. However, much of this work has focused on the child at risk of social exclusion, disregarding the fact that social exclusion is a group-phenomenon that often originates in children's negative stereotyping. In this paper we argue for persuasive sociometric technologies, ones that sense children's social interactions in real-time, and provide persuasive, just-in-time recommendations to children with the goal of challenging their perceptions of diversity and motivating pro-social behaviors. We report on two studies that aimed at inquiring into children's practices of social exclusion in school communities as well as whether and how persuasive technologies can stimulate pro-social behaviors and a sense of empathy among them. | URI: | https://hdl.handle.net/20.500.14279/13326 | DOI: | 10.1145/2499149.2499163 | Rights: | Copyright © 2013 ACM. | Type: | Conference Papers | Affiliation : | Madeira Interactive Technologies Institute Carnegie Mellon University |
Publication Type: | Peer Reviewed |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
CORE Recommender
SCOPUSTM
Citations
50
3
checked on Nov 6, 2023
Page view(s) 50
353
Last Week
2
2
Last month
7
7
checked on Dec 22, 2024
Google ScholarTM
Check
Altmetric
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.