Conversational Analysis to Recommend Collaborative Learning in Distance Education

Antônio Moraes Neto, Márcia Fernandes, Tel Amiel

2022

Abstract

Conversational agents can recommend interactions among students in a Virtual Learning Environment (VLE) for the purpose of supporting collaborative learning, an important approach to improve online education. This paper describes the current position of a research that addresses the implementation of Conversational Analysis (CA) in order to make recommendations through chatbots for promoting collaborative learning among students in a VLE. Based on an experiment, the authors propose a CA strategy to determine the level of collaboration among students, point out possibilities for chatbot’s intervention in favor of collaborative learning, and present the results obtained in the current stage of the research.

Paper Citation

in Harvard Style

Moraes Neto A., Fernandes M. and Amiel T. (2022). Conversational Analysis to Recommend Collaborative Learning in Distance Education. In Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU, ISBN 978-989-758-562-3, pages 196-203. DOI: 10.5220/0011092600003182

in Bibtex Style

@conference{csedu22,
author={Antônio Moraes Neto and Márcia Fernandes and Tel Amiel},
title={Conversational Analysis to Recommend Collaborative Learning in Distance Education},
booktitle={Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,},
year={2022},
pages={196-203},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011092600003182},
isbn={978-989-758-562-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Computer Supported Education - Volume 2: CSEDU,
TI - Conversational Analysis to Recommend Collaborative Learning in Distance Education
SN - 978-989-758-562-3
AU - Moraes Neto A.
AU - Fernandes M.
AU - Amiel T.
PY - 2022
SP - 196
EP - 203
DO - 10.5220/0011092600003182