RTU Research Information System
Latviešu English

Publikācija: Challenges in the Development of Affective Collaborative Learning Environment with Artificial Peers

Publication Type Scientific article indexed in SCOPUS or WOS database
Funding for basic activity State funding for education
Defending: ,
Publication language English (en)
Title in original language Challenges in the Development of Affective Collaborative Learning Environment with Artificial Peers
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Research platform None
Authors Māra Pudāne
Sintija Petroviča
Egons Lavendelis
Alla Anohina-Naumeca
Keywords Affective computing, agent-based modelling, collaborative learning environment, tutoring adaptation.
Abstract Collaborative learning is a process that involves a group of peers collaborating with the aim to acquire new knowledge or skills. Collaborative learning environment enables such interactions by means of ICT. The paper focuses on affective collaborative learning environments, i.e., collaborative learning environments that are additionally aware of user’s emotions and moods. Based on the analysis of existing research, a general architecture of an affective collaborative learning environment has been proposed in the paper and the main challenges for developing such an environment have been identified, namely, nonintrusive and safe detection of user’s emotions, the adaptation of tutoring strategies, as well as modelling of artificial peers. This study can be considered the first step for the development of the collaborative learning environment that takes into account various affective aspects during the collaborative learning process.
DOI: 10.2478/acss-2018-0013
Reference Pudāne, M., Petroviča, S., Lavendelis, E., Anohina-Naumeca, A. Challenges in the Development of Affective Collaborative Learning Environment with Artificial Peers. Applied Computer Systems, 2018, Vol. 23, No. 2, pp.101-108. ISSN 2255-8683. e-ISSN 2255-8691. Available from: doi:10.2478/acss-2018-0013
Full-text Full-text
Publication version
License
ID 28652