| Texto completo | |
| Autor(es): |
Pastushenko, Olena
;
Oliveira, Wilk
;
Isotani, Seiji
;
Hruska, Tomas
;
Assoc Comp Machinery
Número total de Autores: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | CHI'20: EXTENDED ABSTRACTS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS; v. N/A, p. 9-pg., 2020-01-01. |
| Resumo | |
Much research has sought to provide a flow experience for students in gamified educational systems to increase motivation and engagement. However, there is still a lack of quantitative research for evaluating the influence of the flow state on learning outcomes. One of the issues related to flow experience identification is that used techniques are often invasive or not suitable for massive applications. The current paper suggests a way to deal with this challenge. We describe a methodology based on multimodal learning analytics, aimed to provide automatic students' flow experience identification in the gamified assignments and measuring its influence on the learning outcomes. The application of the developed methodology showed that there are correlations between learning outcomes and flow state, but they depend on the initial level of the user. This finding suggests adding dynamic difficulty adjustment and other flow experience dimension to the gamified assignment. (AU) | |
| Processo FAPESP: | 18/07688-1 - Design e detecção automática de experiência de fluxo em estudantes e professores em sistemas educacionais inteligentes gamificados |
| Beneficiário: | Wilk Oliveira dos Santos |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |