Name
Abstract | ||
|---|---|---|
Repeated training of teaching skills for student teachers is difficult as many collaborators should be needed for rehearsal environment. Therefore, we are studying a teaching training system using virtual classroom which is constructed by virtual agents as students. In order to construct such a training system, an automatic assessment of human behaviour by the system is required. On the other hand, it is difficult to assess teaching skills in term of educational environment due to complex interactions with many students and subjectivity of the task of teaching assessment. In this study, we propose an assessment model by neural networks (NN) to learn more potential assessment features using multi-modal information: gesture and prosodic information, facial expressions, and the teacher’s intention.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3351529.3360662 | Adjunct of the 2019 International Conference on Multimodal Interaction |
Keywords | Field | DocType |
education application, multimodal interaction, user assessment, virtual classroom, virtual reality | Computer science,Artificial intelligence,Artificial neural network | Conference |
ISBN | Citations | PageRank |
978-1-4503-6937-4 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Masato Fukuda | 1 | 37 | 6.86 |
| Hung-Hsuan Huang | 2 | 140 | 32.60 |
| Kazuhiro Kuwabara | 3 | 700 | 112.64 |
| Toyoaki Nishida | 4 | 1097 | 196.19 |