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Human intelligence-based metaverse for co-learning of students and smart machines.
Lee, Chang-Shing; Wang, Mei-Hui; Reformat, Marek; Huang, Sheng-Hui.
Afiliação
  • Lee CS; Department of Computer Science and Information Engineering, National University of Tainan, Tainan, Taiwan.
  • Wang MH; Department of Computer Science and Information Engineering, National University of Tainan, Tainan, Taiwan.
  • Reformat M; Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.
  • Huang SH; Information Technology Institute, University of Social Sciences, Warsaw, Poland.
J Ambient Intell Humaniz Comput ; 14(6): 7695-7718, 2023.
Article em En | MEDLINE | ID: mdl-37228697
ABSTRACT
This paper proposes a Human Intelligence (HI)-based Computational Intelligence (CI) and Artificial Intelligence (AI) Fuzzy Markup Language (CI&AI-FML) Metaverse as an educational environment for co-learning of students and machines. The HI-based CI&AI-FML Metaverse is based on the spirit of the Heart Sutra that equips the environment with teaching principles and cognitive intelligence of ancient words of wisdom. There are four stages of the Metaverse preparation and collection of learning data, data preprocessing, data analysis, and data evaluation. During the data preparation stage, the domain experts construct a learning dictionary with fuzzy concept sets describing different terms and concepts related to the course domains. Then, the students and teachers use the developed CI&AI-FML learning tools to interact with machines and learn together. Once the teachers prepare relevant material, students provide their inputs/texts representing their levels of understanding of the learned concepts. A Natural Language Processing (NLP) tool, Chinese Knowledge Information Processing (CKIP), is used to process data/text generated by students. A focus is put on speech tagging, word sense disambiguation, and named entity recognition. Following that, the quantitative and qualitative data analysis is performed. Finally, the students' learning progress, measured using progress metrics, is evaluated and analyzed. The experimental results reveal that the proposed HI-based CI&AI-FML Metaverse can foster students' motivation to learn and improve their performance. It has been shown in the case of young students studying Software Engineering and learning English.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Qualitative_research Idioma: En Revista: J Ambient Intell Humaniz Comput Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Taiwan

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Qualitative_research Idioma: En Revista: J Ambient Intell Humaniz Comput Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Taiwan