A Semantic Network Instant Feedback System to Improve Online Discussion Performance
| Autor: | Pei-Chun Chen, Ming-Chaun Li, Ya-Ling Huang, Chih-Ming Chen |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Online discussion
Multimedia business.industry Group (mathematics) Computer science 05 social sciences Control (management) 050301 education Usability Cognition computer.software_genre Semantics Semantic network 03 medical and health sciences 0302 clinical medicine Informatics ComputingMilieux_COMPUTERSANDEDUCATION business 0503 education computer 030217 neurology & neurosurgery |
| Zdroj: | IIAI-AAI |
| Popis: | The "Semantic Network Instant Feedback System (SNIFS)" is designed in this study to present the semantic network of words used in learners’ discussion and assist learners in grasping the discussion direction to enhance online learning effectiveness. A total of 64 Grade 11 learners from two classes of a senior high school in Northern Taiwan participated in this research. By conducting quasi-experimental research, "SNIFS-assisted discussion" was applied to the experimental group and general online discussion was adopted in the control group. The results show no differences in socio-scientific reasoning performance between the two groups. Moreover, the experimental group showed significantly lower overall technology acceptance and lower perceived ease of use than the control group. However, the results of the interview reveal that learners in the experimental group perceived SNIFS to be helpful in their discussion. Several suggestions were provided by the learners to improve the SNIFS. |
| Databáze: | OpenAIRE |
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