Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic Situation
Due to the Covid-19 pandemic crisis, educational institutions have to change their teaching styles because students cannot go to the school (on-site). Therefore, the purpose of this study was to learning online assessment of electric circuit based on machine learning. To achieve the online assessmen...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Pendidikan Indonesia
2021-09-01
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| Series: | Indonesian Journal of Teaching in Science |
| Subjects: | |
| Online Access: | https://ejournal.upi.edu/index.php/IJoTis/article/view/41188/17364 |
| _version_ | 1797355291710324736 |
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| author | Kunanan Thapwiroch Apisada Kumlue Niradtapong Saoyong Praparat Taprasa Supachai Puengsungewan |
| author_facet | Kunanan Thapwiroch Apisada Kumlue Niradtapong Saoyong Praparat Taprasa Supachai Puengsungewan |
| author_sort | Kunanan Thapwiroch |
| collection | DOAJ |
| description | Due to the Covid-19 pandemic crisis, educational institutions have to change their teaching styles because students cannot go to the school (on-site). Therefore, the purpose of this study was to learning online assessment of electric circuit based on machine learning. To achieve the online assessment, machine learning has been applied as a powerful algorithm to realize the novel online assessment for electric circuit course of bachelor students at the department of electrical technology education, King Mongkut’s University of Technology Thonburi, Thailand. To achieve the data collection process, speech to text algorithm has been applied. Next, feature extraction would be adopted as the main key to extracting the knowledge from the data from speech to text algorithm. The output of feature extraction is the dataset of the proposed system. Finally, the clustering algorithm would be applied to set up the learning process of the proposed method. The accuracy of the proposed method can reach 100% when the word feature is appropriate. |
| first_indexed | 2024-03-08T14:09:02Z |
| format | Article |
| id | doaj.art-79f74f7c23ab49fcbd656e417a2639ad |
| institution | Directory Open Access Journal |
| issn | 2776-6152 2776-6101 |
| language | English |
| last_indexed | 2024-03-08T14:09:02Z |
| publishDate | 2021-09-01 |
| publisher | Universitas Pendidikan Indonesia |
| record_format | Article |
| series | Indonesian Journal of Teaching in Science |
| spelling | doaj.art-79f74f7c23ab49fcbd656e417a2639ad2024-01-15T03:07:34ZengUniversitas Pendidikan IndonesiaIndonesian Journal of Teaching in Science2776-61522776-61012021-09-011210511210.17509/ijotis.v1i2.41188 Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic SituationKunanan Thapwiroch0Apisada Kumlue1Niradtapong Saoyong2Praparat Taprasa3Supachai Puengsungewan4King Mongkut’s University of Technology ThonburiKing Mongkut’s University of Technology ThonburiKing Mongkut’s University of Technology ThonburiKing Mongkut’s University of Technology ThonburiKing Mongkut’s University of Technology ThonburiDue to the Covid-19 pandemic crisis, educational institutions have to change their teaching styles because students cannot go to the school (on-site). Therefore, the purpose of this study was to learning online assessment of electric circuit based on machine learning. To achieve the online assessment, machine learning has been applied as a powerful algorithm to realize the novel online assessment for electric circuit course of bachelor students at the department of electrical technology education, King Mongkut’s University of Technology Thonburi, Thailand. To achieve the data collection process, speech to text algorithm has been applied. Next, feature extraction would be adopted as the main key to extracting the knowledge from the data from speech to text algorithm. The output of feature extraction is the dataset of the proposed system. Finally, the clustering algorithm would be applied to set up the learning process of the proposed method. The accuracy of the proposed method can reach 100% when the word feature is appropriate.https://ejournal.upi.edu/index.php/IJoTis/article/view/41188/17364covid-19 pandemicmachine learningonline assessmentonline learning |
| spellingShingle | Kunanan Thapwiroch Apisada Kumlue Niradtapong Saoyong Praparat Taprasa Supachai Puengsungewan Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic Situation Indonesian Journal of Teaching in Science covid-19 pandemic machine learning online assessment online learning |
| title | Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic Situation |
| title_full | Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic Situation |
| title_fullStr | Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic Situation |
| title_full_unstemmed | Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic Situation |
| title_short | Online Assessment of Electric Circuit based on Machine Learning During Covid-19 Pandemic Situation |
| title_sort | online assessment of electric circuit based on machine learning during covid 19 pandemic situation |
| topic | covid-19 pandemic machine learning online assessment online learning |
| url | https://ejournal.upi.edu/index.php/IJoTis/article/view/41188/17364 |
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