SIAKAD machine learning for correcting errors in speaking Arabic
SIAKAD machine learning for correcting errors in speaking Arabic
Author(s): Mahyudin Ritonga, Zulmuqim Zulmuqim, Bambang Bambang, Rahadian Kurniawan, Pahri PahriSubject(s): Foreign languages learning, Media studies, School education, ICT Information and Communications Technologies, Distance learning / e-learning
Published by: Birlesik Dunya Yenilik Arastirma ve Yayincilik Merkezi
Keywords: Arabic Language Education; Machine Learning; Speaking Errors;
Summary/Abstract: Information technology provides a lot of convenience for humans in completing their tasks and getting results according to targets. In line with that, language teachers have a duty to find out the level of language skills and forms of language errors in students. Machine Learning as part of technology can be maximized to detect forms of Arabic speaking error in students. This study was conducted with a qualitative approach. Data were collected via SIAKAD machine learning containing Arabic videos. Based on the results, the SIAKAD machine learning uncovered several Arabic speaking errors such as grammar, pronunciation, shifat al-huruf, vowels, word expression, and concatenated sentences. Therefore, machine learning with various types can be maximized in Arabic learning which ultimately leads to technological developments that must be accompanied by the ability of teachers to be skilled in operationalizing technology.
Journal: World Journal on Educational Technology: Current Issues
- Issue Year: 14/2022
- Issue No: 3
- Page Range: 768-780
- Page Count: 13
- Language: English
