SIAKAD Machine Learning for Correcting Errors in Speaking Arabic

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 technolo...

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Bibliographic Details
Published inWorld Journal on Educational Technology: Current Issues Vol. 14; no. 3; pp. 768 - 780
Main Authors Ritonga, Mahyudin, Zulmuqim, Zulmuqim, Bambang, Bambang, Kurniawan, Rahadian, Pahri, Pahri
Format Journal Article
LanguageEnglish
Published Birlesik Dunya Yenilik Arastirma ve Yayincilik Merkezi 2022
Subjects
Arabic
Artificial Intelligence
Audio Equipment
Computational Linguistics
Error Analysis (Language)
Error Correction
Foreign Countries
Grammar
Information Technology
Language Usage
Pronunciation
Second Language Instruction
Second Language Learning
Sentences
Speech Communication
Undergraduate Students
Video Technology
Vowels
Indonesia
Online AccessGet full text
ISSN1309-1506

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Summary: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.
ISSN:1309-1506