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All Journal Journal Of Arabic Language Studies And Teaching Kalimatuna: Journal Of Arabic Research
Karima, Salman Rizqan
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Education Languange, Linguistic, Communication & Media

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HelloTalk: A Review of Internet-Based Software to Support Arabic Vocabulary Mastery Fuada, Farha; Karima, Salman Rizqan; Rahmawati, Siti Uriana
Kalimatuna: Journal of Arabic Research Vol 2, No 2 (2023): Kalimatuna: Journal of Arabic Research
Publisher : Department of Arabic Education - Faculty of Educational Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/kjar.v2i2.37499

Abstract

One of the important elements of mastering Arabic is memorizing vocabulary. This is because vocabulary is related to the four language skills. The main impediment to learning Arabic motivation is a lack of vocabulary mastery. This study focuses on the description of the HelloTalk application in learning Arabic, especially in teaching vocabulary. This research covers the advantages and disadvantages of the HelloTalk application as a means of learning vocabulary. A qualitative approach and the application of triangulation are used to verify the data obtained. The data collection method used was observation and interviews to investigate the practice of teaching vocabulary in the HelloTalk application. The data analysis technique used in this research uses the Miles and Huberman model, which consists of the processes of data collection, data reduction, data display, and drawing conclusions. The involvement of multiple instruments and participants makes the HelloTalk application review more comprehensive. HelloTalk as a learning tool that is popular and effective in learning vocabulary must be further developed so that the potential for language learning is increased and made more useful.
HelloTalk: A Review of Internet-Based Software to Support Arabic Vocabulary Mastery Fuada, Farha; Karima, Salman Rizqan; Rahmawati, Siti Uriana
Kalimatuna: Journal of Arabic Research Vol. 2 No. 2 (2023): Kalimatuna: Journal of Arabic Research
Publisher : Department of Arabic Education - Faculty of Educational Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/kjar.v2i2.37499

Abstract

One of the important elements of mastering Arabic is memorizing vocabulary. This is because vocabulary is related to the four language skills. The main impediment to learning Arabic motivation is a lack of vocabulary mastery. This study focuses on the description of the HelloTalk application in learning Arabic, especially in teaching vocabulary. This research covers the advantages and disadvantages of the HelloTalk application as a means of learning vocabulary. A qualitative approach and the application of triangulation are used to verify the data obtained. The data collection method used was observation and interviews to investigate the practice of teaching vocabulary in the HelloTalk application. The data analysis technique used in this research uses the Miles and Huberman model, which consists of the processes of data collection, data reduction, data display, and drawing conclusions. The involvement of multiple instruments and participants makes the HelloTalk application review more comprehensive. HelloTalk as a learning tool that is popular and effective in learning vocabulary must be further developed so that the potential for language learning is increased and made more useful.
A Comparison of the Accuracy of Generative Artificial Intelligence Models in Taṣrīf and the Explanation of Wazan Meanings: A Study on Their Application in Arabic Morphology (Ṣarf) Karima, Salman Rizqan; Edidarmo, Toto; Raswan, Raswan
Journal of Arabic Language Studies and Teaching Vol. 5 No. 2 (2025): November 2025 / نوفمبر ٢٠٢٥
Publisher : Universitas Islam Negeri Sunan Ampel Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15642/jalsat.2025.5.2.234-250

Abstract

This study analyzes and compares the accuracy of two generative artificial intelligence models, ChatGPT and Deepseek, in producing taṣrīf (morphological conjugation) and explaining the meanings of wazan (morphological patterns) in Arabic morphology. Employing a descriptive-qualitative method with a content analysis approach, the research uses 30 fiʿl thulāthī mazīd (triliteral verbs with augmentation) representing all categories ṣaḥīḥ, maḥmūz, muḍāʿaf, muʿtal, miṯāl, ajwaf, nāqiṣ, and lafīf. Each verb was tested on ChatGPT 4.0 and Deepseek V3.1, and the outputs were verified against classical references, including al-Bināʾ, al-Maqṣūd, and al-Amthilah al-Taṣrīfiyyah. The findings show that both models produce fairly accurate results with distinctive tendencies: Deepseek aligns more closely with classical morphological rules, while ChatGPT provides more diverse and contextual explanations. Pedagogically, both have strong potential to support Arabic morphology learning through interactive and varied outputs, though teacher supervision remains essential to maintain adherence to classical standards.
Co-Authors Fuada, Farha Rahmawati, Siti Uriana Raswan Raswan, Raswan Toto Edidarmo