Alibbaa': Jurnal Pendidikan Bahasa Arab

A Conceptual Framework of Arabic Reading Skills in Qur’anic Memorization: Integrating Philosophy of Science and AI-Assisted Learning

Riza Egy Ramadhani — 2026-04-12

This study addresses the tendency in Qur’anic learning research to separate reading skills (maharah qira’ah) and memorization, without integrating them within a philosophy of science framework. In addition, the use of Artificial Intelligence (AI) remains largely technical. This study aims to construct a conceptual framework integrating reading and memorization from ontological, epistemological, and axiological perspectives, and to explore AI-assisted learning as a supporting approach. A qualitative systematic literature-based conceptual design was employed using thematic analysis and conceptual synthesis. The findings indicate that reading functions ontologically as a meaning-making process, epistemologically as a mechanism of knowledge construction through encoding, storage, and retrieval, and axiologically as a means to improve memorization quality in terms of accuracy, retention, and efficiency. AI integration strengthens these processes through real-time feedback and adaptive learning, enabling an integrated learning cycle between reading and memorization. This study contributes a conceptual framework linking reading, memorization, and technology within a unified epistemic system

Rethinking AI in Arabic Translation Learning: The Role of DeepL and Teacher Mediation

Anni Mujahida — 2026-04-20

This study aims to analyze the implementation of DeepL AI Translate in Arabic translation learning at MTs Alkhairaat Pusat Palu Indonesia, examine its impact on students’ learning processes, and identify the role of teachers in controlling the quality of AI-assisted translations. This research employs a qualitative descriptive approach within a naturalistic framework, with data collected through 15 days of classroom observations, in-depth interviews, and documentation. The findings reveal that DeepL is integrated into a structured learning process consisting of pre-translation, AI-assisted translation, post-translation, and evaluation stages. The use of DeepL enhances student participation, learning efficiency, confidence, and vocabulary comprehension. However, its use remains largely limited to lexical-level support and may lead to dependency if not pedagogically controlled. In this context, teachers play a crucial role as mediators, facilitators, and quality controllers of translation outcomes. This study highlights that the effectiveness of AI in language learning depends not only on technological capability but also on its pedagogical integration within the classroom.

Learning Arabic Speaking (Kalam) through Thorndike’s Behaviorism: Pedagogical Implications for AI-Assisted Learning

Andhika Mulia Daulay — 2026-05-15

This study investigates the implementation of Arabic speaking instruction in Thorndike’s behaviorism principles (law of readiness, law of exercise, and law of effect) at SMPIT Imam An-Nawawi Pekanbaru and explores their pedagogical implications for AI-assisted language learning. Using a qualitative case study design, the research involved classroom observations, semi-structured interviews, and documentation in Arabic speaking classes. The findings reveal that law of readiness was reflected through verbal stimulation and guided prompting that prepared students’ speaking engagement, while law of exercise appeared through repetition, drilling, and repeated speaking interaction that gradually formed students’ speaking habits. In addition, law of effect was implemented through positive reinforcement, corrective feedback, and motivational responses that strengthened students’ speaking confidence and verbal participation. The study also found that pedagogical mechanisms identified in the classroom, such as repetition, adaptive prompting, corrective feedback, and reinforcement-based interaction, conceptually align with the learning logic used in contemporary AI-assisted language learning systems. The study concludes that Thorndike’s behaviorism remains pedagogically relevant in Arabic speaking instruction and offers conceptual insights for the development of AI-assisted Arabic language learning, particularly in speaking habit formation and adaptive verbal interaction.

Local Dialect Interference and AI-Based Arabic Speech Recognition: Evidence from Madurese Learners

Indi Hulwun Nasyithah — 2026-05-17

This study investigates the influence of Madurese phonetic interference on the accuracy of AI-based Arabic Speech Recognition systems. The research focuses on vowel-shift deviations produced by Madurese native speakers in Arabic pronunciation and evaluates the performance of Google Speech-to-Text and OpenAI Whisper in recognizing dialect-influenced Arabic speech. Using a mixed-method approach, speech data were collected from 13 sixth-semester students of the Arabic Language Education Department at UIN Madura through direct voice recording involving isolated words, continuous Arabic sentences, and Qur’anic recitations. Acoustic observation using Praat identified systematic vowel shifts, particularly the transitions of /a/ to [e], /i/ to [e], and /u/ to [o], which generated acoustic variability in Arabic speech production. The findings reveal that OpenAI Whisper achieved higher recognition accuracy (84.0%) with a lower Word Error Rate (16.0%) compared to Google Speech-to-Text, which obtained an accuracy of 61.8% and a WER of 38.2%. The dominant errors included substitution, deletion, insertion, and segmentation errors, indicating instability in phoneme mapping caused by dialect-induced vowel transitions. The study concludes that current AI-based Arabic Speech Recognition systems remain sensitive to low-resource dialect interference and that acoustic variability significantly affects recognition stability in multilingual speech environments. These findings highlight the importance of developing more adaptive and linguistically inclusive ASR models for Arabic language learning contexts.

Bridging Traditional Arabic Pedagogy and AI-Supported Learning through Snakes and Ladders Game-Based Instruction

M. Naufal Al Qurthuby Fuady S — 2026-05-18

This study explores the use of snakes and ladders game-based instruction in Arabic uslub learning at LSBA Ula within the broader perspective of AI-supported pedagogy. The study emerged from the challenges of contextual Arabic language learning, particularly students’ difficulties in understanding the communicative functions and contextual usage of Arabic expressions through conventional teacher-centered instruction. Using a qualitative case study approach, data were collected through classroom observation, semi-structured interviews, and learning documentation involving students and teachers participating in Arabic uslub instruction. The findings reveal that the traditional snakes and ladders game created collaborative and contextual learning interactions through peer discussion, meaning negotiation, reflective feedback, and experiential learning activities. The study also found that the pedagogical mechanisms emerging during gameplay, including real-time feedback, error identification, and adaptive instructional support, align with the principles of AI-supported learning without transforming the traditional game into a digital AI-based system. This study concludes that traditional game-based instruction remains pedagogically relevant for Arabic language learning in the AI era because it supports collaborative, reflective, and human-centered learning experiences. The study contributes to the development of low-tech yet AI-compatible Arabic pedagogy, particularly in non-formal educational contexts.

Integrating the Flower and Hayes Cognitive Writing Model into Advanced Arabic Dictation Instruction with AI-Assisted Learning

Aiman — 2026-05-20

This study examines the relevance of the cognitive writing model developed by Linda Flower and John R. Hayes in advanced Arabic dictation instruction and explores the integration of Artificial Intelligence (AI) in supporting cognitive writing processes during orthographic learning. The study is based on the assumption that Arabic dictation (imla’) is not merely a mechanical orthographic exercise, but a cognitive writing activity involving planning, linguistic processing, monitoring, and self-revision throughout the writing process. This research employed a qualitative descriptive-analytical approach through library research by analyzing various studies related to Arabic dictation, cognitive writing processes, the Flower and Hayes model, and AI-assisted language learning. The findings reveal that the stages of planning, translating, and reviewing in the Flower and Hayes model are closely related to orthographic activities in advanced Arabic dictation learning. The planning stage involves orthographic anticipation and linguistic retrieval before writing, the translating stage involves the transformation of mental representation into Arabic graphic forms, while the reviewing stage includes monitoring, evaluation, and orthographic revision. The study also indicates that AI can support these cognitive processes through predictive spelling, contextual prompting, real-time orthographic feedback, and automated revision assistance. Furthermore, AI contributes to the development of metacognitive awareness and self-monitoring during the writing process. This study concludes that integrating the Flower and Hayes cognitive writing model with AI-assisted learning may contribute to the development of more reflective, learner-centered, and cognitively oriented Arabic dictation instruction.

Enhancing Maharah Istima’ Through Roleplay and Focus Group Discussion: Implications for AI-Supported Language Learning

Mushthafa Shadiq Al-Rafi'i — 2026-05-20

Arabic language learning in Indonesia continues to face challenges, particularly in developing students’ Maharah Istima’ (listening skills), which are often hindered by limited vocabulary, rapid speech input, and the dominance of passive instructional approaches. This study aims to examine the effectiveness of integrating Roleplay and Focus Group Discussion (FGD) in improving students’ listening ability within a classroom context. This research employed a quantitative approach using a quasi-experimental design with a non-equivalent control group. The participants consisted of 20 fifth-grade students at Al-Irhaam Global Islamic School Bandung, divided into an experimental group receiving Roleplay and FGD-based instruction and a control group receiving conventional audio-based instruction. Data were collected through pre-test and post-test and analyzed using Shapiro-Wilk normality test, homogeneity test, paired sample t-test, and N-Gain analysis. The findings indicate a statistically significant improvement in the experimental group (p < 0.05), with mean scores increasing from 72.0 to 88.0 and an N-Gain value of 0.63 (moderate category). Compared to the control group, the results suggest that interactive and collaborative learning activities contribute more effectively to the development of listening skills. These findings highlight the pedagogical potential of integrating Roleplay and FGD in promoting active engagement and deeper processing of language input. While this study is limited to a small-scale classroom context, it offers practical implications for designing interactive listening instruction and suggests opportunities for future integration with AI-supported language learning tools.

Arabic Scrabble as a Game-Based Learning Innovation for Vocabulary Mastery in AI-Oriented Arabic Education

Risti Fikriyah — 2026-05-24

This study investigates the implementation of Arabic Scrabble as a game-based learning innovation for enhancing Arabic vocabulary mastery among seventh-grade students at Darul Ihsan Modern Islamic Boarding School within the framework of AI-oriented Arabic education. The study responds to the continuing challenges of Arabic vocabulary learning, particularly students’ difficulties in memorizing and using vocabulary communicatively in classroom interaction. Using a qualitative phenomenological case study approach, data were collected through non-participant observation, semi-structured interviews, and documentation involving Arabic teacher and seventh-grade students. The findings reveal that the implementation of Arabic Scrabble created a more interactive and student-centered learning environment by increasing learner engagement, collaborative learning, vocabulary retention, and students’ confidence in using Arabic vocabulary. Through activities such as arranging Arabic letters into words, discussing meanings collaboratively, and constructing simple sentences, students became more active and motivated during the learning process. Furthermore, the study indicates that Arabic Scrabble reflects several characteristics associated with AI-oriented Arabic pedagogy, particularly interactive, adaptive, and engagement-based learning experiences. This study contributes to the discourse of game-based Arabic learning by positioning Arabic Scrabble not merely as an educational game, but as a pedagogical innovation that supports learner-centered Arabic education in modern Islamic boarding schools.

Fragmented Scaffolding in Arabic Textbooks: A Genre-Based Analysis of the Teaching Learning Cycle in Indonesian Madrasah Education

Safira Nur Rizqina — 2026-05-26

This study investigates the implementation of the Teaching Learning Cycle (TLC) in the Grade XI Arabic textbook published by KSKK Madrasah (2020). Using qualitative content analysis grounded in Systemic Functional Linguistics and Genre-Based Approach, the study analyzed six textbook chapters through the stages of BKOF, MOT, JCOT, and ICOT. AI-assisted comparative validation using ChatGPT-5 was additionally employed to support analytical consistency between manual and AI categorization results. The findings reveal that although all TLC stages formally appeared in the textbook, their pedagogical continuity was implemented inconsistently. BKOF and MOT generally provided adequate contextual and rhetorical support, while JCOT frequently lacked collaborative text construction and was often reduced to oral interaction. Consequently, several ICOT activities required students to produce independent texts without sufficient scaffolding. The study contributes to genre-based Arabic textbook evaluation within the context of Indonesian madrasah education.

Canva AI as a Cognitive Partner in Arabic Writing Instruction: Enhancing Linguistic Expression and Communicative Competence through Magic Write

Nurdiana Arifah — 2026-05-29

The integration of Artificial Intelligence (AI) into language learning has introduced new opportunities for developing writing skills beyond conventional grammar-focused instruction. This study investigates the role of Canva AI, particularly its Magic Write feature, in enhancing Arabic writing (Maharah Kitabah) among university students. Using a qualitative descriptive approach, the study analyzes the transformation of students’ drafts into AI-assisted texts through documentation and content analysis. The primary data consist of Arabic writing products in the genres of condolence messages (ta'ziyah) and birthday greetings (yaumul milad), while relevant literature on AI-assisted writing and Arabic language learning serves as supporting data. The findings reveal that Canva AI contributes to Arabic writing development in two significant ways. First, it functions as a linguistic refinement tool by improving lexical choice, textual cohesion, pragmatic appropriateness, and stylistic quality. Second, it serves as an expressive enrichment tool by expanding semantic content, diversifying expressions, and enhancing the emotional and communicative dimensions of writing. The study further demonstrates that Canva AI operates not merely as a writing assistant but as a cognitive partner that supports students in producing more natural, contextually appropriate, and aesthetically appealing Arabic texts. These findings suggest that the integration of Generative AI into Arabic writing instruction can promote communicative competence, pragmatic awareness, and linguistic creativity while maintaining the learner’s central role in the writing process.

Arabic Orthography Instruction and Writing Accuracy among Madrasah Students: Insights for AI-Assisted Language Learning

Rifka Emiyiati — 2026-05-31

The growing use of AI-assisted language learning highlights the importance of foundational writing competencies in Arabic language education. This study aims to investigate the implementation of Arabic writing instruction, identify students’ writing difficulties, and examine its relevance to AI-assisted language learning. Using a qualitative descriptive approach, the study was conducted at MTs Darul Irsyadiyah Labuhanbatu involving seventh-grade students and an Arabic language teacher. Data were collected through observations, interviews, and documentation and analyzed descriptively. The findings reveal that writing instruction was implemented systematically to improve students’ orthographic accuracy. However, students continued to experience difficulties in distinguishing visually similar Arabic letters, applying harakat accurately, and writing independently. Limited instructional time and insufficient writing practice were identified as major challenges. The study suggests that orthographic competence remains a fundamental prerequisite for effective Arabic writing, even in AI-assisted learning environments where automated feedback and writing support are increasingly available.

The Foundations of AI-Driven Arabic Learning Materials: Toward an Integrative Conceptual Framework

Imam Haromaen — 2026-05-31

Artificial Intelligence (AI) has created new opportunities for developing Arabic learning materials that are more adaptive, personalized, and interactive. However, existing studies have primarily focused on technological applications, with limited attention to the theoretical foundations that should guide the development of AI-driven Arabic learning materials. This study aims to analyze the theoretical foundations underlying the development of Arabic learning materials in the era of artificial intelligence. Using a qualitative library research design, data were collected from scholarly books, journal articles, conference proceedings, and other relevant academic publications. The data were analyzed through content analysis, thematic analysis, and conceptual synthesis. The findings indicate that the development of AI-driven Arabic learning materials should be grounded in five interconnected foundations: philosophical, pedagogical, linguistic, psychological, and sociocultural. These foundations provide a comprehensive framework for integrating AI into Arabic language education while ensuring adaptability, personalization, interactivity, and cultural authenticity. This study contributes an integrative conceptual perspective that positions AI as an educational enabler rather than merely a technological tool.

Enhancing Arabic Speaking Skills Through AI-Assisted Adaptive Vocabulary Games: Evidence from a Classroom Intervention

Cahaya Tuw Fajardini — 2026-06-01

The development of Arabic speaking skills remains a significant challenge for many secondary school learners, particularly due to limited vocabulary mastery and insufficient opportunities for meaningful oral communication. This study investigates the effectiveness of AI-assisted adaptive vocabulary games in enhancing Arabic speaking skills among secondary school students. Using a classroom intervention design conducted in two instructional cycles, the study involved 31 tenth-grade students at MA Muhammadiyah Kota Bima, Indonesia. Data were collected through speaking performance tests, classroom observations, and learning documentation. The findings revealed a consistent improvement in students’ speaking performance, as indicated by an increase in the mean score from 62 in the pre-intervention stage to 68 in Cycle I and 76.25 in Cycle II. Learning mastery also increased substantially from 16.7% to 80.64% by the end of the intervention. Furthermore, the N-Gain score of 0.375 indicated a moderate level of effectiveness. The findings suggest that vocabulary-centered interactive activities can facilitate oral language production by promoting contextual vocabulary use and repeated speaking practice. From an adaptive learning perspective, the study highlights the potential of integrating Generative Artificial Intelligence into vocabulary game design to support more personalized and communicative Arabic language learning environments. The study contributes to the growing discourse on AI-enhanced language learning by demonstrating the pedagogical value of adaptive vocabulary-based interventions for developing Arabic speaking skills.