Development of Smart Live Edu-Multimedia Multilingual Adaptive for Digital Quran to Children and Parents Utilize meta-Deep Lightweight SORA Algorithm
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Abstract
This research related to collaboration Islamic religious education methods in the family home is urgent and important, particularly for children and parents, especially regarding the introduction of the Quran as the word of Allah SWT delivered by the Prophet Muhammad SAW through the angel Gabriel. To improve education ways, the approach, if only conducted conventionally, such as only monotonous with static books, of course, is not enough to attract interest in reading to memorization. Based on these constraints, this study carried out an adaptive approach by utilizing technology from the meta-Deep lightweight SORA algorithm as a tool to create a smart digital Quran that is able to display live adaptive multilingual multimedia, including textual, audio, and video content. We propose Cooperative Agents Meta-Learning (CAML) algorithm as its contribution in supporting greater convenience for early childhood education and parents. The results of this study are expected to be able to provide a treasure trove of Islamic education with a blended method while maintaining methods such as in Islamic boarding schools with the latest Artificial Intelligence (AI) technology.
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References
[2] Rahman B 2020 AI in Quranic education: A review J. AI Innov. Educ. 10 78–85
[3] Al-Ghamdi A and Al-Zahrani S 2018 A new approach to Quranic learning using mobile apps Procedia Computer Science vol 134 (ScienceDirect) pp 224–31
[4] Ahmed C 2022 Multilingual Quranic learning platforms IEEE Trans. Educ. Technol. 49 120–9
[5] Malik D and Hasan E 2021 Challenges in digital Quranic education J. Islam. Educ. Res. 21 45–58
[6] Khan E 2020 AI-enhanced educational tools for religious studies IEEE Access 7 114–20
[7] Yusuf F 2020 Personalized Quranic learning for children Educ. Multimed. Int. 8 23–30
[8] Ibrahim G 2021 Deep learning in Islamic education systems IEEE Comput. Intell. Mag. 17 102–10
[9] Ali H 2021 Lightweight AI algorithms for mobile applications IEEE Trans. Mob. Comput. 18 92–9
[10] Mansour I and Karim J 2022 Meta-learning frameworks in educational AI J. Educ. Res. AI 15 130–42
[11] Saleh J 2023 Adaptive learning models for Quranic education IEEE Trans. Knowl. Data Eng. 35 1230–5
[12] Hassan K 2018 Real-time adaptation in digital learning platforms Procedia Computer Science vol 141 (ScienceDirect) pp 97–104
[13] Rashid L 2022 Meta-learning in low-resource environments J. Comput. Sci. Educ. 23 110–7
[14] Ahmad M 2021 Multimedia approaches to Quranic education J. Multimed. Technol. Educ. 20 84–93
[15] Zain N 2020 Interactive Quranic learning for children IEEE Access 8 1120–8
[16] Latif O 2020 The role of multimedia in religious education Educ. Innov. Rev. 16 43–50
[17] Malik P and Abdullah Q 2021 AI-based real-time learning models IEEE Trans. Comput. Educ. 27 212–21
[18] Chen K 2021 Artificial Intelligence in Islamic Studies: A Modern Approach IEEE Access 9 12345–57
[19] Doe J 2020 Random Forest in Education for Quran Studies Sci. J. AI 35 103–15
[20] Smith A, Johnson B and Williams C 2020 Optimizing Learning Patterns in Quranic Education IEEE Trans. Educ. 62 310–21
[21]Wang L 2019 Interactive AI for Quranic Educational Videos IEEE Access 7 20058–67
[22]Kim M 2019 AI in Quranic Studies: Enhancing Adaptive Learning for Children IEEE Access 6 21542–50
[23] Liu R 2022 AI-Assisted Quranic Learning Tools for Parents and Children IEEE Trans. Multimed. 15 120–32
[24] Kemenag K Qur’an Kemenag - Lajnah Pentashihan mushaf Al-Qur’an
[25] Dukes K The Quranic Arabic Corpus - Word by Word Grammar, Syntax and Morphology of the Holy Quran
[26] Fahad S A 2020 Use of Information Technology in the Teaching of Quran IEEE Access 8 195420–35
[27] Rahman F R and others 2021 Artificial Intelligence in Islamic Education: Ethical and Educational Implications ScienceDirect 50 812–25
[28] Hossain A and others 2021 Adaptive Video Streaming Using AI Techniques for Educational Platforms IEEE Trans. Multimed. 27 1230–45
[29] Liu Y, Zhang K, Li Y, Yan Z, Gao C, Chen R, Yuan Z, Huang Y, Sun H, Gao J, He L and Sun L 2024 Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models
[30] Norvig M J and Aljafri J G 2022 Integrating AI in Religious Education: A Case Study on Quran Learning ScienceDirect 49 159–70
[31] Anon Few-Shot Learning & Meta-Learning | Tutorial Boreal. AI