The Effect of Mobile Learning on the Study Results of Arab Language Students of MTs-TI Pariangan
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Arabic Language, Learning Outcomes, Mobile Learning
Abstract
Background. In today’s digital era, the use of technology in education is becoming increasingly important. Mobile learning in the form of Articulate Storyline application offers easy access and interactivity that can enrich students’ learning experience. However, not many studies have specifically investigated the impact of using the application on student learning outcomes at MTs-TI Pariangan.
Purpose. This study aims to evaluate the effect of using the Articulate Storyline application on students’ Arabic learning outcomes at MTs-TI Pariangan. Factors that influence the effectiveness of the app in improving academic achievement will be scrutinised to provide greater insight into the effectiveness of the app.
Method. The research method used is an experimental study with a pre-test and post-test design. The research sample was 8th grade students of MTs-TI Pariangan consisting of 20 students. Data was collected through an initial test before the use of the application and a final test after the period of application use.
Results. The results of this study showed a significant improvement in student learning outcomes after using the Articulate Storyline app. Students who actively used the application showed greater improvement in material understanding and academic achievement compared to those who did not use the application. The findings support the hypothesis that the use of the Articulate Storyline application has a positive effect on student learning outcomes at MTs-TI Pariangan.
Conclusion. This study shows that the use of Articulate Storyline mobile learning application significantly improves the Arabic learning outcomes of grade 8 students of MTs-TI Pariangan. Validity and reliability tests confirm that the instruments used have high consistency and reliability. The results of statistical analysis showed a significant difference between the pre-test and post-test scores, with an increase in the average score from 65.00 to 80.50.
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References
Aborokbah, M. (2021). Using augmented reality to support children with dyslexia. International Journal of Cloud Computing, 10(1), 17–25. https://doi.org/10.1504/IJCC.2021.113972
Ahmad, M., Jiang, P., Majeed, A., Umar, M., Khan, Z., & Muhammad, S. (2020). The dynamic impact of natural resources, technological innovations and economic growth on ecological footprint: An advanced panel data estimation. Resources Policy, 69, 101817. https://doi.org/10.1016/j.resourpol.2020.101817
AlKhuraym, B. Y., Ismail, M. M. B., & Bchir, O. (2022). Arabic Sign Language Recognition using Lightweight CNN-based Architecture. International Journal of Advanced Computer Science and Applications, 13(4). https://doi.org/10.14569/IJACSA.2022.0130438
Al-Megren, S. (2019). Analysis of user requirements for a mobile augmented reality application to support literacy development amongst hearing-impaired children. Journal of Information and Communication Technology, 18(1), 97–121.
Al-Qatawneh, S. (2022). Effects and Perceptions of Mobile Learning in Higher Education. Emerging Science Journal, 6(Query date: 2024-06-30 10:46:26), 78–91. https://doi.org/10.28991/ESJ-2022-SIED-06
Al-Razgan, M. (2019). Design and development of a mobile spelling game for elementary students using genetic algorithms. ACM International Conference Proceeding Series, Query date: 2024-06-30 10:46:26, 205–209. https://doi.org/10.1145/3369255.3369311
Bradley, L. (2023). Designing mobile language learning with Arabic speaking migrants. Interactive Learning Environments, 31(1), 514–526. https://doi.org/10.1080/10494820.2020.1799022
Chader, A. (2021). Sentiment analysis in google play store: Algerian reviews case. Lecture Notes in Networks and Systems, 156(Query date: 2024-06-30 10:46:26), 107–121. https://doi.org/10.1007/978-3-030-58861-8_8
Chandio, A. A. (2020). Cursive-Text: A Comprehensive Dataset for End-to-End Urdu Text Recognition in Natural Scene Images. Data in Brief, 31(Query date: 2024-06-30 10:46:26). https://doi.org/10.1016/j.dib.2020.105749
Ghani, M. T. A. (2022). The Impact of Mobile Digital Game in Learning Arabic Language at Tertiary Level. Contemporary Educational Technology, 14(1). https://doi.org/10.30935/cedtech/11480
Hassan, S., Hasib, A., Shahid, S., Asif, S., & Khan, A. (2019). Kahaniyan—Designing for Acquisition of Urdu as a Second Language. Dalam D. Lamas, F. Loizides, L. Nacke, H. Petrie, M. Winckler, & P. Zaphiris (Ed.), Human-Computer Interaction – INTERACT 2019 (Vol. 11747, hlm. 207–216). Springer International Publishing. https://doi.org/10.1007/978-3-030-29384-0_13
Jain, M., Singh, V., & Rani, A. (2019). A novel nature-inspired algorithm for optimization: Squirrel search algorithm. Swarm and Evolutionary Computation, 44, 148–175. https://doi.org/10.1016/j.swevo.2018.02.013
Lakens, D., & Caldwell, A. R. (2021). Simulation-Based Power Analysis for Factorial Analysis of Variance Designs. Advances in Methods and Practices in Psychological Science, 4(1), 251524592095150. https://doi.org/10.1177/2515245920951503
Lee, H.-H., Wang, Y.-N., Xia, W., Chen, C.-H., Rau, K.-M., Ye, L., Wei, Y., Chou, C.-K., Wang, S.-C., Yan, M., Tu, C.-Y., Hsia, T.-C., Chiang, S.-F., Chao, K. S. C., Wistuba, I. I., Hsu, J. L., Hortobagyi, G. N., & Hung, M.-C. (2019). Removal of N-Linked Glycosylation Enhances PD-L1 Detection and Predicts Anti-PD-1/PD-L1 Therapeutic Efficacy. Cancer Cell, 36(2), 168-178.e4. https://doi.org/10.1016/j.ccell.2019.06.008
Mahzari, M. (2021). Learning Arabic as a second language: An exploration of the efficacy of Arabic subtitles by netflix viewers. Asian ESP Journal, 17(3), 174–197.
Mohammed, T. A. S. (2021). Towards a Blended Programme for Arabic and Other Less Commonly Taught Languages (LCTLs) in the South African Higher Education Context. Education Research International, 2021(Query date: 2024-06-30 10:46:26). https://doi.org/10.1155/2021/1455705
Omar, N. (2020). Machine learning model for personalizing online Arabic journalism. International Journal of Advanced Computer Science and Applications, 11(4), 646–660. https://doi.org/10.14569/IJACSA.2020.0110484
Osimo, E. F., Pillinger, T., Rodriguez, I. M., Khandaker, G. M., Pariante, C. M., & Howes, O. D. (2020). Inflammatory markers in depression: A meta-analysis of mean differences and variability in 5,166 patients and 5,083 controls. Brain, Behavior, and Immunity, 87, 901–909. https://doi.org/10.1016/j.bbi.2020.02.010
Rahimi, N. A. Z. N. M. (2019). Mobile Applications for Teaching and Learning Arabic Braille. 2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application, ICSIMA 2018, Query date: 2024-06-30 10:46:26. https://doi.org/10.1109/ICSIMA.2018.8688763
Salem, N. (2019). Real-time glove and android application for visual and audible Arabic sign language translation. Procedia Computer Science, 163(Query date: 2024-06-30 10:46:26), 450–459. https://doi.org/10.1016/j.procs.2019.12.128
Salhi, D. E. (2019). Sentiment Analysis Application on Twitter for E-reputation. Proceedings - 2019 6th International Conference on Image and Signal Processing and their Applications, ISPA 2019, Query date: 2024-06-30 10:46:26. https://doi.org/10.1109/ISPA48434.2019.8966833
Voskergian, D. (2022). AMAR_ABSA: Arabic Mobile App Reviews Dataset Targeting Aspect-based Sentiment Analysis Tasks. Proceedings - 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022, Query date: 2024-06-30 10:46:26. https://doi.org/10.1109/ASYU56188.2022.9925324
Zhao, J., Xu, X., Jiang, H., & Ding, Y. (2020). The effectiveness of virtual reality-based technology on anatomy teaching: A meta-analysis of randomized controlled studies. BMC Medical Education, 20(1), 127. https://doi.org/10.1186/s12909-020-1994-z
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Copyright (c) 2024 Rifki Zaitul Ikhlas, Munirul Abidin
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