Utilization of ICT in Improving Four Arabic Language Learning Skills in Higher Education
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The use of ICT is everything that is used to communicate and create, manage and distribute information. The use of ICT can help Arabic language students in improving the four maharah skills. By applying ICT in learning, students' difficulties in the Arabic learning process can be significantly reduced. This is due to the innovation in learning in higher education by utilizing ICT during the teaching and learning process of students. The purpose of this research is to support Arabic language learning with ICT learning system in higher education. The method used in this research is quantitative method, which can show that this research contains numerical data. The data was obtained by using geogle from as a means to create a questionnaire containing questions and then distributed to respondents who were used as research subjects. The results showed that with the utilization of ICT in learning, it can improve four Arabic language skills in college. The conclusion of this study is that ICT can be used in learning Arabic to increase student enthusiasm and know the ability to understand Arabic learning in college. The limitation of this study is that the researcher only conducted research on the utilization of ICT as a medium of Arabic learning
Ai, T., Yang, Z., Hou, H., Zhan, C., Chen, C., Lv, W., Tao, Q., Sun, Z., & Xia, L. (2020). Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology, 296(2), E32–E40. https://doi.org/10.1148/radiol.2020200642
Akbari, M., Khodayari, M., Khaleghi, A., Danesh, M., & Padash, H. (2021). Technological innovation research in the last six decades: A bibliometric analysis. European Journal of Innovation Management, 24(5), 1806–1831. https://doi.org/10.1108/EJIM-05-2020-0166
Alawamleh, M., Al-Twait, L. M., & Al-Saht, G. R. (2022). The effect of online learning on communication between instructors and students during Covid-19 pandemic. Asian Education and Development Studies, 11(2), 380–400. https://doi.org/10.1108/AEDS-06-2020-0131
Almagro Armenteros, J. J., Tsirigos, K. D., Sønderby, C. K., Petersen, T. N., Winther, O., Brunak, S., von Heijne, G., & Nielsen, H. (2019). SignalP 5.0 improves signal peptide predictions using deep neural networks. Nature Biotechnology, 37(4), 420–423. https://doi.org/10.1038/s41587-019-0036-z
Appio, F. P., Lima, M., & Paroutis, S. (2019). Understanding Smart Cities: Innovation ecosystems, technological advancements, and societal challenges. Technological Forecasting and Social Change, 142, 1–14. https://doi.org/10.1016/j.techfore.2018.12.018
Asadi, S., Wexler, A. S., Cappa, C. D., Barreda, S., Bouvier, N. M., & Ristenpart, W. D. (2019). Aerosol emission and superemission during human speech increase with voice loudness. Scientific Reports, 9(1), 2348. https://doi.org/10.1038/s41598-019-38808-z
Bokolo Anthony Jnr. (2020). Use of Telemedicine and Virtual Care for Remote Treatment in Response to COVID-19 Pandemic. Journal of Medical Systems, 44(7), 132. https://doi.org/10.1007/s10916-020-01596-5
Campbell, K. L., Winters-Stone, K. M., Wiskemann, J., May, A. M., Schwartz, A. L., Courneya, K. S., Zucker, D. S., Matthews, C. E., Ligibel, J. A., Gerber, L. H., Morris, G. S., Patel, A. V., Hue, T. F., Perna, F. M., & Schmitz, K. H. (2019). Exercise Guidelines for Cancer Survivors: Consensus Statement from International Multidisciplinary Roundtable. Medicine & Science in Sports & Exercise, 51(11), 2375–2390. https://doi.org/10.1249/MSS.0000000000002116
Chan, P. P., & Lowe, T. M. (2019). tRNAscan-SE: Searching for tRNA Genes in Genomic Sequences. In M. Kollmar (Ed.), Gene Prediction (Vol. 1962, pp. 1–14). Springer New York. https://doi.org/10.1007/978-1-4939-9173-0_1
Chang, Y., Iakovou, E., & Shi, W. (2020). Blockchain in global supply chains and cross border trade: A critical synthesis of the state-of-the-art, challenges and opportunities. International Journal of Production Research, 58(7), 2082–2099. https://doi.org/10.1080/00207543.2019.1651946
Chen, Z., & Zhang, H. (2019). Learning Implicit Fields for Generative Shape Modeling. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 5932–5941. https://doi.org/10.1109/CVPR.2019.00609
ChengChiang Chen, J., & Kent, S. (2020). Task engagement, learner motivation and avatar identities of struggling English language learners in the 3D virtual world. System, 88, 102168. https://doi.org/10.1016/j.system.2019.102168
Department of Mathematics, Shanghai Normal University Shanghai 200234, China, E-mail: zenglc@hotmail.com, Ceng, L.-C., Petru?el, A., Department of Mathematics, Babes-Bolyai University Kogalniceanu Str., no. 1, 400084 Cluj-Napoca, Romania, E-mail: petrusel@math.ubbcluj.ro, Yao, J.-C., Center for General Education, China Medical University, Taichung 40402, Taiwan and Department of Applied Mathematics, National Sun Yat-sen University Kaohsiung, Taiwan 804, E-mail: yaojc@mail.cmu.edu.tw, Yao, Y., & Department of Mathematics Tianjin Polytechnic University Tianjin 300387, China and School of Mathematics and Information Science, North Minzu University Yinchuan, 750021, China, E-mail: yaoyonghong@aliyun.com. (2019). Systems of variational inequalities with hierarchical variational inequality constraints for Lipschitzian pseudocontractions. Fixed Point Theory, 20(1), 113–134. https://doi.org/10.24193/fpt-ro.2019.1.07
Dollinger, M., & Lodge, J. (2020). Student-staff co-creation in higher education: An evidence-informed model to support future design and implementation. Journal of Higher Education Policy and Management, 42(5), 532–546. https://doi.org/10.1080/1360080X.2019.1663681
Giamarellos-Bourboulis, E. J., Netea, M. G., Rovina, N., Akinosoglou, K., Antoniadou, A., Antonakos, N., Damoraki, G., Gkavogianni, T., Adami, M.-E., Katsaounou, P., Ntaganou, M., Kyriakopoulou, M., Dimopoulos, G., Koutsodimitropoulos, I., Velissaris, D., Koufargyris, P., Karageorgos, A., Katrini, K., Lekakis, V., … Koutsoukou, A. (2020). Complex Immune Dysregulation in COVID-19 Patients with Severe Respiratory Failure. Cell Host & Microbe, 27(6), 992-1000.e3. https://doi.org/10.1016/j.chom.2020.04.009
Hwangbo, J., Lee, J., Dosovitskiy, A., Bellicoso, D., Tsounis, V., Koltun, V., & Hutter, M. (2019). Learning agile and dynamic motor skills for legged robots. Science Robotics, 4(26), eaau5872. https://doi.org/10.1126/scirobotics.aau5872
Jahroni, J. (2020). Saudi Arabia Charity and the Institutionalization of Indonesian Salafism. Al-Jami’ah: Journal of Islamic Studies, 58(1), 35–62. https://doi.org/10.14421/ajis.2020.581.35-62
Jeyanathan, M., Afkhami, S., Smaill, F., Miller, M. S., Lichty, B. D., & Xing, Z. (2020). Immunological considerations for COVID-19 vaccine strategies. Nature Reviews Immunology, 20(10), 615–632. https://doi.org/10.1038/s41577-020-00434-6
Jia, L., Xu, Y., Sun, Y., Feng, S., Yu, L., & Anpalagan, A. (2019). A Game-Theoretic Learning Approach for Anti-Jamming Dynamic Spectrum Access in Dense Wireless Networks. IEEE Transactions on Vehicular Technology, 68(2), 1646–1656. https://doi.org/10.1109/TVT.2018.2889336
Kang, L., Ma, S., Chen, M., Yang, J., Wang, Y., Li, R., Yao, L., Bai, H., Cai, Z., Xiang Yang, B., Hu, S., Zhang, K., Wang, G., Ma, C., & Liu, Z. (2020). Impact on mental health and perceptions of psychological care among medical and nursing staff in Wuhan during the 2019 novel coronavirus disease outbreak: A cross-sectional study. Brain, Behavior, and Immunity, 87, 11–17. https://doi.org/10.1016/j.bbi.2020.03.028
Lin, H.-C., & Hwang, G.-J. (2019). Research trends of flipped classroom studies for medical courses: A review of journal publications from 2008 to 2017 based on the technology-enhanced learning model. Interactive Learning Environments, 27(8), 1011–1027. https://doi.org/10.1080/10494820.2018.1467462
Liu, C., Ginn, H. M., Dejnirattisai, W., Supasa, P., Wang, B., Tuekprakhon, A., Nutalai, R., Zhou, D., Mentzer, A. J., Zhao, Y., Duyvesteyn, H. M. E., López-Camacho, C., Slon-Campos, J., Walter, T. S., Skelly, D., Johnson, S. A., Ritter, T. G., Mason, C., Costa Clemens, S. A., … Screaton, G. R. (2021). Reduced neutralization of SARS-CoV-2 B.1.617 by vaccine and convalescent serum. Cell, 184(16), 4220-4236.e13. https://doi.org/10.1016/j.cell.2021.06.020
Lundervold, A. S., & Lundervold, A. (2019). An overview of deep learning in medical imaging focusing on MRI. Zeitschrift Für Medizinische Physik, 29(2), 102–127. https://doi.org/10.1016/j.zemedi.2018.11.002
Menni, C., Valdes, A. M., Freidin, M. B., Sudre, C. H., Nguyen, L. H., Drew, D. A., Ganesh, S., Varsavsky, T., Cardoso, M. J., El-Sayed Moustafa, J. S., Visconti, A., Hysi, P., Bowyer, R. C. E., Mangino, M., Falchi, M., Wolf, J., Ourselin, S., Chan, A. T., Steves, C. J., & Spector, T. D. (2020). Real-time tracking of self-reported symptoms to predict potential COVID-19. Nature Medicine, 26(7), 1037–1040. https://doi.org/10.1038/s41591-020-0916-2
Mi, H., Muruganujan, A., Ebert, D., Huang, X., & Thomas, P. D. (2019). PANTHER version 14: More genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Research, 47(D1), D419–D426. https://doi.org/10.1093/nar/gky1038
Molina, M., & Garip, F. (2019). Machine Learning for Sociology. Annual Review of Sociology, 45(1), 27–45. https://doi.org/10.1146/annurev-soc-073117-041106
Nutt, N., & Kubjas, A. (2021). The model of trees for the restoration of historical manor parks in Estonia. Landscape Architecture and Art, 17(17), 22–29. https://doi.org/10.22616/j.landarchart.2020.17.03
Obleser, J., & Kayser, C. (2019). Neural Entrainment and Attentional Selection in the Listening Brain. Trends in Cognitive Sciences, 23(11), 913–926. https://doi.org/10.1016/j.tics.2019.08.004
Odysseas Kosmatos, K., Theofylaktos, L., Giannakaki, E., Deligiannis, D., Konstantakou, M., & Stergiopoulos, T. (2019). ?ethylammonium Chloride: A Key Additive for Highly Efficient, Stable, and Up?Scalable Perovskite Solar Cells. ENERGY & ENVIRONMENTAL MATERIALS, 2(2), 79–92. https://doi.org/10.1002/eem2.12040
Patricia Aguilera-Hermida, A. (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1, 100011. https://doi.org/10.1016/j.ijedro.2020.100011
Perez-Riverol, Y., Csordas, A., Bai, J., Bernal-Llinares, M., Hewapathirana, S., Kundu, D. J., Inuganti, A., Griss, J., Mayer, G., Eisenacher, M., Pérez, E., Uszkoreit, J., Pfeuffer, J., Sachsenberg, T., Y?lmaz, ?., Tiwary, S., Cox, J., Audain, E., Walzer, M., … Vizcaíno, J. A. (2019). The PRIDE database and related tools and resources in 2019: Improving support for quantification data. Nucleic Acids Research, 47(D1), D442–D450. https://doi.org/10.1093/nar/gky1106
Puri, N., Coomes, E. A., Haghbayan, H., & Gunaratne, K. (2020). Social media and vaccine hesitancy: New updates for the era of COVID-19 and globalized infectious diseases. Human Vaccines & Immunotherapeutics, 16(11), 2586–2593. https://doi.org/10.1080/21645515.2020.1780846
Ruiz?Fernández, M. D., Ramos?Pichardo, J. D., Ibáñez?Masero, O., Cabrera?Troya, J., Carmona?Rega, M. I., & Ortega?Galán, Á. M. (2020). Compassion fatigue, burnout, compassion satisfaction and perceived stress in healthcare professionals during the COVID?19 health crisis in Spain. Journal of Clinical Nursing, 29(21–22), 4321–4330. https://doi.org/10.1111/jocn.15469
Rydyznski Moderbacher, C., Ramirez, S. I., Dan, J. M., Grifoni, A., Hastie, K. M., Weiskopf, D., Belanger, S., Abbott, R. K., Kim, C., Choi, J., Kato, Y., Crotty, E. G., Kim, C., Rawlings, S. A., Mateus, J., Tse, L. P. V., Frazier, A., Baric, R., Peters, B., … Crotty, S. (2020). Antigen-Specific Adaptive Immunity to SARS-CoV-2 in Acute COVID-19 and Associations with Age and Disease Severity. Cell, 183(4), 996-1012.e19. https://doi.org/10.1016/j.cell.2020.09.038
Shannon, A., Le, N. T.-T., Selisko, B., Eydoux, C., Alvarez, K., Guillemot, J.-C., Decroly, E., Peersen, O., Ferron, F., & Canard, B. (2020). Remdesivir and SARS-CoV-2: Structural requirements at both nsp12 RdRp and nsp14 Exonuclease active-sites. Antiviral Research, 178, 104793. https://doi.org/10.1016/j.antiviral.2020.104793
Shea, P., Li, C. S., Swan, K., & Pickett, A. (2019). DEVELOPING LEARNING COMMUNITY IN ONLINE ASYNCHRONOUS COLLEGE COURSES: THE ROLE OF TEACHING PRESENCE. Online Learning, 9(4). https://doi.org/10.24059/olj.v9i4.1779
Slamet, Mohamed, I. I., & Samsuri, F. (2020). Campus Hybrid Intrusion Detection System Using SNORT and C4.5 Algorithm. In A. N. Kasruddin Nasir, M. A. Ahmad, M. S. Najib, Y. Abdul Wahab, N. A. Othman, N. M. Abd Ghani, A. Irawan, S. Khatun, R. M. T. Raja Ismail, M. M. Saari, M. R. Daud, & A. A. Mohd Faudzi (Eds.), InECCE2019 (Vol. 632, pp. 591–603). Springer Singapore. https://doi.org/10.1007/978-981-15-2317-5_50
Sukendro, S., Habibi, A., Khaeruddin, K., Indrayana, B., Syahruddin, S., Makadada, F. A., & Hakim, H. (2020). Using an extended Technology Acceptance Model to understand students’ use of e-learning during Covid-19: Indonesian sport science education context. Heliyon, 6(11), e05410. https://doi.org/10.1016/j.heliyon.2020.e05410
Vinyals, O., Babuschkin, I., Czarnecki, W. M., Mathieu, M., Dudzik, A., Chung, J., Choi, D. H., Powell, R., Ewalds, T., Georgiev, P., Oh, J., Horgan, D., Kroiss, M., Danihelka, I., Huang, A., Sifre, L., Cai, T., Agapiou, J. P., Jaderberg, M., … Silver, D. (2019). Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nature, 575(7782), 350–354. https://doi.org/10.1038/s41586-019-1724-z
Wang, J., Wei, G., Wei, C., & Wei, Y. (2020). MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment. Defence Technology, 16(1), 208–216. https://doi.org/10.1016/j.dt.2019.06.019
Wang, Y., Zhang, D., Du, G., Du, R., Zhao, J., Jin, Y., Fu, S., Gao, L., Cheng, Z., Lu, Q., Hu, Y., Luo, G., Wang, K., Lu, Y., Li, H., Wang, S., Ruan, S., Yang, C., Mei, C., … Wang, C. (2020). Remdesivir in adults with severe COVID-19: A randomised, double-blind, placebo-controlled, multicentre trial. The Lancet, 395(10236), 1569–1578. https://doi.org/10.1016/S0140-6736(20)31022-9
Zhou, M., Wang, H., Zeng, X., Yin, P., Zhu, J., Chen, W., Li, X., Wang, L., Wang, L., Liu, Y., Liu, J., Zhang, M., Qi, J., Yu, S., Afshin, A., Gakidou, E., Glenn, S., Krish, V. S., Miller-Petrie, M. K., … Liang, X. (2019). Mortality, morbidity, and risk factors in China and its provinces, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 394(10204), 1145–1158. https://doi.org/10.1016/S0140-6736(19)30427-1
Zhuang, F., Qi, Z., Duan, K., Xi, D., Zhu, Y., Zhu, H., Xiong, H., & He, Q. (2021). A Comprehensive Survey on Transfer Learning. Proceedings of the IEEE, 109(1), 43–76. https://doi.org/10.1109/JPROC.2020.3004555
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