Understanding Technological Trends in Education: How Artificial Intelligence Helps Learning in Colleges In Susta
Abstract
Background. Understanding technological trends is how popular technology is used to assist learning, Artificial Intelligence is created and programmed and designed by humans to assist activities in completing human tasks.
Purpose to understand technological trends in education how Artificial Intelligence helps learning in higher education in a sustainable manner, where in the last year 2020 there was Covid 19 which had spread throughout the world so there were online classes, but over the years the problem has ended, that's what caused it technology trend of Artificial intelligence in assisting learning.
Method. using the method of conducting interviews from sources directly, conducting interviews with this research with the aim of getting the correct data.
Results. shows that understanding the trend of Artificial Intelligence technology in helping learning in higher education in a sustainable manner is very helpful and its use has increased in recent years due to the impact of covid 19 so that it has greatly affected online learning.
Conclusion it was concluded that the results of the interviews showed the use of Artificial Intelligence in assisting learning through individuals in using technology in completing learning tasks and assisting when the learning process takes place in the classroom is very helpful, technology as a medium used in learning, students still use the same technology cannot be said in sustainable
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References
Anjum, N., He, J.-H., Ain, Q. T., & Tian, D. (2021). LI-HE’S MODIFIED HOMOTOPY PERTURBATION METHOD FOR DOUBLY-CLAMPED ELECTRICALLY ACTUATED MICROBEAMS-BASED MICROELECTROMECHANICAL SYSTEM. Facta Universitatis, Series: Mechanical Engineering, 19(4), 601. https://doi.org/10.22190/FUME210112025A
Bai, C., Dallasega, P., Orzes, G., & Sarkis, J. (2020). Industry 4.0 technologies assessment: A sustainability perspective. International Journal of Production Economics, 229, 107776. https://doi.org/10.1016/j.ijpe.2020.107776
Bao, L., Yang, J., Wu, C. Q., Qi, H., Zhang, X., & Cai, S. (2022). XML2HBase: Storing and querying large collections of XML documents using a NoSQL database system. Journal of Parallel and Distributed Computing, 161, 83–99. https://doi.org/10.1016/j.jpdc.2021.11.003
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/j.inffus.2019.12.012
Beagan, J. A., & Phillips-Cremins, J. E. (2020). On the existence and functionality of topologically associating domains. Nature Genetics, 52(1), 8–16. https://doi.org/10.1038/s41588-019-0561-1
Bilal, M., & Iqbal, H. M. N. (2020). Ligninolytic Enzymes Mediated Ligninolysis: An Untapped Biocatalytic Potential to Deconstruct Lignocellulosic Molecules in a Sustainable Manner. Catalysis Letters, 150(2), 524–543. https://doi.org/10.1007/s10562-019-03096-9
Bouckaert, R., Vaughan, T. G., Barido-Sottani, J., Duchêne, S., Fourment, M., Gavryushkina, A., Heled, J., Jones, G., Kühnert, D., De Maio, N., Matschiner, M., Mendes, F. K., Müller, N. F., Ogilvie, H. A., du Plessis, L., Popinga, A., Rambaut, A., Rasmussen, D., Siveroni, I., … Drummond, A. J. (2019). BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis. PLOS Computational Biology, 15(4), e1006650. https://doi.org/10.1371/journal.pcbi.1006650
Bragazzi, N. L., Dai, H., Damiani, G., Behzadifar, M., Martini, M., & Wu, J. (2020). How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic. International Journal of Environmental Research and Public Health, 17(9), 3176. https://doi.org/10.3390/ijerph17093176
Chiarella, S. G., Torromino, G., Gagliardi, D. M., Rossi, D., Babiloni, F., & Cartocci, G. (2022). Investigating the negative bias towards artificial intelligence: Effects of prior assignment of AI-authorship on the aesthetic appreciation of abstract paintings. Computers in Human Behavior, 137, 107406. https://doi.org/10.1016/j.chb.2022.107406
Darmayenti, D., Besral, B., & Yustina, L. S. (2021). Developing EFL religious characters and local wisdom based EFL textbook for Islamic higher education. Studies in English Language and Education, 8(1), 157–180. https://doi.org/10.24815/siele.v8i1.18263
Ding, D., He, F., Yuan, L., Pan, Z., Wang, L., & Ros, M. (2021). The first step towards intelligent wire arc additive manufacturing: An automatic bead modelling system using machine learning through industrial information integration. Journal of Industrial Information Integration, 23, 100218. https://doi.org/10.1016/j.jii.2021.100218
Doncel, J., Gast, N., Gaujal, B., ,University of the Basque Country, UPV/EHU, Spain, & ,Univ. Grenoble Alpes, Inria, CNRS, LIG, F-38000 Grenoble, France. (2019). Discrete mean field games: Existence of equilibria and convergence. Journal of Dynamics & Games, 0(0), 1–19. https://doi.org/10.3934/jdg.2019016
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
Ellison, B., Savchenko, O., Nikolaus, C. J., & Duff, B. R. L. (2019). Every plate counts: Evaluation of a food waste reduction campaign in a university dining hall. Resources, Conservation and Recycling, 144, 276–284. https://doi.org/10.1016/j.resconrec.2019.01.046
Fernández-Batanero, J. M., Cabero-Almenara, J., Román-Graván, P., & Palacios-Rodríguez, A. (2022). Knowledge of university teachers on the use of digital resources to assist people with disabilities. The case of Spain. Education and Information Technologies, 27(7), 9015–9029. https://doi.org/10.1007/s10639-022-10965-1
Florian, L. (2019). On the necessary co-existence of special and inclusive education. International Journal of Inclusive Education, 23(7–8), 691–704. https://doi.org/10.1080/13603116.2019.1622801
Grover, P., Kar, A. K., & Dwivedi, Y. K. (2022). Understanding artificial intelligence adoption in operations management: Insights from the review of academic literature and social media discussions. Annals of Operations Research, 308(1–2), 177–213. https://doi.org/10.1007/s10479-020-03683-9
Jena, A. K., Kulkarni, A., & Miyasaka, T. (2019). Halide Perovskite Photovoltaics: Background, Status, and Future Prospects. Chemical Reviews, 119(5), 3036–3103. https://doi.org/10.1021/acs.chemrev.8b00539
Kelson, D. M., Mathiassen, S. E., & Srinivasan, D. (2019). Trapezius muscle activity variation during computer work performed by individuals with and without neck-shoulder pain. Applied Ergonomics, 81, 102908. https://doi.org/10.1016/j.apergo.2019.102908
Li, M. (2020). Multimodal pedagogy in TESOL teacher education: Students’ perspectives. System, 94, 102337. https://doi.org/10.1016/j.system.2020.102337
Liu, Y., Wang, X., Li, L., Cheng, S., & Chen, Z. (2019). A Novel Lane Change Decision-Making Model of Autonomous Vehicle Based on Support Vector Machine. IEEE Access, 7, 26543–26550. https://doi.org/10.1109/ACCESS.2019.2900416
Liu, Z., Jiang, P., Zhang, L., & Niu, X. (2020). A combined forecasting model for time series: Application to short-term wind speed forecasting. Applied Energy, 259, 114137. https://doi.org/10.1016/j.apenergy.2019.114137
Makowski, D., Ben-Shachar, M. S., Chen, S. H. A., & Lüdecke, D. (2019). Indices of Effect Existence and Significance in the Bayesian Framework. Frontiers in Psychology, 10, 2767. https://doi.org/10.3389/fpsyg.2019.02767
Mazza, C., Ricci, E., Biondi, S., Colasanti, M., Ferracuti, S., Napoli, C., & Roma, P. (2020). A Nationwide Survey of Psychological Distress among Italian People during the COVID-19 Pandemic: Immediate Psychological Responses and Associated Factors. International Journal of Environmental Research and Public Health, 17(9), 3165. https://doi.org/10.3390/ijerph17093165
Moriguchi, T., Harii, N., Goto, J., Harada, D., Sugawara, H., Takamino, J., Ueno, M., Sakata, H., Kondo, K., Myose, N., Nakao, A., Takeda, M., Haro, H., Inoue, O., Suzuki-Inoue, K., Kubokawa, K., Ogihara, S., Sasaki, T., Kinouchi, H., … Shimada, S. (2020). A first case of meningitis/encephalitis associated with SARS-Coronavirus-2. International Journal of Infectious Diseases, 94, 55–58. https://doi.org/10.1016/j.ijid.2020.03.062
Nie, W., Li, T., & Zhu, L. (2020). Market demand and government regulation for quality grading system of agricultural products in China. Journal of Retailing and Consumer Services, 56, 102134. https://doi.org/10.1016/j.jretconser.2020.102134
Qin, Z., Zhao, S., Pang, X., Safaei, B., & Chu, F. (2020). A unified solution for vibration analysis of laminated functionally graded shallow shells reinforced by graphene with general boundary conditions. International Journal of Mechanical Sciences, 170, 105341. https://doi.org/10.1016/j.ijmecsci.2019.105341
Ravichandran, C., Logeswari, K., & Jarad, F. (2019). New results on existence in the framework of Atangana–Baleanu derivative for fractional integro-differential equations. Chaos, Solitons & Fractals, 125, 194–200. https://doi.org/10.1016/j.chaos.2019.05.014
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J., Carvalhais, N., & Prabhat. (2019). Deep learning and process understanding for data-driven Earth system science. Nature, 566(7743), 195–204. https://doi.org/10.1038/s41586-019-0912-1
Sanche, S., Lin, Y. T., Xu, C., Romero-Severson, E., Hengartner, N., & Ke, R. (2020). High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2. Emerging Infectious Diseases, 26(7), 1470–1477. https://doi.org/10.3201/eid2607.200282
Sandín, B., Valiente, R. M., García-Escalera, J., & Chorot, P. (2020). Impacto psicológico de la pandemia de COVID-19: Efectos negativos y positivos en población española asociados al periodo de confinamiento nacional. Revista de Psicopatología y Psicología Clínica, 25(1), 1. https://doi.org/10.5944/rppc.27569
Sangster, A., Stoner, G., & Flood, B. (2020). Insights into accounting education in a COVID-19 world. Accounting Education, 29(5), 431–562. https://doi.org/10.1080/09639284.2020.1808487
Swennen, G. R. J., Pottel, L., & Haers, P. E. (2020). Custom-made 3D-printed face masks in case of pandemic crisis situations with a lack of commercially available FFP2/3 masks. International Journal of Oral and Maxillofacial Surgery, 49(5), 673–677. https://doi.org/10.1016/j.ijom.2020.03.015
Wong, J., Baars, M., Davis, D., Van Der Zee, T., Houben, G.-J., & Paas, F. (2019). Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review. International Journal of Human–Computer Interaction, 35(4–5), 356–373. https://doi.org/10.1080/10447318.2018.1543084
Wu, F., Zhao, S., Yu, B., Chen, Y.-M., Wang, W., Song, Z.-G., Hu, Y., Tao, Z.-W., Tian, J.-H., Pei, Y.-Y., Yuan, M.-L., Zhang, Y.-L., Dai, F.-H., Liu, Y., Wang, Q.-M., Zheng, J.-J., Xu, L., Holmes, E. C., & Zhang, Y.-Z. (2020). A new coronavirus associated with human respiratory disease in China. Nature, 579(7798), 265–269. https://doi.org/10.1038/s41586-020-2008-3
Yan, R., Zhang, Y., Li, Y., Xia, L., Guo, Y., & Zhou, Q. (2020). Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2. Science, 367(6485), 1444–1448. https://doi.org/10.1126/science.abb2762
Yaros, R. A., & Misak, J. (2021). Completing College Writing Assignments on Mobile Phones: Comparing Students’ Attitudes and Engagement Across Disciplines and Age. Journalism & Mass Communication Educator, 76(2), 216–227. https://doi.org/10.1177/1077695820942422
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Copyright (c) 2023 Adam Mudinillah, Fetri Yeni J, Ahmad Firdaus bin Mohd Noor

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