The effectiveness of artificial intelligence on education: learning during the pandemic and in the future

https://doi.org/10.31295/ijecs.v3n1.195

Authors

  • Taghfirul Azhima Yoga Siswa Universitas Muhammadiyah Kalimantan Timur, Indonesia

Keywords:

artificial intelligence, education during pandemic, future learning, international publications

Abstract

This paper reviewed ten international publication about the effectiveness of Artificial Intelligence in Education: During the Pandemic and Learning in the future. Since the pandemic has disrupted world education, distance learning has become an alternative by relying on machine learning. To understand the extent of the power of artificial intelligence in education both during the COVID-19 period and the future learning period, we try to understand it through the example of ten international scientific publications that speak out about artificial intelligence in education today and the future of earning. Besides reviewing ten papers, we also conducted an online search engine for related literature. We performed searches with keywords such as "artificially intelligent," "learning during a pandemic," and "future learning," Then, we analyzed a phenomenological approach to ensure our findings answered the study questions under a qualitative method design. By considering the evidence of research and literature, we can summarize our findings, among others, that the critical understanding of artificial intelligence in education, the use of AI in education, typical Learning in the pandemic era, and the role of AI in pandemic learning as long as residents and future Learning still depend on data patterns and automation based on learning tasks that are smarter than usual.

Downloads

Download data is not yet available.

References

Alava, L. A. C., Castillo, G. A. L., Llanes, M. V., & Fernandez, M. C. (2017). Experiences of artificial intelligence application at international level. International research journal of engineering, IT & scientific research, 3(2), 9-18.

Allam, Z., Dey, G., & Jones, D. S. (2020). Artificial intelligence (AI) provided early detection of the coronavirus (COVID-19) in China and will influence future Urban health policy internationally. AI, 1(2), 156-165.

Arel, I., Rose, D. C., & Karnowski, T. P. (2010). Deep machine learning-a new frontier in artificial intelligence research [research frontier]. IEEE computational intelligence magazine, 5(4), 13-18.

Aslan, A. (2020). Pengembangan Bahan Ajar Berbasis Imtaq Dan Iptek Di Era Revolusi Industri 4.0 Pada Mata Pelajaran Sains Madrasah Ibtidaiyah. TaLimuna: Jurnal Pendidikan Islam, 9(1), 1-15.

Astini, N. K. S. (2020). Tantangan Dan Peluang Pemanfaatan Teknologi Informasi Dalam Pembelajaran Online Masa Covid-19. Cetta: Jurnal Ilmu Pendidikan, 3(2), 241-255.

Barton, D. C. (2020). Impacts of the COVID?19 pandemic on field instruction and remote teaching alternatives: Results from a survey of instructors. Ecology and evolution.

Beck, J. E., & Mostow, J. (2008). How who should practice: Using learning decomposition to evaluate the efficacy of different types of practice for different types of students. In International conference on intelligent tutoring systems (pp. 353-362). Springer, Berlin, Heidelberg.

Boden, M. A. (1998). Creativity and artificial intelligence. Artificial intelligence, 103(1-2), 347-356. https://doi.org/10.1016/S0004-3702(98)00055-1

Chao, T. N., Frost, A. S., Brody, R. M., Byrnes, Y. M., Cannady, S. B., Luu, N. N., ... & Newman, J. G. (2020). Creation of an interactive virtual surgical rotation for undergraduate medical education during the COVID-19 pandemic. Journal of Surgical Education. https://doi.org/10.1016/j.jsurg.2020.06.039

Di Vaio, A., Boccia, F., Landriani, L., & Palladino, R. (2020). Artificial intelligence in the agri-food system: Rethinking sustainable business models in the COVID-19 scenario. Sustainability, 12(12), 4851.

Du Boulay, B. (2016). Artificial intelligence as an effective classroom assistant. IEEE Intelligent Systems, 31(6), 76-81.

Engeström, Y., & Sannino, A. (2010). Studies of expansive learning: Foundations, findings and future challenges. Educational research review, 5(1), 1-24. https://doi.org/10.1016/j.edurev.2009.12.002

Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., ... & Wang, D. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14), 6531-6539.

Güzer, B., & Caner, H. (2014). The past, present and future of blended learning: an in depth analysis of literature. Procedia-social and behavioral sciences, 116, 4596-4603. https://doi.org/10.1016/j.sbspro.2014.01.992

Hilburg, R., Patel, N., Ambruso, S., Biewald, M. A., & Farouk, S. S. (2020). Medical education during the COVID-19 pandemic: learning from a distance. Advances in Chronic Kidney Disease. https://doi.org/10.1053/j.ackd.2020.05.017

Lalmuanawma, S., Hussain, J., & Chhakchhuak, L. (2020). Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review. Chaos, Solitons & Fractals, 110059. https://doi.org/10.1016/j.chaos.2020.110059

Lase, D. (2019). Education in the fourth industrial revolution age. Sundermann Journal, 1(1), 28-43.

Lee, S. J., Ward, K. P., Chang, O. D., & Downing, K. M. (2020). Parenting Activities and the Transition to Home-based Education During the COVID-19 Pandemic. Children and Youth Services Review, 105585. https://doi.org/10.1016/j.childyouth.2020.105585

Li, L., Qin, L., Xu, Z., Yin, Y., Wang, X., Kong, B., ... & Cao, K. (2020). Artificial intelligence distinguishes COVID-19 from community acquired pneumonia on chest CT. Radiology.

Lu, H., Li, Y., Chen, M., Kim, H., & Serikawa, S. (2018). Brain intelligence: go beyond artificial intelligence. Mobile Networks and Applications, 23(2), 368-375.

Luckin, R. (2018). Machine Learning and Human Intelligence: The Future of Education for the 21st Century. UCL IOE Press. UCL Institute of Education, University of London, 20 Bedford Way, London WC1H 0AL.

Nguyen, T. T. (2020). Artificial intelligence in the battle against coronavirus (COVID-19): a survey and future research directions. Preprint, DOI, 10.

Putra, P., Mizani, H., Basir, A., Muflihin, A., & Aslan, A. (2020). The Relevancy on Education Release Revolution 4.0 in Islamic Basic Education Perspective in Indonesia (An Analysis Study of Paulo Freire's Thought). Test Engineering & Management, 83, 10256-10263.

Ratten, V. (2020). Coronavirus (Covid-19) and the entrepreneurship education community. Journal of Enterprising Communities: People and Places in the Global Economy.

Samek, W., Wiegand, T., & Müller, K. R. (2017). Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models. arXiv preprint arXiv:1708.08296.

Turing, A. M. (1950). The word problem in semi-groups with cancellation. Annals of Mathematics, 491-505.

Valle-Cruz, D., & Sandoval-Almazan, R. (2018). Towards an understanding of artificial intelligence in government. In Proceedings of the 19th Annual International Conference on Digital Government Research: Governance in the Data Age (pp. 1-2).

Published

2020-11-26

How to Cite

Siswa, T. A. Y. . (2020). The effectiveness of artificial intelligence on education: learning during the pandemic and in the future. International Journal of Engineering & Computer Science, 3(1), 24-30. https://doi.org/10.31295/ijecs.v3n1.195