Abstract
In this article, we focus on Artificial Intelligence (AI) as a teaching topic. At the moment, it is important that every citizen is not a simple consumer of technology. We have challenges to overcome around digital sciences which must have the same place as life and earth sciences in the training of an individual in school curricula. Artificial intelligence is particularly concerned. How to overcome the initial representations of students who may think that these little machines work like magic. It is crucial that students can understand how these voices can inform us about time. The school has a big role to play. As for the teaching and learning of programming which has experienced an exceptional boom in recent years, the idea is not to make young people trained at the school of computer engineers. Rather, it is a question of fully preparing them for the world of tomorrow and understanding what AI is by asking these crucial questions. Beyond the learning mode (individual and / or collaborative), the modeling of user profiles and educational resources of a training domain represent essential parameters for the realization of adaptation to a user in order to recommend relevant educational resources and more finely customize a learning path for a single user in individual mode, but also for a group of users during the synchronization of events in collaborative mode. In this article, after an overview of the existing AI in education, we propose an architecture for the management of this type of adaptive learning.
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References
Pereira, S.W., Fishman, E.K., Rowe, S.P.: The future is now: how technology and entertainment are transforming education in the artificial intelligence era. J. Am. Coll. Radiol. 19(9), 1077–1078 (2022). https://doi.org/10.1016/j.jacr.2022.06.015
Zhu, X.: College English assisted teaching based on artificial intelligence. In: 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS), pp. 18–21 (2018). https://doi.org/10.1109/ICVRIS.2018.00013
Sanusi, I.T., Olaleye, S.A., Oyelere, S.S., Dixon, R.A.: Investigating learners’ competencies for artificial intelligence education in an African K-12 setting. Comput. Educ. Open 3 (2022). https://doi.org/10.1016/j.caeo.2022.100083
Shaikh, A.A., Kumar, A., Jani, K., Mitra, S., García-Tadeo, D.A., Devarajan, A.: The role of machine learning and artificial intelligence for making a digital classroom and its sustainable impact on education during covid-19. Mater. Today: Proc. 56(6), 3211–3215 (2022). https://doi.org/10.1016/j.matpr.2021.09.368
Brusilovsky, P., Peylo, C.: Adaptive and intelligent web-based educational systems. Int. J. Artif. Intell. Educ. (IJAIED) 13, 159–172
Agbanglanon, S.: Numerical tools in the learning of mechanical design: analysis of the links between external representations and visuo-spatial capacities in the design process. Cergy-Pontoise University, Val-d’Oise (2019). http://www.theses.fr/2019CERG1013
Carreño Valdivia, Y.: Contribution of technologies to the learning of written language in primary school: comparative approach of educational policies and teaching practices between France and Chile. Sorbonne University, Paris (2018). http://www.theses.fr/2018USPCB160
Fotsing, J.: The use of simulation software in hybrid devices in science training for engineering students: evaluative study at the ENSP - Ecole Nationale Supérieure Polytechnique - of Yaoundé, Cergy-Pontoise university, Val-d’Oise (2019). http://www.theses.fr/2019CERG1040
Boullé Loffreda, M.: The activity of organizing educational resources by teachers ENS Paris-Saclay, Paris (2021). http://www.theses.fr/s174473
Messaoui, A.: Development of the documentary expertise of teachers in situations of change in their teaching: the case of teachers of mathematics and English, ENS de Lyon, Lyon (2020). http://www.theses.fr/2019LYSEN052
Nyebe Atangana, S.: Effects of the use of XO computers on pedagogical practices in primary school in Cameroon: case of the public school of application of angale. CY Cergy University, Paris (2015). http://www.theses.fr/s144564
Pauty, C.: Systemic analysis of the process of appropriation of digital cultures. The Case of Operation Ordival. Paris University, Paris (2020). http://www.theses.fr/s176724
UNESCO: Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development, Working Papers on Education Policy, Paris, p. 46. UNESCO (2019)
Sanchez, E., Lama, M.: Artificial intelligence and education. In: Rabuñal Dopico, J.R., Dorado, J., Pazos, A. (eds.) Encyclopedia of Artificial Intelligence, Hershey (PA), Information Science Reference, pp. 138–143 (2008)
Van Ranst, J: The ethical issues of AI in education, education carrefour, Ref. of december 2020 (2019). https://carrefour-education.qc.ca/dossiers/lintelligence_artificielle_en_education/les_enjeux_ethiques_de_lia_en_education
Hou, J.-W., Jia, K., Jiao, X.-J.: Teaching evaluation on a WebGIS course based on dynamic self-adaptive teaching-learning-based optimization. J. Central South Univ. 26(3), 640–653 (2019). https://doi.org/10.1007/s11771-019-4035-5
Rahayu, N.W., Ferdiana, R., Kusumawardani, S.S.: A systematic review of learning path recommender systems. Educ. Inf. Technol. (2022). https://doi.org/10.1007/s10639-022-11460-3
Kanya Kumari, L., Naga Jagadesh, B.: An adaptive teaching learning based optimization technique for feature selection to classify mammogram medical images in breast cancer detection. Int. J. Syst. Assur. Eng. Manag. (2022). https://doi.org/10.1007/s13198-021-01598-7
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Rahioui, F., El Ghzaoui, M., Jouti, M.A.T., Jamil, M.O., Qjidaa, H. (2023). Machine Learning with Reinforcement for Optimal and Adaptive Learning. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2023. Lecture Notes in Networks and Systems, vol 669. Springer, Cham. https://doi.org/10.1007/978-3-031-29860-8_15
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