Abstract
The implementation of chatbots in multiple platforms with which man interacts has allowed automating processes and being able to respond to requests, one of its applications is the educational field, where they are still experimenting with good results in some areas and in others analyzing their feasibility, the deployment of this technology has been used both in basic education and in higher education, the former mainly addresses the resolution of simple queries facilitating the work of the teacher, and the latter seeks to go further by offering itself as a learning assistant. This work focuses on understanding the impact that chatbots have on education and their integration in some areas of the educational process, analyzing the results offered by other research and real applications. Chatbots have proved to be effective and increase user efficiency by providing information and being a support, evaluation, and follow-up tool. They have even shown favorable results in several learning levels, being a source that centralizes information without the need for the user to access multiple sources to learn a subject or to monitor the level of learning of students or their own.
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References
Fortune Business Insights (2021) GlobeNewswire. https://www.globenewswire.com/news-release/2021/08/16/2280848/0/en/Learning-Management-System-Market-to-Reach-USD-44-49-Billion-by-2028-Rising-Usage-of-Internet-and-Cloud-Platforms-to-Boost-Growth-Fortune-Business-Insights.html.
Carayannopoulos S (2018) Using chatbots to aid transition. Int J Inf Learn Technol 35–21
Palasundram K, Sharef NM, Nasharuddin N, Kasmiran K, Azman A (2019) Sequence to sequence model performance for education CHATBOT. Int J Emerg Technol Learn (iJET) 14(24):56–68. https://doi.org/10.3991/ijet.v14i24.12187
Mauldin ML (1994) Chatterbots, tinymuds, and the turing test entering the loebner prize competition. In: Proceedings of the 12th National Conference on Artificial, pp 16–21
Bansal H, Khan R (2018) A review paper on human computer interaction. Int J Adv Res Comput Sci Softw Eng 8(4):53
Motta V, Guillen R, Rodriguez C (2019) Artificial neural networks to optimize learning and teaching in engineering careers. In: Proceedings of the 2019 International Symposium on Engineering Accreditation and Education, ICACIT 2019, 2019, 9130296. EID: 2-s2.0–85084220713
Shawar BA (2007) Chatbots: are they really useful? LDV-Forum 2007:29–49
Ramesh K, Ravishankaran S, Joshi A, Chandrasekaran K (2017) A survey of design techniques for conversational agents. In: Information, Communication and Computing Technology, pp. 336–350
BhashkarK (2019). www.medium.com https://bhashkarkunal.medium.com/conversational-ai-chatbot-using-deep-learning-how-bi-directional-lstm-machine-reading-38dc5cf5a5a3.
Szabo M (2002) CMI theory and practice: historical roots of learning management systems. In: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 929–936
Ahn JW et al (2017) Wizard’s apprentice: cognitive suggestion support for wizard-of-oz question answering. In: International Conference on Artificial Intelligence in Education. Springer, Cham
Gonda DE, Luo J, Wong YL, Lei CU (2019) Evaluation of developing educational Chatbots based on the seven principles for good teaching. In: 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), p. 8
Young S, Nichols HE (2017) A reflexive evaluation of technology-enhanced learning. Research in Learning Technology, p. 25
Petrlik I, Rodriguez C, Gonzales P (2019) M-learning applied to the improvement of the learning of university engineering students. In: Proceedings of the 2019 International Symposium on Engineering Accreditation and Education, ICACIT 2019. https://doi.org/10.1109/ICACIT46824.2019.9130215
Montes R, Herrera F, Nieto JMM (2018) Detection of academic failure and evaluation of teaching practice through automated communication with a Chatbot. In: XVIII Conference of the Spanish Association for Artificial Intelligence (CAEPIA), pp. 245–250
Sinha S, Basak S, Dey Y, Mondal A (2019) An educational Chatbot for answering queries. Emerg Technol Model Graph 17(7):55–60
María S, et al (2019) Tutor-bots application of chatbots in teacher tutoring, Unirioja, p. 10
Pereira J, Medina, H, Díaz, Ó (2017) Use of Chatbots in University Teaching, Unirioja, pp. 97–104
Rodriguez C, Angeles D, Chafloque R, Kaseng F, Pandey B (2020) Deep learning audio spectrograms processing to the early COVID-19 detection. In: 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN), Bhimtal, India, 2020, pp. 429–434. https://doi.org/10.1109/CICN49253.2020.9242583.
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Yataco-Irrazábal, S., Moscol-Albañil, I., Rodriguez, C., Lezama, P., Rodriguez, D., Pomachagua, Y. (2023). How Current Chatbots Applications Impact Education: An Overview. In: Arya, K.V., Tripathi, V.K., Rodriguez, C., Yusuf, E. (eds) Proceedings of 7th ASRES International Conference on Intelligent Technologies. ICIT 2022. Lecture Notes in Networks and Systems, vol 685. Springer, Singapore. https://doi.org/10.1007/978-981-99-1912-3_31
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