References
- Akinlar, A., Kamisli, M., U., Yildiz, H. S., Bozkurt, A. (2023). Bridging the digital divide in migrant education: Critical pedagogy and inclusive education approach. Journal of Qualitative Research in Education, (36), 30-53.
- Aravantinos, S., Lavidas, K., Voulgari, I., Papadakis, S., Karalis, T., Komis, V. (2024). Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus. Education Sciences, 14(7), 744.
- Asqui, J. D. C., Quichimbo, D. M. D., Vélez, L. E., Ajila, D. A. L. M., Campos, M. E. V. (2024). Inclusive Education from Cultural Diversity and ICT. Migration Letters, 21(S2), 400-412.
- Bennett, J., Lubben, F., Hogarth, S., Campbell, B. (2005). Systematic reviews of research in science education: rigour or rigidity? International Journal of Science Education, 27(4), 387-406.
- Bhutoria, A., (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model, Computers and Education: Artificial Intelligence, т. 3, No 3, p. online, 2022.
- Birenbaum, M. (2023). The Chatbots’ Challenge to Education: Disruption or Destruction? Education Sciences, 13(7), 711. Computers and Education: Artificial Intelligence, Vol.3,100050,
- Computers and Education: Artificial Intelligence, Volume 3,100050, https://doi.org/10.1016/j.caeai.2022.100050.
- Cope, B., Kalantzis, M. (2016). Big Data Comes to School: Implications for Learning, Assessment, and Research. AERA Open, 2(2). https://doi.org/10.1177/2332858416641907
- Dizon, G., Tang, D., Yamamoto,Y.,(2022), A case study of using Alexa for out-of-class, self-directed Japanese language learning, Computers and Education: Artificial Intelligence, Volume 3,100088, ISSN 2666-920X, https://doi.org/10.1016/j.caeai.2022.100088.
- Fernández-Martínez, C., Hernán-Losada, I., Fernández, A. (2021). Early introduction of AI in Spanish middle schools. A motivational study. KI-Künstliche Intelligenz, 35(2), 163-170.
- Fierli, C., Roverselli, C., Olmedo-Moreno, E. (2024). Non-Formal Education for the Inclusion of Unaccompanied Migrant Children in Italy. Education Sciences, 14(7), 781.
- Garg, S., Sharma, S. (2020). Impact of artificial intelligence in special need education to promote inclusive pedagogy. International Journal of Information and Education Technology, 10(7), 523-527.
- Gauffriau, M. (2017). A categorization of arguments for counting methods for publication and citation indicators. Journal of Informetrics, 11(3), 672-684.
- Gün, M., Yilmaz, A. (2020). Perceptions of secondary school 8th grade students regarding smart board concept. Journal of Language and Linguistic Studies, 16(1), 154-165. https://doi.org/10.17263/jlls.712676
- Han, D. E. (2020). The effects of voice-based AI chatbots on Korean EFL middle school students’ speaking competence and affective domains. Asia-pacific Journal of Convergent Research Interchange, 6(7), 71–80.
- Holmes, W., Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57, 542–570. https://doi.org/10.1111/ejed.12533
- Hopcan, S., Polat, E., Ozturk, M. E., Ozturk, L. (2023). Artificial intelligence in special education: A systematic review. Interactive Learning Environments, 31(10), 7335-7353.
- Ibrahim, H., Asim, R., Zaffar, F., Rahwan, T., Zaki, Y., (2023). Rethinking Homework in the Age of Artificial Intelligence, IEEE Intelligent Systems, vol. 38, no. 2, pp. 24-27, March-April 2023, doi: 10.1109/MIS.2023.3255599. ISSN 2666-920X, https://doi.org/10.1016/j.caeai.2022.100050
- Jauhiainen, J.S., Guerra, A.G. (2023), Generative AI and ChatGPT in School Children’s Education: Evidence from a School Lesson. Sustainability, n 15, 14025. https://doi.org/10.3390/su151814025
- Kapoor, V., Naik, P. (2020). Augmented Reality-Enabled Education for Middle Schools. SN COMPUT. SCI. 1, 166 https://doi.org/10.1007/s42979-020-00155-6
- Kaul, N., Deshpande, A., Mittal A., Raut, R., (2023). The Intersection of AI and Blockchain in Education: A Bibliometric and Thematic Analysis, 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA), Pune, India, 2023, pp. 1-6, doi: 10.1109/ICCUBEA58933.2023.10392092.
- Liu, P. L., Chen, C. J. (2023). Using an AI-Based Object Detection Translation Application for English Vocabulary Learning. Educational Technology & Society, 26(3), 5-20.
- Mathai, A. (2024). Enhancing Education for Underprivileged Children Through AI-Powered Native Language Learning Inclusive Education Through AI-Powered Native Language Learning. Available at SSRN 4899553.
- Migliarini, V., D’Alessio, S., Bocci, F. (2020). SEN Policies and migrant children in Italian schools: micro-exclusions through discourses of equality. Discourse: studies in the cultural politics of education, 41(6), 887-900.
- Minn, S., (2022). AI-assisted knowledge assessment techniques for adaptive learning environments, Murphy R.F. (2019). Artificial Intelligence Applications to Support K–12 Teachers and Teaching // A Review of Promising Applications, Opportunities, and Challenges. RAND Corporation, 2019. URL: https://www.rand.org/content/dam/rand/pubs/perspectives/PE300/PE315/RAND_PE315.pdf
- Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., Qiao, M. S. (2021). Conceptualizing AI literacy an exploratory review, Computers in Education: Artificial Intelligence, 2, https://doi.org/10.1016/j.caeai.2021.100041
- Nguyen, G., Nguyen, N., Giang, N. (2022). Situation and Proposals for Implementing Artificial Intelligence-based Instructional Technology in Vietnamese Secondary Schools. International Journal of Emerging Technologies in Learning (iJET), 17(18), 53-75.
- Nguyen, D., Nguyen, X., Than T., Nguyen, M., (2021). Automated Attendance System in the Classroom Using Artificial Intelligence and Internet of Things Technology, 2021 8th NAFOSTED Conference on Information and Computer Science (NICS), Hanoi, Vietnam, 2021, pp. 531-536, doi: 10.1109/NICS54270.2021.9700991.
- Ojwang, F. (2022). Accelerating integration of immigrants using artificial intelligence-driven solutions: The panacea for integration gaps in Finland. Technium Soc. Sci. J., 33, 549.
- Othman, N., Aydin, I., (2019). A Smart School by Using an Embedded Deep Learning Approach for Preventing Fake Attendance, 2019 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Turkey, 2019, pp. 1-6, doi: 10.1109/IDAP.2019.8875883.
- Qian, J., (2022). Research on Artificial Intelligence Technology of Virtual Reality Teaching Method in Digital Media Art Creation, Journal of Internet Technology, vol. 23, no. 1, pp. 125–132,
- Schleicher A., Borhan H., Cerna L., Chandra S., Fuster Rabella M., Santiago P., Vidal Q., Cabbar E., Torres Lima D., (2024). “The Potential Impact of Artificial Intelligence on Equity and Inclusion in Education”. OECD, No. 23
- Shamir, G., Levin, I. (2021). Neural Network Construction Practices in Elementary School. Künstl Intell 35, 181–189. https://doi.org/10.1007/s13218-021-00729-3
- Sousa, M.J.; Dal Mas, F., Gonçalves, S.P., Calandra, D., (2022). AI and Blockchain as New Triggers in the Education Arena. Eur. J. Investig. Health Psychol. Educ. Vol., 12, pp- 445–447. https://doi.org/10.3390/ejihpe12040032
- Thomas, D. R., Gatz, E., Gupta, S., Aleven, V., Koedinger, K. R. (2024, July). The Neglected 15%: Positive Effects of Hybrid Human-AI Tutoring Among Students with Disabilities. In International Conference on Artificial Intelligence in Education (pp. 409-423). Cham: Springer Nature Switzerland.
- Tsai, C.-Y.; Lai, Y.-C. (2022). Design and Validation of an Augmented Reality Teaching System for Primary Logic Programming Education. Sensors, Vol .22, 389. https://doi.org/10.3390/s22010389
- Varsha T. Lokare, Prakash M. Jadhav, (2024). An AI-based learning style prediction model for personalized and effective learning, Thinking Skills and Creativity, Vol. 51, 101421, https://doi.org/10.1016/j.tsc.2023.101421.
- Wang, Pei. “On Defining Artificial Intelligence” Journal of Artificial General Intelligence, vol.10, no.2, 2019, pp.1–37. https://doi.org/10.2478/jagi-2019-0002
- Wang, X., Gülenman, T., Pinkwart, N., Witt, C., Gloerfeld, C., Wrede, S., ( 2020). Automatic Assessment of Student Homework and Personalized Recommendation,” 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT), Tartu, Estonia, pp. 150-154, doi: 10.1109/ICALT49669.2020.00051.
- Wu, R., Yu, Z. (2024). Do AI chatbots improve students learning outcomes? Evidence from a meta-analysis. British Journal of Educational Technology, 55, 10–33. https://doi.org/10.1111/bjet.13334
- Xia, Q., Chiu, T. K., Lee, M., Sanusi, I. T., Dai, Y., Chai, C. S. (2022). A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education. Computers Education, 189, 104582.
- Xiaojuan Chen, H., (2021). Research on Personalized Recommendation Methods for Online Video Learning Resources, Applied Science, Vol. 1, No 11, p. 804.
- Xu, J., He, S., Jiang, H., Yang, Y., Cai, S. (2019). Design and Implementation of an English Lesson Based on Handwriting Recognition and Augmented Reality in Primary School. International Association for Development of the Information Society.
- Xu, X., C. Sun and X. Yu, (2023). A Personalized Intelligent Tutoring System for Mathematics Homework,” 2023 International Conference on Intelligent Education and Intelligent Research (IEIR), Wuhan, China, 2023, pp. 1-7, doi: 10.1109/IEIR59294.2023.10391237.
- Yang, C. (2022). The application of artificial intelligence in translation teaching. In Proceedings of the 4th International Conference on Intelligent Science and Technology (pp. 56–60).