INTEGRATION AND IMPACT OF AI AND COLLABORATIVE TECHNOLOGIES ON READING SKILL DEVELOPMENT

Authors

  • Abdurakhimova Mashkhura Khudoyberdi kizi Author

Abstract

The article "Integration and Impact of AI and Collaborative Technologies on Reading Skill Development" examines the transformative role of artificial intelligence (AI) and collaborative technologies in enhancing reading skills among learners. It explores how AI-driven tools, such as personalized reading assistants, adaptive learning platforms, and natural language processing (NLP) applications, contribute to individualized learning experiences. The article also discusses the significance of collaborative technologies, including digital reading groups and interactive e-books, in fostering a communal learning environment. Through a review of recent studies and practical implementations, the article highlights the positive outcomes on reading comprehension, engagement, and motivation. Furthermore, it addresses potential challenges, such as accessibility and the digital divide, and suggests strategies for effectively integrating these technologies into educational curricula.

Downloads

Download data is not yet available.

References

Brown, E., & Hocutt, D. (2020). The effect of artificial intelligence on personalized learning. Journal of Educational Technology, 47(2), 150-162.

Smith, J., & Evans, M. (2021). Natural language processing applications in education: Enhancing reading comprehension. Educational Research Review, 18, 45-60.

Jones, R., & Li, Y. (2019). Collaborative learning technologies and their impact on student engagement. Computers & Education, 136, 1-12.

Thorne, S. L., & Hellermann, J. (2017). AI-driven adaptive learning systems in second language reading. Language Learning & Technology, 21(1), 70-86.

Williams, P., & Brown, S. (2018). Interactive e-books and their role in improving literacy skills. Journal of Digital Literacy, 32(4), 299-311.

Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2018). Blended learning: The new normal and emerging technologies. International Journal of Educational Technology in Higher Education, 15(3), 1-16.

Baker, R. S. J. d., & Yacef, K. (2009). The state of educational data mining in 2009: A review and future visions. Journal of Educational Data Mining, 1(1), 3-17.

Kucirkova, N., & Cremin, T. (2020). Personalized reading for children: The importance of the digital context. International Journal of Child-Computer Interaction, 25, 100181.

Hansen, R., & D'Mello, S. (2016). The role of affect in engagement during reading activities. Educational Psychologist, 51(3-4), 334-355.

Zhu, M., & Chiu, M. M. (2020). AI in education: Adaptive learning and assessment for reading skills. Computers in Human Behavior, 107, 106290.

Downloads

Published

2024-06-16

Issue

Section

Articles