Revolutionizing Language Learning with Smart Technologies
DOI:
https://doi.org/10.5281/Keywords:
Language learning, geography, mobile learning, smart technologies, mobile-assisted language learning.Abstract
The technologies also enable more personalized and engaging experiences for students with very little additional burden on the instructor. As students create language utterances and engage in activities with these technologies, valuable data is collected to reveal uncommon mistakes, matters that are genuinely hard for reasons other than non-comprehension, relevant skill trajectories to consider, reasons for disengagement, and measures of whether effort will be sufficient to reach the needed proficiency in time. It is also possible to demonstrate whether a failing student can perform well when the needed accommodation in pedagogical strategy is identified and implemented. In this chapter, we identify three major pillars to revolutionize language study through the use of smart technologies: 1) Individually adaptive learning systems that learn about the students, the content, and the semantics and pragmatics of student interaction; 2) Pedagogically smart virtual characters, also able to understand their students and possess appropriate personality and emotion; 3) Immersive virtual environments that increase the rate of experiences and simulate the situations where language is needed.
References
Makhmudov, K., 2020. Ways of forming intercultural communication in foreign language teaching. Science and Education. cyberleninka.ru
Lock, J., Lakhal, S., Cleveland‐Innes, M., Arancibia, P., Dell, D. and De Silva, N., 2021. Creating technology‐enabled lifelong learning: A heutagogical approach. British Journal of Educational Technology, 52(4), pp.1646-1662. [HTML]
Friedrichsen, A., 2020. Second language acquisition theories and what it means for teacher instruction. nwciowa.edu
Santana, L. H., 2023. Comparing Watson's Behaviorism and Meyer's Objectivism: Reassessing Traditional Assumptions in Psychology. psyarxiv.com
Muhajirah, M., 2020. Basic of learning theory:(behaviorism, cognitivism, constructivism, and humanism). International Journal of Asian Education. journal-asia.education
Khan, A.B. and Mansoor, H.S., 2020. Integrated Collaborative Learning Approach (ICLA): Conceptual framework of pedagogical approach for the integration of language skills. Competitive Social Science Research Journal, 1(1), pp.14-28. cssrjournal.com
Harris, R., Blundell-Birtill, P., Sutherland, E. and Pownall, M., 2021. Students' Perceptions of Online Lecture Delivery: An Empirical Mixed-Methods Investigation. Psychology Teaching Review, 27(1), pp.69-78. ed.gov
Kalsoom, T., Jabeen, S., Alshraah, S.M., Khasawneh, M.A.S. and Al-Awawdeh, N., 2024. Using Technological-based Models as Digital Tutors for Enhancing Reading and Writing Proficiency of Foreign Language Undergraduates. Kurdish Studies, 12(1). kurdishstudies.net
Huang, X., Zou, D., Cheng, G., Chen, X. and Xie, H., 2023. Trends, research issues and applications of artificial intelligence in language education. Educational Technology & Society, 26(1), pp.112-131. j-ets.net
Ahmed, A.A.A., Sayed, B.T., Wekke, I.S., Widodo, M., Rostikawati, D., Ali, M.H., Abdul Hussein, H.A. and Azizian, M., 2022. An Empirical Study on the Effects of Using Kahoot as a Game‐Based Learning Tool on EFL Learners’ Vocabulary Recall and Retention. Education Research International, 2022(1), p.9739147. wiley.com
Lin, V., Barrett, N.E., Liu, G.Z., Chen, N.S. and Jong, M.S.Y., 2023. Supporting dyadic learning of English for tourism purposes with scenery-based virtual reality. Computer Assisted Language Learning, 36(5-6), pp.906-942. [HTML]
Johnson, C., 2021. Language learners' perceptions of automatic speech recognition as a writing tool: A Technology Acceptance Model analysis. concordia.ca
