Assessing Artificial Intelligence’s Capability to Support Various Intelligence-Based Language Learning Environments

DOI

10.2991/978-94-6463-787-8_35How to use a DOI?

Keywords

Artificial Intelligence (AI); Multiple Intelligences; Language Learning; Personalized Learning; Natural Language Processing; Adaptive Learning Systems; Interactive Simulations; Educational Technology; Learning Styles; Cognitive Strengths; Educational Accessibility

Abstract

Based on Howard Gardner’s hypothesis of multiple intelligences, this study investigates how well artificial intelligence (AI) can support language learning settings. In order to improve the customization and flexibility of language instruction, the study investigates how AI technologies may be used to accommodate a variety of cognitive strengths, including linguistic, logical-mathematical, spatial, and interpersonal intelligences. The capacity of important AI tools and technologies, such as interactive simulations, adaptive learning platforms, and natural language processing systems, to accommodate different learning styles and intelligences is assessed. The study also discusses issues and constraints that might affect AI’s efficacy in learning environments, including data biases, technology accessibility, and the requirement for human-like interactions.To evaluate the impact of AI, the study process include establishing assessment criteria, creating research frameworks, and examining both quantitative and qualitative data. The results imply that although AI has great potential for efficient and customized language acquisition, resolving these issues is essential to realizing its full potential. Future studies should concentrate on enhancing accessibility, developing AI technologies, and making sure that resources are useful and inclusive for all students. The study comes to the conclusion that using AI to improve language learning outcomes and satisfy the various demands of learners requires a careful and inclusive approach.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Rupali Babaso Dhansare
AU  - Priyanka Vijay Patil
AU  - Asavari Ajit Patil
PY  - 2025
DA  - 2025/07/17
TI  - Assessing Artificial Intelligence’s Capability to Support Various Intelligence-Based Language Learning Environments
BT  - Proceedings of the Recent Advances in Artificial Intelligence for Sustainable Development (RAISD 2025)
PB  - Atlantis Press
SP  - 452
EP  - 462
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-787-8_35
DO  - 10.2991/978-94-6463-787-8_35
ID  - Dhansare2025
ER  -