An exploration of how artificial intelligence enhances language learning, focusing on natural language processing, its impact on linguistic analysis, and the sociocultural and ethical implications of AI-mediated language learning.
Additional Requirements for Graduate Students: Graduate students will have separate research projects (based on theoretical or empirical work) related to AI and language education.
Athena Title
AI and Language Learning
Equivalent Courses
Not open to students with credit in LLED 5074E or LLED 7074E
Prerequisite
Permission of department
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Student learning Outcomes
Students will be able to explain the principles behind AI language models, including how these models are constructed, trained, and applied in the context of language learning.
Students will critically assess existing AI-based tools and platforms for language learning, identifying strengths, limitations, and potential impacts on language acquisition and pedagogy.
Students will be able to identify opportunities for enhancing language learning through AI, as well as potential challenges and ethical considerations in their implementation.
Students will critique the role of artificial intelligence in language acquisition, examining its implications for linguistic diversity, cultural sensitivity, and educational equity.
Students will propose innovative applications of AI language models to support language learning, grounded in theoretical knowledge and understanding of current technological capabilities and limitations.
Topical Outline
A. Introduction to AI and Language Learning
B. AI Language Models and Their Applications
C. Critical Evaluation of AI in Language Learning
D. Cultural and Linguistic Implications of AI Language Models
