Leveraging Generative AI to Address Bloom's Two Sigma Problem: A Multilingual and Inclusive Approach
Location
Gold Coast III-IV
Start Date
23-7-2024 10:15 AM
End Date
23-7-2024 10:45 AM
Description
This presentation explores using generative AI to tackle Bloom's Two Sigma Problem, emphasizing enhanced individual learning through personalized, contextually relevant instruction. Discussing the gap between one-on-one tutoring and conventional teaching, we examine how generative AI provides high-quality, personalized tutoring, especially in multilingual contexts, promoting exclusive learning. We explore augmenting your teaching practice with AI to boost student engagement, learning outcomes, and personal mastery, offering practical insights for higher education teaching enhancements. This approach suggests a promising avenue for effectively addressing educational disparities and achieving including learning environments.
Recommended Citation
Fichman, Jonathan, "Leveraging Generative AI to Address Bloom's Two Sigma Problem: A Multilingual and Inclusive Approach" (2024). Teaching and Learning with AI Conference Presentations. 33.
https://stars.library.ucf.edu/teachwithai/2024/tuesday/33
Leveraging Generative AI to Address Bloom's Two Sigma Problem: A Multilingual and Inclusive Approach
Gold Coast III-IV
This presentation explores using generative AI to tackle Bloom's Two Sigma Problem, emphasizing enhanced individual learning through personalized, contextually relevant instruction. Discussing the gap between one-on-one tutoring and conventional teaching, we examine how generative AI provides high-quality, personalized tutoring, especially in multilingual contexts, promoting exclusive learning. We explore augmenting your teaching practice with AI to boost student engagement, learning outcomes, and personal mastery, offering practical insights for higher education teaching enhancements. This approach suggests a promising avenue for effectively addressing educational disparities and achieving including learning environments.