Don’t Lose Your Voice! Strategies for Using LLMs to Improve Student Writing
Alternative Title
Don’t Lose Your Voice! Strategies for Using Large Language Models (LLMs) to Improve Student Writing
Contributor
University of Central Florida. Faculty Center for Teaching and Learning; University of Central Florida. Division of Digital Learning; Teaching and Learning with AI Conference (2023 : Orlando, Fla.)
Location
Seminole A
Start Date
23-7-2024 11:30 AM
End Date
23-7-2024 12:00 PM
Publisher
University of Central Florida Libraries
Keywords:
Large language models; Student writing; Voice preservation; Feedback strategies; Language translation
Subjects
English language--Rhetoric--Study and teaching--Technological innovations; Voice in education; Academic writing--Computer-assisted instruction; English language--Writing--Study and teaching; English language--Study and teaching--Technological innovations
Description
Having the capability to support students in improving their writing is a significant value proposition of large language models (LLMs). However, that support should not put students at risk of losing their voice to the LLM in their own writing. In response, this session’s presenters will share strategies for leveraging LLMs to support student writing that specifically focus on language translation, feedback, and class norms. The session will include examples and strategies that instructors can implement in their next class!
Language
eng
Type
Event
Rights Statement
This work is licensed under a Creative Commons Attribution 4.0 International License.
Audience
Faculty, Students, Educators
Recommended Citation
Cherner, Todd and Riger, Dana, "Don’t Lose Your Voice! Strategies for Using LLMs to Improve Student Writing" (2024). Teaching and Learning with AI Conference Presentations. 42.
https://stars.library.ucf.edu/teachwithai/2024/tuesday/42
Don’t Lose Your Voice! Strategies for Using LLMs to Improve Student Writing
Seminole A
Having the capability to support students in improving their writing is a significant value proposition of large language models (LLMs). However, that support should not put students at risk of losing their voice to the LLM in their own writing. In response, this session’s presenters will share strategies for leveraging LLMs to support student writing that specifically focus on language translation, feedback, and class norms. The session will include examples and strategies that instructors can implement in their next class!
