Leveraging LLM Tutoring Systems for Non-Native English Speakers in Introductory CS Courses

Fuente: arXiv
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Autori principali: Molina, Ismael Villegas, Montalvo, Audria, Ochoa, Benjamin, Denny, Paul, Porter, Leo
Natura: Preprint
Pubblicazione: 2024
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author Molina, Ismael Villegas
Montalvo, Audria
Ochoa, Benjamin
Denny, Paul
Porter, Leo
author_facet Molina, Ismael Villegas
Montalvo, Audria
Ochoa, Benjamin
Denny, Paul
Porter, Leo
contents Computer science has historically presented barriers for non-native English speaking (NNES) students, often due to language and terminology challenges. With the rise of large language models (LLMs), there is potential to leverage this technology to support NNES students more effectively. Recent implementations of LLMs as tutors in classrooms have shown promising results. In this study, we deployed an LLM tutor in an accelerated introductory computing course to evaluate its effectiveness specifically for NNES students. Key insights for LLM tutor use are as follows: NNES students signed up for the LLM tutor at a similar rate to native English speakers (NES); NNES students used the system at a lower rate than NES students -- to a small effect; NNES students asked significantly more questions in languages other than English compared to NES students, with many of the questions being multilingual by incorporating English programming keywords. Results for views of the LLM tutor are as follows: both NNES and NES students appreciated the LLM tutor for its accessibility, conversational style, and the guardrails put in place to guide users to answers rather than directly providing solutions; NNES students highlighted its approachability as they did not need to communicate in perfect English; NNES students rated help-seeking preferences of online resources higher than NES students; Many NNES students were unfamiliar with computing terminology in their native languages. These results suggest that LLM tutors can be a valuable resource for NNES students in computing, providing tailored support that enhances their learning experience and overcomes language barriers.
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id arxiv_https___arxiv_org_abs_2411_02725
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Leveraging LLM Tutoring Systems for Non-Native English Speakers in Introductory CS Courses
Molina, Ismael Villegas
Montalvo, Audria
Ochoa, Benjamin
Denny, Paul
Porter, Leo
Human-Computer Interaction
Computer science has historically presented barriers for non-native English speaking (NNES) students, often due to language and terminology challenges. With the rise of large language models (LLMs), there is potential to leverage this technology to support NNES students more effectively. Recent implementations of LLMs as tutors in classrooms have shown promising results. In this study, we deployed an LLM tutor in an accelerated introductory computing course to evaluate its effectiveness specifically for NNES students. Key insights for LLM tutor use are as follows: NNES students signed up for the LLM tutor at a similar rate to native English speakers (NES); NNES students used the system at a lower rate than NES students -- to a small effect; NNES students asked significantly more questions in languages other than English compared to NES students, with many of the questions being multilingual by incorporating English programming keywords. Results for views of the LLM tutor are as follows: both NNES and NES students appreciated the LLM tutor for its accessibility, conversational style, and the guardrails put in place to guide users to answers rather than directly providing solutions; NNES students highlighted its approachability as they did not need to communicate in perfect English; NNES students rated help-seeking preferences of online resources higher than NES students; Many NNES students were unfamiliar with computing terminology in their native languages. These results suggest that LLM tutors can be a valuable resource for NNES students in computing, providing tailored support that enhances their learning experience and overcomes language barriers.
title Leveraging LLM Tutoring Systems for Non-Native English Speakers in Introductory CS Courses
topic Human-Computer Interaction
url https://arxiv.org/abs/2411.02725