AI in qualitative research: Using large language models to code survey responses in native languages

Food systems research - and more generally, policy and development research -often relies on structured surveys, administrative data, or experiments. While these approaches yield valuable quantitative insights, they tend to miss critical qualitative dimensions. One useful qualitative approach is ope...

Full description

Bibliographic Details
Main Authors: Singh, Tushar, Kumar, Himangshu
Format: Blog Post
Language:Inglés
Published: International Food Policy Research Institute 2025
Subjects:
Online Access:https://hdl.handle.net/10568/178199
_version_ 1855540473474580480
author Singh, Tushar
Kumar, Himangshu
author_browse Kumar, Himangshu
Singh, Tushar
author_facet Singh, Tushar
Kumar, Himangshu
author_sort Singh, Tushar
collection Repository of Agricultural Research Outputs (CGSpace)
description Food systems research - and more generally, policy and development research -often relies on structured surveys, administrative data, or experiments. While these approaches yield valuable quantitative insights, they tend to miss critical qualitative dimensions. One useful qualitative approach is open-ended interview questions. When such responses are collected in participants' native languages, they can provide rich and nuanced information-for example, on the complex local challenges smallholder farmers face.
format Blog Post
id CGSpace178199
institution CGIAR Consortium
language Inglés
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher International Food Policy Research Institute
publisherStr International Food Policy Research Institute
record_format dspace
spelling CGSpace1781992025-11-25T20:10:16Z AI in qualitative research: Using large language models to code survey responses in native languages Singh, Tushar Kumar, Himangshu digital technology artificial intelligence large language models languages Food systems research - and more generally, policy and development research -often relies on structured surveys, administrative data, or experiments. While these approaches yield valuable quantitative insights, they tend to miss critical qualitative dimensions. One useful qualitative approach is open-ended interview questions. When such responses are collected in participants' native languages, they can provide rich and nuanced information-for example, on the complex local challenges smallholder farmers face. 2025-07-10 2025-11-25T19:51:16Z 2025-11-25T19:51:16Z Blog Post https://hdl.handle.net/10568/178199 en Open Access International Food Policy Research Institute Singh, Tushar; and Kumar, Himangshu. 2025. AI in qualitative research: Using large language models to code survey responses in native languages. IFPRI Blog Post. https://www.ifpri.org/blog/ai-in-qualitative-research-using-large-language-models-to-code-survey-responses-in-native-languages/
spellingShingle digital technology
artificial intelligence
large language models
languages
Singh, Tushar
Kumar, Himangshu
AI in qualitative research: Using large language models to code survey responses in native languages
title AI in qualitative research: Using large language models to code survey responses in native languages
title_full AI in qualitative research: Using large language models to code survey responses in native languages
title_fullStr AI in qualitative research: Using large language models to code survey responses in native languages
title_full_unstemmed AI in qualitative research: Using large language models to code survey responses in native languages
title_short AI in qualitative research: Using large language models to code survey responses in native languages
title_sort ai in qualitative research using large language models to code survey responses in native languages
topic digital technology
artificial intelligence
large language models
languages
url https://hdl.handle.net/10568/178199
work_keys_str_mv AT singhtushar aiinqualitativeresearchusinglargelanguagemodelstocodesurveyresponsesinnativelanguages
AT kumarhimangshu aiinqualitativeresearchusinglargelanguagemodelstocodesurveyresponsesinnativelanguages