Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish
- Autores
- Parra, Verónica Ester; Sureda Figueroa, Diana Patricia; Corica, Ana Rosa; Schiaffino, Silvia Noemi; Godoy, Daniela Lis
- Año de publicación
- 2024
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Generative Artificial Intelligence (AI) has emerged as a disruptive technology that is challenging traditional teaching and learning practices. Question-answering in natural language fosters the use of chatbots, such as ChatGPT, Bard and others, that generate text based on pre-trained Large Language Models (LLMs). The performance of these models in certain areas, like Math problem solving is receiving a crescent attention as it directly impacts on its potential use in educational settings. Most of these evaluations, however, concentrate on the construction and use of benchmarks comprising diverse Math problems in English. In this work, we discuss the capabilities of most used LLMs within the subfield of Geometry, in view of the relevance of this subject in high-school curricula and the difficulties exhibited by even most advanced multimodal LLMs to deal with geometric notions. This work focuses on Spanish, which is additionally a less resourced language. The answers of three major chatbots, based on different LLMs, were analyzed not only to determine their capacity to provide correct solutions, but also to categorize the errors found in the reasoning processes described. Understanding LLMs strengths and weaknesses in a field like Geometry can be a first step towards the design of more informed methodological proposals to include these technologies in classrooms as well as the development of more powerful automatic assistance tools based on generative AI.
Fil: Parra, Verónica Ester. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: Sureda Figueroa, Diana Patricia. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: Corica, Ana Rosa. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina - Materia
-
GENERATIVE AI
GEOMETRY
LLMS
MATH - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/240281
Ver los metadatos del registro completo
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Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in SpanishParra, Verónica EsterSureda Figueroa, Diana PatriciaCorica, Ana RosaSchiaffino, Silvia NoemiGodoy, Daniela LisGENERATIVE AIGEOMETRYLLMSMATHhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Generative Artificial Intelligence (AI) has emerged as a disruptive technology that is challenging traditional teaching and learning practices. Question-answering in natural language fosters the use of chatbots, such as ChatGPT, Bard and others, that generate text based on pre-trained Large Language Models (LLMs). The performance of these models in certain areas, like Math problem solving is receiving a crescent attention as it directly impacts on its potential use in educational settings. Most of these evaluations, however, concentrate on the construction and use of benchmarks comprising diverse Math problems in English. In this work, we discuss the capabilities of most used LLMs within the subfield of Geometry, in view of the relevance of this subject in high-school curricula and the difficulties exhibited by even most advanced multimodal LLMs to deal with geometric notions. This work focuses on Spanish, which is additionally a less resourced language. The answers of three major chatbots, based on different LLMs, were analyzed not only to determine their capacity to provide correct solutions, but also to categorize the errors found in the reasoning processes described. Understanding LLMs strengths and weaknesses in a field like Geometry can be a first step towards the design of more informed methodological proposals to include these technologies in classrooms as well as the development of more powerful automatic assistance tools based on generative AI.Fil: Parra, Verónica Ester. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Sureda Figueroa, Diana Patricia. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Corica, Ana Rosa. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaUniversidad Internacional de La Rioja2024-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/240281Parra, Verónica Ester; Sureda Figueroa, Diana Patricia; Corica, Ana Rosa; Schiaffino, Silvia Noemi; Godoy, Daniela Lis; Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish; Universidad Internacional de La Rioja; International Journal of Interactive Multimedia and Artificial Intelligence; 8; 1; 2-2024; 65-741989-1660CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.ijimai.org/journal/bibcite/reference/3432info:eu-repo/semantics/altIdentifier/url/https://www.ijimai.org/journal/sites/default/files/2024-02/ijimai8_5_7.pdfinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:11:11Zoai:ri.conicet.gov.ar:11336/240281instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:11:12.201CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish |
| title |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish |
| spellingShingle |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish Parra, Verónica Ester GENERATIVE AI GEOMETRY LLMS MATH |
| title_short |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish |
| title_full |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish |
| title_fullStr |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish |
| title_full_unstemmed |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish |
| title_sort |
Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish |
| dc.creator.none.fl_str_mv |
Parra, Verónica Ester Sureda Figueroa, Diana Patricia Corica, Ana Rosa Schiaffino, Silvia Noemi Godoy, Daniela Lis |
| author |
Parra, Verónica Ester |
| author_facet |
Parra, Verónica Ester Sureda Figueroa, Diana Patricia Corica, Ana Rosa Schiaffino, Silvia Noemi Godoy, Daniela Lis |
| author_role |
author |
| author2 |
Sureda Figueroa, Diana Patricia Corica, Ana Rosa Schiaffino, Silvia Noemi Godoy, Daniela Lis |
| author2_role |
author author author author |
| dc.subject.none.fl_str_mv |
GENERATIVE AI GEOMETRY LLMS MATH |
| topic |
GENERATIVE AI GEOMETRY LLMS MATH |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
| dc.description.none.fl_txt_mv |
Generative Artificial Intelligence (AI) has emerged as a disruptive technology that is challenging traditional teaching and learning practices. Question-answering in natural language fosters the use of chatbots, such as ChatGPT, Bard and others, that generate text based on pre-trained Large Language Models (LLMs). The performance of these models in certain areas, like Math problem solving is receiving a crescent attention as it directly impacts on its potential use in educational settings. Most of these evaluations, however, concentrate on the construction and use of benchmarks comprising diverse Math problems in English. In this work, we discuss the capabilities of most used LLMs within the subfield of Geometry, in view of the relevance of this subject in high-school curricula and the difficulties exhibited by even most advanced multimodal LLMs to deal with geometric notions. This work focuses on Spanish, which is additionally a less resourced language. The answers of three major chatbots, based on different LLMs, were analyzed not only to determine their capacity to provide correct solutions, but also to categorize the errors found in the reasoning processes described. Understanding LLMs strengths and weaknesses in a field like Geometry can be a first step towards the design of more informed methodological proposals to include these technologies in classrooms as well as the development of more powerful automatic assistance tools based on generative AI. Fil: Parra, Verónica Ester. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina Fil: Sureda Figueroa, Diana Patricia. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina Fil: Corica, Ana Rosa. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina |
| description |
Generative Artificial Intelligence (AI) has emerged as a disruptive technology that is challenging traditional teaching and learning practices. Question-answering in natural language fosters the use of chatbots, such as ChatGPT, Bard and others, that generate text based on pre-trained Large Language Models (LLMs). The performance of these models in certain areas, like Math problem solving is receiving a crescent attention as it directly impacts on its potential use in educational settings. Most of these evaluations, however, concentrate on the construction and use of benchmarks comprising diverse Math problems in English. In this work, we discuss the capabilities of most used LLMs within the subfield of Geometry, in view of the relevance of this subject in high-school curricula and the difficulties exhibited by even most advanced multimodal LLMs to deal with geometric notions. This work focuses on Spanish, which is additionally a less resourced language. The answers of three major chatbots, based on different LLMs, were analyzed not only to determine their capacity to provide correct solutions, but also to categorize the errors found in the reasoning processes described. Understanding LLMs strengths and weaknesses in a field like Geometry can be a first step towards the design of more informed methodological proposals to include these technologies in classrooms as well as the development of more powerful automatic assistance tools based on generative AI. |
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2024 |
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2024-02 |
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http://hdl.handle.net/11336/240281 Parra, Verónica Ester; Sureda Figueroa, Diana Patricia; Corica, Ana Rosa; Schiaffino, Silvia Noemi; Godoy, Daniela Lis; Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish; Universidad Internacional de La Rioja; International Journal of Interactive Multimedia and Artificial Intelligence; 8; 1; 2-2024; 65-74 1989-1660 CONICET Digital CONICET |
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Parra, Verónica Ester; Sureda Figueroa, Diana Patricia; Corica, Ana Rosa; Schiaffino, Silvia Noemi; Godoy, Daniela Lis; Can generative AI solve Geometry problems? Strengths and weaknesses of LLMs for geometric reasoning in Spanish; Universidad Internacional de La Rioja; International Journal of Interactive Multimedia and Artificial Intelligence; 8; 1; 2-2024; 65-74 1989-1660 CONICET Digital CONICET |
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eng |
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