Can Generative AI Solve Geometry Problems? Strengths and Weaknesses of LLMs for Geometric Reasoning in Spanish

• Verónica Parra ^[1] ; Patricia Sureda ^[1] ; Ana Corica ^[1] ; Silvia Schiaffino ^[1] ; Daniela Godoy ^[1]
  1. [1] Universidad Nacional del Centro de la Provincia de Buenos Aires; CONICET
• Localización: IJIMAI, ISSN-e 1989-1660, Vol. 8, Nº. 5, 2024, págs. 65-74
• Idioma: inglés
• DOI: 10.9781/ijimai.2024.02.009
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• Dialnet Métricas: 6 Citas
• Resumen

  • 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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