Large language models (ChaptGPT etc.)

Let's agree on something: they are impressive!

Large Language Models (LLMs) like ChatGPT have revolutionized the landscape of digital learning and teaching, becoming increasingly popular among educators and students alike. These advanced AI models, trained on vast amounts of text data, excel in understanding and generating human-like text, making them a valuable tool in education. Their ability to provide instant, articulate, and often insightful responses to a wide range of queries has made them particularly appealing in academic settings.

For teachers, LLMs offer a unique resource for curriculum development, providing access to a broad spectrum of information and ideas that can stimulate educational content creation. They can assist in generating creative teaching materials, suggest alternative approaches to explaining complex concepts, and offer insights into diverse subject matters. Students, on the other hand, find these models beneficial for homework assistance, research, and enhancing their understanding of various topics through interactive and engaging dialogues.

However..

Despite their versatility, LLMs like ChatGPT exhibit notable deficiencies, especially when it comes to solving mathematics homework and designing math teaching materials. One primary limitation is their inherent design, which focuses on language processing, not numerical computation or mathematical reasoning. This means they might struggle with interpreting and solving complex mathematical problems accurately. They lack the ability to perform symbolic manipulation and advanced mathematical computations that are essential in higher-level mathematics.

These are several examples of incorrect responses we obtained from ChatGPT 4.0.

Furthermore, their responses can sometimes be over-generalized or based on patterns seen in the training data, which may not always align with the precise, step-by-step logical reasoning required in mathematics. This can lead to incorrect or incomplete solutions, potentially misleading students. Additionally, while they can generate explanatory content, they cannot inherently understand mathematical concepts, making the creation of mathematically rich and pedagogically sound teaching materials challenging.

In conclusion, while LLMs like ChatGPT have become invaluable tools in modern education, their application in mathematics education, particularly in solving homework and designing teaching materials, is limited by their language-centric design and lack of advanced mathematical capabilities.

Note: This text was adapted from an article that was generated by ChatGPT 4.0. Here is a link to the prompt and the original ChatGPT response.