Rethinking learning in the Artificial Intelligence era: incorporating an LLM in elementary school
Year: 2023
Type: dissertation
Abstract: With the evolution of conversational Large Language Models (LLMs), such as ChatGPT, and the availability of an Application Programming Interface (API) to access this technology, there emerged a need for greater control over the functioning of this tool. Prompt engineering, a field of study focused on enhancing methods and techniques to better control the responses of these models, played a crucial role in this context. This approach involves the inclusion of additional information in the user’s initial call, such as rules and roles that the model should assume, as well as details about the user’s profile. In this work, the GPT 3.5 model was employed in the creation of a web application aimed at educating children in the third grade of elementary school, aged between 8 and 9 years. The project focused on developing a controlled prompt pattern that assumes the role of a teacher, accompanied by a set of rules to model the interaction with the LLM. This allowed the children to ask the tool questions on specific topics. The responses were tailored to the children’s inquiries, and the effectiveness of the application was evaluated by experts in the field. The conclusion of this process demonstrated the viability and efficiency of prompt engineering in personalizing the educational experience for the child audience, however, many aspects still can be improved in the future.
Author: Ribeiro, Thyago de Azevedo
Language: Portuguese
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7155462817