Potential of Large Language Models (LLMs) as Supplementary Tools for Historical Learning: Users’ Interaction and Knowledge Acquisition

  • Muhammad Hasnain Lahore Leads University, Lahore, Pakistan
  • Sardar Usman Grand Asian University, Sialkot, Pakistan
Keywords: Large Language Models, Historical Figure, Prompt Engineering, Performance


This study explores the strengths and limits of large language models (LLMs) in exploring the information on history, an area unexplored in the existing literature. ChatGPT and Gemini, as LLMs, have demonstrated superior performance in education, healthcare, and business. This study proposes utilizing the ChatGPT (ver. 3.5) and Gemini applications to acquire information on historical figures like Sher Shah Suri and Mughal Emperors and Sikhs in the subcontinent. To evaluate the proposed study, this study used two data sets: the first data set comprised a set of questions (n = 26) and the second data set contained questions (n = 35). The results indicate that ChatGPT provides concise answers to the questions of both datasets compared to the Gemini application. However, Gemini exhibited a higher accuracy (92.30%) than ChatGPT with accuracy (76.92%) for dataset 1. For the dataset 2, ChatGPT showed better accuracy (68.57%) than Gemini with accuracy (65.71%). Further research could expand on this study by employing additional artificial intelligence (AI) tools on large-scale datasets from diverse domains.