Automated Generation and Evaluation of MultipleChoice Quizzes using Langchain and Gemini LLM

Abstract

The research study investigates the use of cutting-edge technologies like Langchain and Gemini AI for the automated creation and assessment of multiple-choice questions (MCQs). Although producing multiple-choice questions (MCQs) has traditionally been done by hand and required a lot of work, advances in artificial intelligence (AI) and natural language processing (NLP) have opened up new possibilities. The creation and implementation of an MCQ generator—which uses Gemini AI to generate MCQs and Langchain for rapid engineering are covered in this paper. Customizing prompts for prompt engineering, chaining prompts with the Gemini AI model, and utilizing OpenAI's GPT-3.5 and multiple Language Learning Models (LLMs) to assess the created MCQs are the steps in the process. The study intends to assess these models' efficiency in handling intricate queries, producing appropriate answers, and examining the caliber of the MCQs that are produced.