Inspiration: The inspiration for my project stems from a freelance job post I encountered, which involved editing HKDSE Economics Exam questions. This experience highlighted the significant amount of time and effort educators spend on creating and refining multiple-choice questions (MCQs) for exam and practice materials. Recognizing the potential of generative AI, I envisioned a solution that could automate the process, thereby allowing teachers to focus more on teaching and less on administrative tasks. Moreover, such tool could provide students with readily available, low-cost practice questions, enhancing their learning experience.
What it does: The project aims to develop an AI-powered MCQ generator that can create high-quality multiple-choice questions. The generator will cater to various subjects and difficulty levels, making it a versatile tool for both educators and students.
How we built it: The generator is built using a combination of Python and Azure OpenAI API to leverage advanced natural language processing capabilities for generating high quality multiple-choice questions. Additionally, a simple user interface is implemented to allow users to interact with the system.
Challenges we ran into: Firstly, we need to ensure that the generated questions are accurate, relevant and free of bias. Secondly, it is important to create an intuitive interface that meets the needs of both teachers and students
Accomplishments that we're proud of: The MCQ generator simplifies the process of question creation and contributes to the boarder goal of improving educational outcomes through innovative technology.
What we learned: This project offers multiple learning opportunities. I work with advanced NLP models and learn their capabilities and limitations. It also enhances my skill in designing user interfaces that are both functional and user friendly. Finally, I learn about testing and validation to ensure high-quality output.
What's next for DSE Economics MCQs generator: The generator has great potential to integrate with existing learning management systems for seamless adoption in education institutions. Also, user feedback can be collected to continuously enhance the accuracy and relevance of generated questions.
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