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Study Material Discovery and Summarization Tool for Students

Added Jun 2025 3 design docs

Students beginning a paper or exam preparation face the same first hurdle: finding material worth reading and understanding it quickly. Search engines return too much, academic language slows comprehension, and hours evaporate before any actual learning happens. A tool that helps a student locate relevant material and immediately produces study-friendly summaries shortens the distance between assignment and understanding.

The intern builds this tool as a Streamlit application in Python. The interface lets a student enter a topic or paste in source text, and the backend uses OpenAI models to do the heavy lifting: suggesting the kinds of sources and search directions worth pursuing, summarizing pasted articles into clear key points, and reformulating dense academic passages into plain language. The intern implements features that make the tool genuinely study-oriented, including adjustable summary length, automatic extraction of key terms with definitions, and a session view where a student can collect summaries from multiple sources into one revision sheet.

As an accessible early project, it teaches the intern how to build a responsive Streamlit interface, design prompts that reliably produce educational output, and manage multi-step interactions with a language model API, while producing an application their fellow students would genuinely use during exam season.

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