Evaluating Semantic Search vs. Keyword Search for Educational Video Retrieval in Technical Subjects
Project by Polygence alum Aiden
Project's result
This project resulted in a completed research paper, presentation, and comparative evaluation of semantic search and keyword search for educational video retrieval. Through designing and testing both systems, I found that semantic search was significantly more effective at understanding the intent behind natural language and conceptual questions, helping learners find information even when they did not know the exact technical terminology. Beyond the technical findings, this project reinforced the idea that technology can play a meaningful role in reducing barriers to learning. It allowed me to combine my interests in artificial intelligence and education while exploring how AI can create more accessible, intuitive, and student-centered learning experiences.
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Summary
Computer engineering students often struggle to find clear, structured, and relevant video content that precisely addresses the topics they're learning — such as Verilog, cache design, or pipelining. Mainstream platforms like YouTube are cluttered, lack technical depth filtering, and offer minimal support for semantic search or automatic topic indexing. As a result, students spend valuable time hunting for content instead of absorbing knowledge. The goal of this project is to design and develop a smart video hosting platform tailored specifically for the computer engineering domain. This web-based system will allow educators and students to upload, access, and explore educational videos with built-in AI features.
Jay Ryan
Polygence mentor
Industry expert
Subjects
Computer Science
Expertise
web development, app development, software engineering, programming, cybersecurity
Aiden
Student
Graduation Year
2026
Project review
“My experience with this project was incredibly rewarding. It gave me the opportunity to explore the intersection of artificial intelligence and education while investigating a problem that I had personally observed through teaching students. Throughout the project, I not only learned about semantic search, natural language processing, and information retrieval, but also gained valuable experience conducting independent research, analyzing data, and communicating technical ideas in a meaningful way. One of the most fulfilling aspects of the project was realizing how technology can be used to reduce barriers to learning and make educational resources more accessible to students. Overall, this experience strengthened my interest in AI and reinforced my passion for building technologies that have a positive impact on education and the lives of others.”
About my mentor
“Working with my Polygence mentor during my research project was an incredibly valuable experience. They guided me through the process of developing my research question, organizing my ideas, and strengthening my writing and analysis. What stood out most was their ability to challenge my thinking while also being very supportive and encouraging. Through our meetings, I learned not only more about my topic but also how to approach research more critically and independently. Overall, the mentorship made the entire research process much more meaningful and helped me produce a stronger final paper.”
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