REFLEX Learning

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  Our chatbot screen

Inspiration

Across Klein ISD, students often struggle to find immediate answers to academic questions and lack engaging study resources There is a gap in the utilization of technology that could be gapped to help students learn.

What it does

We are introducing a chatbot that answers questions, breaks down topics, and generates quizzes can bridge this gap, providing instant support and enhancing learning experiences.

How we built it

We trained an AI language model on AP and Class Data to respond to learner's questions but also use context in general situations to help learners. We used an online software to integrate our frontend and backend using Python. We use natural language processing techniques to make our language sound fluent and our morality of our chatbot well defined and principled.

Challenges we ran into

We struggled to integrate our frontend and backend initially, but by researching online models we were able to get the job done.

Accomplishments that we're proud of

We are proud that we are able to successfully develop an AI chatbot successfully within 24 hours to help KISD students learn.

What we learned

We learned the importance of working with a group and efficient time management and organization. We learned how to integrate the frontend and backend in an efficient manner.

What's next for REFLEX Learning

We plan to involve more tools to assist with adaptive learning and to cater to more students and areas of learning. We also plan to integrate the chatbot with existing LMS (Learning Management Systems) platforms used by educational institutions to seamlessly complement classroom instruction and track student progress.

Built With

• css3
• html5
• mongodb
• python
• react
• reflex