How we built it
The website was built through Python, Flask, HTML, CSS, and Javascript.
We implemented a database using Amazon S3, storing/uploading videos through a separate admin page and accessing them through Amazon Cloudfront, to ensure quick access to videos. We also used APIs called AssemblyAI and OpenAI, along with Natural Language Processing Toolkits to search through lectures, generate summaries and quizzes, and provide lecture references to answer questions.
The main process of programming used was Flask and Python to program the backend so that the website could perform tasks like creating the AI Assistant, Forums, Translating Transcript, and more. The main overall structure and design of the website were done through HTML and CSS, this was to create an overall appealing webpage for the users.
Inspiration
The project's inspiration is about how noninteractive and unengaging many of the Student LMS are used by the education system. We have incorporated digital tools to make an LMS that is more interactive and improve efficiency and effectiveness in learning
What it does
The LMS consists of several features to improve learning, for example, an interactive quiz that students can partake in while watching a lecture and questioning their knowledge. In addition, an AI called Dougless acts as an AI Assistant which helps reference lectures to answer students' questions. It provides an autogenerated summary, and titles and translates the language to help with accessibility and refine the organisation of lectures.
Challenges we ran into
Some challenges that we ran into were looking for APIs for our program and integrating both the front-end and back-end. There was a lot of debugging that we ran into to make the program functional and usable to the user.
Accomplishments that we're proud of
The overall accomplishment that we are proud of is the learning of programming languages and the use of libraries that are unfamiliar to us. We learned how to program in both JavaScript and Flask to achieve our solution. To complete this project was another accomplishment that we are proud of.
What we learned
As stated before, we learned JavaScript and Flask for our solution. However, we learned more than just programming languages. The use of market research and business models for our product made us reflect beyond the development of the solution. We had to learn to analyse and design our product and evaluate whether it was a feasible solution.
What's next for CatalystEd
There are a few features of the program that are still in development. The aim is to create a fully functional product within the coming weeks with little to no bugs. That is to create a better video player with features. The recording of data to track the most difficult topics to provide feedback to teachers. A translation feature that allows international students to understand the content more easily. Integrate a server-side application so that we can optimize the webpage loadings. We want to explore more features that students want and through that, we will improve and conduct better market research.
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