Developing a Language Teacher Assistant Tool with GenAI
Editors Note. This is a blog written by interns from NTU who joined DeepDive Labs as part of the veNTUre program. Read on for their hackathon experience with DeepDive Labs. Background
During a two-day hackathon, our team worked on enhancing a teacher assistant tool that leverages Generative AI (GenAI) to assist language teachers in creating personalized lesson plans. Our goal was to implement practical solutions that could support teachers in their daily tasks by making lesson plan creation more efficient.
By the end of the hackathon, we aimed to achieve two primary objectives:
Our team comprised of Juneyoung Seo: Front-End Development, Pamela Lee: Back-End Development, Daeun Kang: Prompt Engineering and Molly: Business Strategy.
User Authentication and Access: Enable users to log in with their Google ID and access a list of their previously created lesson plans. This feature allows teachers to manage and review their work from any device.
Lesson Plan Creation: Allow logged-in users to create a new lesson plan, specifically in French, streamlining the process of crafting targeted language exercises.
Front-End Development (Juneyoung)
As the front-end developer, my focus was on designing and implementing a user-friendly interface that allows teachers to navigate the platform with ease. I integrated third-party authentication, specifically Google login, ensuring that users could securely access their lesson plans.
Using ReactJS and NextJS, I implemented features that allow seamless interaction between the front end and the back end. This included managing user data storage and retrieval, and displaying AI-generated prompts to enhance the lesson plan creation process.
One of the main challenges was ensuring consistency between the front-end and back-end code, particularly when integrating the login functionality. Managing state and variables effectively was another critical aspect of the development process.
Overall, this experience provided valuable insights into front-end development for SaaS platforms and reinforced the importance of teamwork in building a functional application.
Back-End Development (Pamela)
As the back-end developer, I was responsible for implementing the logic, managing the database, and integrating APIs that supported our application. Utilizing AWS services, I worked on making the application scalable and reliable.
I employed AWS Lambda to handle core functionalities like lesson creation and user authentication. Additionally, I set up DynamoDB to store user data and lesson plans, and used API Gateway to manage communication between the front-end and back-end systems.
This project deepened my understanding of serverless architecture, the benefits of NoSQL databases, and the principles of API design. Challenges included ensuring smooth integration with GenAI outputs and maintaining consistent communication with the front-end developer to align our efforts.
Overall, working on the back-end was a rewarding experience that enhanced both my technical skills and my ability to collaborate effectively within a team.
Prompt Engineering (Daeun)
My role as the prompt engineer involved crafting precise AI prompts and integrating them with AWS services. This was my first experience using AWS, and I learned how to coordinate backend processes using S3 and Lambda functions.
One of the key challenges was ensuring that the AI-generated prompts were correctly formatted and integrated smoothly with the back-end processes. Although the AWS Lambda environment posed some difficulties, these challenges provided valuable learning experiences.
This project highlighted the importance of teamwork, especially during the fast-paced environment of a hackathon, and it significantly broadened my technical skills in prompt engineering and backend coordination.
Business Strategy (Molly)
At the conclusion of the hackathon, we presented our project along with a pitch titled "Innovative Teaching with GenAI," focusing on the potential applications of generative AI in education. Our presentation covered:
Introduction to GenAI: An overview of generative AI and its capabilities.
Educational Applications: Exploring how GenAI can personalize learning, automate grading, and create engaging educational content.
Case Studies: Examples of institutions successfully integrating GenAI into their curricula.
Ethical Considerations: Discussing the ethical implications of using AI in education, emphasizing fairness and responsibility.
Future Directions: Speculating on the evolving role of educators in a tech-enhanced environment.
This experience provided me with a deeper understanding of GenAI's potential in education and underscored the importance of ethical considerations when implementing advanced technologies.
Conclusion
The hackathon was a valuable learning experience that emphasized the importance of collaboration and communication in developing practical solutions. Over two days, our team combined technical and strategic skills to create a tool that we believe can support language teachers in their work. This project reinforced our collective commitment to continuous learning and innovation in the educational technology space.