Although tools such as textbooks and personal readings may be used to augment our learning, the vast majority of information that forms our foundational understanding comes from lectures. Given the great weighting placed on the value of information retention during lectures, we determined the importance of innovating the way that information is presented in lectures to students. We approached this problem via addressing the question of how we may present reliable, unbiased and live feedback to professors during lectures and redesign the learning experience. We believe that lectur does just that.
What it does
Our interface is a web server that displays live student feedback and attentivity to educators and lecturers with minimal graphing and imaging tools. Beyond providing professors with real-time metrics on student engagement, lectur services educators in a way that is accessible and easy to implement in a learning environment.
How we built it
We have a Node back-end, HTML front-end and Amazon s3 buckets for storage. AWS was utilized for the AI aspect of facial recognition and analysis.
Challenges we ran into
We utilized a variety of new and unfamiliar technologies and faced a learning curve during the initial setup and testing phases.
Accomplishments that we're proud of
We are delighted at how well we came together and maximized each of our strengths in bringing our vision to fruition.
What we learned
- Use AWS and connect it to s3 buckets
- Connect front-end interfaces with back-end servers
- Make API calls
- Design webpages with Bootstrap
What's next for lectur
We believe that lectur has a bright future in classrooms and how education is received by students. Lectur has a potential to reform student attentivity and learning, but we believe that it does not stop here. Beyond the limited time slot and scope of DeltaHacks, our next steps include designing a system that is able to seamlessly integrate built in cameras around a classroom so that students who rely on handwritten notes may benefit from this model. We also recognize legality and privacy right implications that arise with the implementation of this system in classroom settings. To overcome these challenges, we propose this model be used with consensual participants in order to better curate and tailor lecture content for classrooms not participating in this augmented learning tool.