Inspiration

Education is a key pilar on the development of society. Thanks to the advance of technology on the last decades, it is now easier to reach more sectors of the population and share the knowledge around the world. Nevertheless, teaching itself can still take a lot of advantage of the current communication systems to achieve its full potencial.

With this aim, SlideBack wants to provide a better interaction between teachers and students making the process of learning and teaching easier and more interactive.

What it does

SlideBack provides a platform for teachers and students to interact in both senses.

On one hand, teachers can get feedback from the students' reactions thanks to a system of image recognition that analyses audience expressions to get their level of attention and understanding. In this way teachers will be able to detect when a concept has not been understood and make more emphasis on its explanation.

On the other hand, students are provided with a live system of translation what decreases the effect of linguistic barriers in the process of knowledge sharing. Finally, all the participants can interact through to a live feed to provide feedback or ask questions.

How we built it

The system is developed in JavaScript and React. The image analysis for emotion extraction is performed through an Azure API as well as the text translation. Finally, all the users are connected through a web socket connection.

Challenges we ran into

Getting images to a cloud bucket to analyse them.

Accomplishments that we're proud of

Deploying services to the cloud. Working with image recognition.

What's next for SlideBack

SlideBack has a great potential of growth in several directions. New functionalities can be integrated such as:

  • generation of graphics using color palettes adapted for colour-blind people.
  • text to speech support for individuals with low vision or blindness.
  • improvement of the translation system and increase in the number of supported languages.

Moreover, improvement of the image analysis system can be done to obtained more accurate and personalised metrics on the attention and comprehension of the students.

Share this project:

Updates