TeacherAssist is a tool to track the students attentiveness and effectiveness.
- Short Description
- Demo Video
- The Architecture
- Long Description
- Project Roadmap
- Getting Started
- Execution
- Live Demo
- Built with
- Contributing
Amplifying Learning by empowering the teachers to deliver better content
Covid-19 pandemic caused the education to move online. Teachers and students are facing a lot of challenges. In a class of roughly 30-40 students monitoring each one using media devices is not easy. One of the major challenges we identified is that the attention span of the students is on a decline, which in turn reduces their effectiveness. Teacher is no control.
To address this issue, we moved back to the physical classrooms, where the same problem does exist. When a teacher feels a student is not paying attention, she would buzz the student by asking a question! This is what TeacherAssist does.
TeacherAssist prompts questions to students at regular intervals. These intervals correspond to their attention span. The max duration is 15minutes which is less than the TED benchmark. These questions are pre-loaded by the teacher relevant to the given topic. Based on the response, we capture the student’s attentiveness and effectiveness.
Attentiveness is the time taken by the student to respond to a question. Effectiveness is the accuracy of the response.
User (Teacher)
- The user logs in to the web application
- Updates question for the topic
- Host meeting for a subject
- Provided with a mini dashboard to track real-time the class attendance, student attentiveness and effectiveness
User (Student)
- The user logs in to the web application
- Join meeting based on the meeting id
- Prompted for questions at attention span intervals
-
Tutor Mode for Student - Based on the insights from the data, the teacher can recommend a tutor to the student. The tutor will be build utilizing the capabilities of IBM Watson Assistant. The tutor will interact with the students to answer the queries and check the understanding level of each student.
-
Real-Time Questions based on topic - Make use of the capabilities of IBM Speech to Text and Named-Entity Recognition (NER). During an on-going class, perform a prompt question to the student based her speech to text. This could be a simple fill in the blank.
-
Assessment Tool - Map the data collected from the regular class and introduce an ongoing assessment process to track the performance.
-
Recap - Play a quick recap of the previous session at the start of new session for a teacher. During the on-going session the highlights will be recorded and quick recap will be created.
-
Role-based view - Develop role-based views for Parents, School Administration, School Management, Vendors.
-
Integrate with any collaborative platform.
-
Face recognition for better results.
-
Make the solution available for Corporates trainings, Project Management, Conferences, etc.
By following the tutorial, you'll set up a development environment, deploy an app locally on IBM Cloud®, and integrate a database service in your app.
Explain how to run the application.
You can find a running system to test at remote-e.eu-gb.mybluemix.net
- IBM Cloud Foundry - Used for solution deployment
- IBM DB2 - Database on Cloud
- Python - Developed using Python
- Django - The web framework used
- Jitsi.org - deploy secure video conferencing solutions
- [Bootstrap 4] (https://getbootstrap.com/docs/4.0/getting-started/introduction/) - Fast, responsive design
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.