KYS Progress Tracker

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  Prediction along with reason for poor performance

The COVID-19 has resulted in schools shut all across the world. Globally, over 1.2 billion children are out of the classroom. As a result, education has changed dramatically, with the distinctive rise of e-learning, whereby teaching is undertaken remotely and on digital platforms, resulting in the issue of the digital divide. Developing a student progress tracker that predicts student performance would help rectify the divide, as the tracker predicts performance levels and suggestions to aid educators to help students who are lagging behind academically. Educators can focus on taking practical and effective decisions for each and every student, thereby ensuring no student is marginalized in digital education. Detection of student performance based on predictive analysis aids educators to concentrate particularly on students in genuine need of assistance. In this Covid struck the world, this will create a major impact on education as every single thing is done via online mediums. The idea can be incorporated into present learning management systems to make them even more successful. Challenges I ran into were collecting and arranging student data was the most challenging part of the whole building process. We managed to collect data from learning management systems and cleaned it up. Another challenge was in developing UI for the project. We used the Streamlit library to resolve that.

Built With

• python
• scikit-learn
• streamlit