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Cognitive_Challengers (Challenge 1)

by mvneema10

This project is related to the submission for #BuildWithAI 2021 for Challenge 1. CHALLENGE #1 - Digital Learning & Education The Pandemic has impacted education - classes have moved online, students have been isolated on screens and coping with this change. Despite the challenges, the digital school has the potential to transform education. How can we empower students and teachers in this new digital school paradigm? The kit is a collection of all the libraries we used to develop the predictive model to predict the Success Factor based on the student's input such as course module, date, score, activity type, total clicks on materials, disable, imd_band, studied credits, etc. The project can be extended to predictive the Knowledge factor where the students are knowledgeable based on the combination of date assignment, activity like Forum, Quizzes, subpage, clicks, type, etc.

Solution Source, Deployment Instructions are not available for this kit.


These are the basic libraries that are used to build the entire project.

Feature Engineering:

The project uses a label encoder to encode the necessary columns for model fitting and prediction.

Model Building:

The project uses Logistic Regression to develop the model for predicting Success Factors for the list of inputs. The model predicts based on the inputs provided by the user that the student will succeed or fail in the course module.

Front End Application:

The project uses Flask, HTML, CSS for the Front End UI application.