Predicting Students' Performance Using Machine Learning Models

Local Chapter Ondo, Nigeria Chapter

Coordinated by,

Jeremiaha Oluseye

Project background.

Student performance has been a global concern since it is influenced by a variety of causes and environments that vary by place. Student performance in certain places might be influenced by regional difficulties for a variety of reasons. Machine learning can be used to determine whether a student’s performance is poor or high, and it can also provide solutions by comparing low-performing students to high-performing students and observing what each of them accomplishes differently. Different prediction models will be used to guarantee that each model’s accuracy is adequate.

The problem.

The project focuses on analyzing the reason for student performances in exams both the success and failures and also deploying a machine learning model to predict the

Project goals.

The goals of the project are:1. Using various visuals, analyse the various performances of students. 2. Develop a model that can predict student performance and the underlying cause of that performance. 3.Make an attempt to devise a study plan that all students can adhere to. 4. Create a detailed report with analytical visualisation and briefs on these major items.

Project plan.

  • Week 1

    Data Collection (pre-week 1 even)

    Data Pre-Processing

  • Week 2

    Data Pre-Processing

  • Week 3

    Exploratory Data Analysis

    Modelling

  • Week 4

    Modelling (cont)

  • Week 5

    Possible deployment into API

  • Week 6

    Visualisation and publication

  • Week 7

    Visualization and publication (cont.)

  • Week 8

    Visualization and publication (cont.)

  • Week 9

    Wrap up

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