Recommendation System for learning personalization based on learning style identification

Creation of a recommendation system capable of identifying class of learners? based on student data collected for a particular programming subject. The data will comprise of student previous knowledge, marks obtained by students in previous core subjects (programming), ru

Project Title

Recommendation System for learning personalization based on learning style identification

Project Area of Specialization

Artificial Intelligence

Project Summary

Creation of a recommendation system capable of

identifying class of learners’ based on student data collected for a

particular programming subject. The data will comprise of student

previous knowledge, marks obtained by students in previous core

subjects (programming), rubrics and any other relevant data. The

project has two parts: identification of class of learners’ (slow

learners, average learners, and efficient learners) and based on the

identified class, suggestion of personalized course modules for

improvement of student learning.

Project Objectives

To create a system that better learns the type of students(learner's type) and help the teacher to assist him/her more accurately and betterly in class.

To help the student get good grip on studies. Based upon his/her learning style, the system will encourage student to learn via his/her best-fit method/style.

Project Implementation Method

First a huge amount of data is required to train the algorithm once algorithm is trained we need more data (dataset of students) to test our algorithm once the algorithm is tested and is better to use then we can implement the algorithm on any site of any context i-e E-Learning System or Coursera like Web Applications or Even University Student's Portal.

Benefits of the Project

Student will better understand his/her learning style, then he/she can focus on that particular area and can learn smartly.

Learners of different types(Visualistic: one who better understands with Graphs and Pictorial Morphs, Talkative: one who better understands with group of other people via chitchat or discussion, Loner: one who understands by speaking to himself, making notes or self studying), for a teacher to deliver lecture and identify types of students at the same time is quite hectic. So student can always get help from this algorithm. Algorithm not only classifies the type of student but it also recommends the learning modules

Technical Details of Final Deliverable

The final results will include a full-fledged web application that takes data from student (statically) or from other agents in environment (dynamic) and classifies student and recommend him/her the best-fit learning module.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Education

Core Technology

Artificial Intelligence(AI)

Other Technologies

Big Data

Sustainable Development Goals

Quality Education, Reduced Inequality

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com