Developing Intelligent Learning Management System for School in Remote Area

The Developing Intelligent Learning Management System for Schools in Remote Area project was made to solve the problem of the scarcity of a learning platform for underprivileged kids in remote areas in Thailand. 

The objective of this project is to create a Learning Management System(LMS) for Minmahaw School in the town of Mae Sot, Thailand. The LMS will include a way for the teachers and students to submit, grade, and review their assignments and other essential functions for an LMS such as a calendar and a report card. It will also incorporate the use of AI technology to optimize the LMS system and provide the user with some useful insights in terms of the performance of both the students and the teachers.

Solution Approach 

Our plan involves using Moodle to construct a comprehensive learning website that caters to high school students who may not have prior experience with online learning platforms. These websites will encompass all essential features, including sections for assignments, grading, class materials, and slides. For the assignment section, we intend to expand it to include subsections such as projects and homework.

We will use Figma as our primary UI/UX design tool to ensure our learning websites are user-friendly and seamlessly integrated into the existing school education system. Our aim is to make them as intuitive as possible, minimizing disruptions and delays as students and teachers increasingly rely on the platform.

Project Objectives

By the end of Fall 2023, our goal is to complete the foundational development of an LMS website featuring essential functionalities. These include maintaining a student database and course records, distributing assignments, sending timely notifications about deadlines, and providing grading for student work. The website will also host a calendar displaying students' learning schedules and public holidays.


The current results from the project consist of the LMS website and the two machine learning models.

4.1 LMS website

Our LMS website has all the basic features of an LMS website including: 

1. Courses:

Teachers can create courses and organize the content inside of them. Teachers can also enroll students on their courses.

2. Content Creation and Learning Resources:

The students and teachers can upload their files to the website.

3. Activity Modules:

Each course has the capability to post assignments and quizzes.

4. Gradebook:

The website has a grading scheme, a page to see the student’s grades and a way to print the grade book. 5. Calendar

6. Roles and permissions

7. Authentication:


4.2 Machine Learning

4.2.1 Polynomial Regression

Based on the generated data. The regression model can predict scores based on the previous scores.

Summary of Accomplishments

The basic parts of the LMS have been built to support users to view assignments, submit assignments, and the teachers to grade them. There are also convenience features such as a calendar, a home page, and a grade page. The UI has been made with usability in mind. The LMS also holds a basic authentication feature, allowing only certified users to access the website. The website has been hosted on the internet, allowing anyone to access it online.

Future Directions 

Web Hosting

The plan for the project in the future is to change the hosting platform as it’s not feasible in the long term to host it on a university computer due to security reasons and scalability issues. The server is planned to be hosted on the Minmahaw School’s computer and then accessed remotely using Tail Scale to access the computer using Secure Shell.

ML Models

There are several ML models that could be used in the future for different purposes. 5.3.3 


The current website does not have clear documentation on how to use it, in the future, if we’re going to be scaling the website to different schools, we would need to have a comprehensive instructions tutorial on how to properly use the website.

Pasit Wanlapha
CMKL University
Kadpon Duangkaew
CMKL University
Kunanont Taechaaukarakul
CMKL University
Rawipol Korpraphong
CMKL University
Korn Visaltanachoti
CMKL University
Adil Siripatana
Assistant Professor
CMKL University