Taking the classroom monitoring to the next level with SLPES

Works well for Administration, Lecturers and Students

Get Started

Research Project Scope

Literature Survey

ClassDojo

Software that encourages positive classroom behavior by awarding points for participation

Best For:
  • Teachers
  • School leaders
  • Families
Features

Useful for classrooms, Real-time chat facility.

TopHat

The Top Hat app motivates students to engage with course content, participate in class and ultimately master your material.

Run discussions in your classroom, assign interactive readings and quiz for understanding, all with one easy-to-use interface.

Features
  • Get real-time feedback on student progress.
  • Leverage students' devices in class to increase participation.
  • Upload your slides easily and add interactive questions.
  • Take attendance effortlessly and prevent absent students from bending the rules.
  • Launch real-time polls to gauge student understanding.

AI-enabled classrooms in China

A High School in Hangzhou, China has installed cameras which are designed to mark attendance automatically and track activities that students are engaging in, including reading, writing or listening.

In addition, students’ real-time emotions such as fear, happiness, sadness, surprise, disgust, anger and neutral are also tracked.

EduSense: Practical Classroom Sensing at Scale

EduSense is a comprehensive, open source, sensing system that produces a plethora of theoretically-motivated visual and audio features correlated with effective instruction, which can feed professional development tools in much the same way as a Fitbit sensor reports step count to an end user app

The system consists of 3 main components as follows.

  • Body Segmentation, Keypoints and Interframe tracking
  • Facial Landmarks
  • Speech Detection

Research Gap

AI Systems in China TopHat ClassDojo EduSense SLPES
Attendance Register
Monitoring Student Behavior
Lecture Summarizing
Monitoring Lecturer Performance

Research Problem

  • “What is the optimum way of tracking student attendance in a much efficient way and how does the lecturer analyze reasons for student absenteeism?” (Q1).
  • “Does a correlation exist between lecturing style and student behavior in the classroom and how can Computer Vision and Artificial Intelligence be incorporated in determining this relationship?” (Q2).
  • “How to summarize the lecture content to enable students to pay more attention to the lecture and reduce time spent for taking notes?” (Q3).
  • “How to evaluate lecture performance by tracking their behavior during a lecture and analyzing the quality of the lecture content which is delivered by the lecturer?” (Q4).

Research Objectives

Main Objectives

Tracking student attendance using facial detection and facial recognition, notify and getting opinion from the students who are absent and students who are leaving the lecture in the during a specified time period.

Monitoring student behavior within the classroom during lecture periods to identify potential problem areas in retaining student attention and adapting the lecturing styles to suit the student needs.

Summarize the converted text and present as a document and identify the important points of the lecture to display them highlighted.

Monitoring lecturers’ behavior by analyzing the lecture audio data recorded in a lecture hall during lecture hours.

Specific Objectives

Hello

Methodology

system diagram

As mentioned in the System Diagram, this system will mainly consist of a mobile and web application. When the students and the lecturer enter the classroom, their behavior will be monitored by two separate video-cameras and a microphone. The collected data will transmit to the server through local machine and stores the gathered data in the MongoDB cloud database service.

While the video camera tracks both facial expression and body movements, the microphone will record the lecture for further analysis. The student attendance will register by capturing facial identity using deep learning and computer vision mechanisms. Students will be monitored by capturing their facial and body movements by Computer Vision and Deep Learning algorithms.

The lecturer audio and video details will be gathered and stored for analyzing as such lecture summarizing and monitoring lecturer performance using machine learning, deep learning, and computer vision technologies. While the students have access to the mobile application, the lecturers and the higher management have the authority to manage the web-application. Frontend components will communicate with the backend using Django REST API.

Domains

Tools

Research Project Milestones

Proposal

Description

The Research group was given the opportunity to elaborate the research problem, research objectives and tentative methodology of the proposed study. The presentation was carried out by each individual describing their components

Date

Feb 27th, 2020.

Marks

10

Progress Presentation - 1

Description

This presentation was aimed to show the progress of the ongoing porcess, such that 50% of the complete product had to be presented. Each individual had to clearly mention what they have done and the actual percentage of the work completed

Date

July 13, 2020

Marks

15%

Progress Presentation - 2

Description

The main purpose of this presentation was to show the progress of the project. It was expected that 90% of the project to be completed.

Date

September 24, 2020

Marks

N/A

Demo

Description

The research project group had to design a Research Poster to provide a basic understand about the Research. The content included were Introduction, Literature Survey, Research Problem, Research Objectives, Methodology, Results and Discussion and Conclusion

Date

September 24, 2020

Marks

N/A

Final Assessment

Description

Date

Marks

Viva

Description

Date

Marks

Presentation

Proposal Presentation

  • Ullamco laboris nisi ut aliquip ex ea commodo consequat.
  • Duis aute irure dolor in reprehenderit in voluptate velit.

Progress Presentation - II

  • Ullamco laboris nisi ut aliquip ex ea commodo consequat.
  • Duis aute irure dolor in reprehenderit in voluptate velit.
  • Facilis ut et voluptatem aperiam. Autem soluta ad fugiat.

About Us

Supervisors

Samantha Rajapaksha

Senior Lecturer

Ms. Dinuka Wijendra

Lecturer

Group Members

Ishan Seneviratne

Group Leader

Sohan Perera

Member

Sachith Fernando

Member

Linisha Siriwardana

Member

Pricing

Free

$014 Days

  • Setup for one classroom
  • Includes: A Raspberry pi, 2 Cameras and a microphone

Paid

$150 Per Classroom

  • $25 Per annual
  • Includes: A Raspberry pi, 2 Cameras and a microphone

Contact

Make contact via the details below to get in touch with us.

Our Address

Sri Lanka Institute of Information Technology, New Kandy Rd, Malabe 10115

Loading
Your message has been sent. Thank you!