Effective online learning management system to improve and enhance the online learning and student engagement experience

With the spread of Covid-19, there has been a shift towards distance learning and teachers find it difficult to keep track of students who are attentive during class. Unlike before, where the traditional classroom environment helped teachers keep track of the students who are not fully concentrating during the lessons. This shift to online learning has made teachers find it much more difficult to keep track of students who are idling during their lecture period. For this the following solution is proposed to introduce an extension to help teachers integrate with existing video conferencing platforms. This solution will help teachers to know whether the student has been attentive during class, by keeping track of their peripheral device movements, such as mouse movements or keystrokes. Previous studies have been conducted to keep track of student's eye movement and browser history, but no solution has been developed to easily plug and play' into an existing platform for teachers to get real time progress of a student's interaction to the lecture. The main objective of this research will be to help enhance the learning experience of a student by keeping the teacher aware of the student's progress just like in a traditional classroom environment. © 2022 ACM.

Slide Hatch: Smart Slide Generator

With the current situation of Covid-19 and people are moving into online learning for their studies, lecturers and teachers should find a way in which they could make online learning effective for students. The radical shift towards online learning has surged the use of various online tools and methods. The most common tool being used is the presentation slide. Due to the fact that most teachers and lecturers have less knowledge on creating presentations which helps retain student concentration levels during online learning, a system to help them to auto generate these lecture materials would be worthwhile. Previous studies have been conducted to look into generating slides for research and academic papers. However, there is no system which is fine-tuned to help teachers in generating slides automatically just by them uploading images from the lecture material they use. The main objective of this research will be to minimize the overhead and to have a smart way of generating slides for teaching to help students retain their concentration levels. © 2021 IEEE.

COVID-19 Spread prediction Based on Food Categories using Data Science

Novel corona (COVID-19) disease is an infectious disease caused by a newly discovered coronavirus. Covid-19 was started from Wuhan China and present it is spread all over the world. Presently the USA is affected by the Covid-19 virus hardly. Present there are more than 4.0 million confirmed cases and more than 200 thousand happens because of the Covid-19 virus. [1]. However, there is no medicine found by the researchers yet for the virus. According to the WHO (World Health Organization), the COVID-19 virus is spreading by several methods. And for protection from the COVID-19 virus, their suggestion is community distance. Moreover, doctors and other medical instructors advise concentrating more on doing sanitizations often. Presently there are lots of researches doing for identifying reasons, make a medicine in this area. When it concentrates on the spread of the COVID-19 virus it cloud be able to identify that there is a difference between Asian and European countries. As an example from Asian countries, only China and Russia are affected by the COVID-19 virus majorly. However European countries like Italy, Spain has the highest death rates more than china. Mainly south Asian countries have a low confirm rate of the COVID-19 virus. [2] For this, the main reason what here in this research identified is the food used by each region. We know that people in European countries eat fast foods and they have used alcohol more than the people in Asian countries. [3] Therefore this research was done to identify a pattern between the spread of the COVID-19 virus and the Food categories used by the people. So here in this research using data science. Here it does some data modeling part to visualize a pattern between the spread of the COVID-19 virus and food categories. Thereafter using a machine learning model here it implement a prediction model. Through this research, it could be able to understand that there is a clear pattern between the spread of the virus and the food factors. Moreover, this research will be a novel approach to evaluate the spread of the COVID-19 based on food categories. © 2020 IEEE.