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Paper Title : E-Learning and Student Motivation

ISSN : 2395-1303
Year of Publication : 2020
10.29126/23951303/IJET-V6I2P8

Authors: -Dhivin Joshua Nelson, Mihir Jatin Shah, Ganesh Dhole, Kaustav Biswas, Ratnmala Bhimanpallewar

         


Abstract
The main aim of this project is to provide a methodology for crop yield production based on the historical climatic and production data. Crop yield prediction based on the previous years of temperature and rainfall can help farmers take necessary steps to improve crop yield in the coming season. Understanding crop yield can help ensure food security and reduce impacts of climate change. Crops are sensitive to various weather phenomena such as temperature and rainfall. Therefore, it becomes crucial to include these features when predicting the yield of a crop. Weather the forecasting are complicated process. In this work, ARMA (Auto Regressive Moving Average) method is used to forecast crop yield. Past ten years of data set is taken for temperature, rainfall and ground water level for our country. Yield prediction is then carried out using a Fuzzy logic algorithm to better judge the crop yield. In addition, this project classifies the ground water level data set records using KNN to predict the model for future test record data sets. It will be helpful in analyzing the ground water levels in the past and so as to predict the future levels. Our aim is to develop an efficient, “E-Learning” System in which we will detect user presence by using[1] OpenCV this will make sure that the user to complete the course has to be physically present, the moment our System detects that the user is not present the video will automatically be paused. To help the system admin analyze user activity we our plotting a graph with the help of Bokeh plot which shows when the user was present, and when the user was absent. To understand better the user behavior for the course, we have also implemented an Emotion detection system that will take the frames captured in the motion detection as input and will identify the emotion of the user such as happy or sad. This will give us the precise idea about the quality of the content of the course. This is a self-learning bot developed to take course feedback, user opinions and reviews of user to improve course contents and make the course more effective and interesting to learn for the users. Basically the Chatbot is included in the E-learning System for feedback purposes. [2]Feedback is an important component of interaction. The educational contents in the course is continually improved using the information between the interaction of the bot and the user. These results in a more effective way of course development.

Reference
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Keywords
Motion Detection, Chatbot, E-Learning, CNN, Smart CED, Student Motivation, Data Virtualization.