Peer Review #1 of "Students’ performance in interactive environments: an intelligent model (v0.2)"

Abstract

Students' performance must be tracked in order to closely monitor all unfavorable barriers that may affect their academic progress in order to improve education quality and learning levels, especially during the spread of coronavirus as a result of school and university closures, and adapt to new developments.As a consequence, in the current study, a model has been designed to tell students about the results of the computer networks course in the middle of the second semester, as well as 11 machine algorithms (out of 5 classes).The efficiency of utilizing infographics for teaching computer networks course was determined using a questionnaire, and the findings demonstrated the effectiveness of infographics as a strategy for teaching computer networks.This is when the course is presented utilizing the Moodle (Modular Object-Oriented Dynamic Learning Environment) educational platform.Moreover, the numerous classification approaches in data mining were utilized to establish the best practices used to forecast students' performance using the Weka software, where the findings demonstrated the efficiency of the true positive direction of classification.The best approaches to categorize are functions, Multilayer Perceptron, trees Random Forest, trees Random Tree, Provided test set, and F-measure algorithms.