Students' performance in interactive environments: an intelligent model [PeerJ]

Modern approaches in education technology, which make use of advanced resources such as electronic books, infographics, and mobile applications, are progressing to improve education quality and learning levels, especially during the spread of the coronavirus, which resulted in the closure of schools, universities, and all educational facilities. To adapt to new developments, students’ performance must be tracked in order to closely monitor all unfavorable barriers that may affect their academic progress. Educational data mining (EDM) is one of the most popular methods for predicting a student’s performance. It helps monitoring and improving students’ results. Therefore, in the current study, a model has been developed so that students can be informed about the results of the computer networks course in the middle of the second semester and 11 machine algorithms (out of five classes). A questionnaire was used to determine the effectiveness of using infographics for teaching a computer networks course, as the results proved the effectiveness of infographics as a technique for teaching computer networks. The Moodle (Modular Object-Oriented Dynamic Learning Environment) educational platform was used to present the course because of its distinctive characteristics that allow interaction between the student and the teacher, especially during the COVID-19 pandemic. In addition, the different methods of classification in data mining were used to determine the best practices used to predict students’ performance using the weka program, where the results proved the effectiveness of the true positive direction of functions, multilayer perceptron, random forest trees, random tree and supplied test set, f-measure algorithms are the best ways to categories.

Swarm intelligence-based model for improving prediction performance of low-expectation teams in educational software engineering projects [PeerJ]

Students' performance in interactive environments: an intelligent model [ PeerJ]

Design of innovation ability evaluation model based on IPSO-LSTM in intelligent teaching [PeerJ]

Factors affecting digital technology access in vocational education

Computer model of a spectrum analyzer for a virtual laboratory: development and introduction to the educational process [PeerJ]

Full article: The influence of material and spatial size on indoor environment preference evaluation

Zmp 2017 29 issue 1 by Hogrefe - Issuu

A two-way model showing the interaction of Self-Directedness

Perspectives in machine learning for wildlife conservation

Students' performance in interactive environments: an intelligent model [ PeerJ]

Immersive virtual environments and embodied agents for e-learning applications [PeerJ]

Frontiers Exploring female students' perceptions of the use of digital technologies in managing academic stress

Education Sciences, Free Full-Text