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.

A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling [PeerJ]

A comparative analysis of the impact of online, blended, and face-to-face learning on medical students' clinical competency in the affective, cognitive, and psychomotor domains, BMC Medical Education

Layer-by-Layer Analysis of In Vitro Skin Models

ProtInteract: A deep learning framework for predicting protein–protein interactions - Computational and Structural Biotechnology Journal

The evaluation of university management performance using the CS-RBM algorithm [PeerJ]

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

System model. Full-size  DOI: 10.7717/peerj-cs.11011101/fig-2

Perspectives in machine learning for wildlife conservation

Review of artificial intelligence‐based question‐answering systems in healthcare - Budler - 2023 - WIREs Data Mining and Knowledge Discovery - Wiley Online Library

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