This article is a Preprint
Preprints are preliminary research reports that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Preprints posted online allow authors to receive rapid feedback and the entire scientific community can appraise the work for themselves and respond appropriately. Those comments are posted alongside the preprints for anyone to read them and serve as a post publication assessment.
A prediction system using AI techniques to predict Students’ learning difficulties using LMS for sustainable development at KFU (preprint)
researchsquare; 2022.
Preprint
in English
| PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-1730504.v1
ABSTRACT
With the emergence of the covid 19 pandemic, E-learning usage was the only way to solve the problem of study interruption in educational institutions and universities. Therefore, this field reserved significant attention in current times. In this paper, we used ten Machine Learning (ML) algorithms Decision Tree(DT), Random Forest(RF), Logistic Regression(LR), SGD Classifier, Multinomial NB, K- Nearest Neighbors Classifier(KNN), Ridge Classifier, Nearest Centroid, Complement NB and Bernoulli NB) to build a prediction system based on artificial intelligence techniques to predict the difficulties students face in using the e-learning management system, to support related decision-making. Which, in turn, contributes supporting the sustainable development of technology at the university. From the results obtained, we detect the important factors that affect the use of E-learning to solve students' learning difficulties using LMS by building a prediction system based on AI techniques.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-RESEARCHSQUARE
Language:
English
Year:
2022
Document Type:
Preprint
Similar
MEDLINE
...
LILACS
LIS