A Plain Bayesian Algorithm-Based Method for Predicting the Mental Health Status and Biomedical Diagnosis of University Students.
Comput Intell Neurosci
; 2022: 2617488, 2022.
Article
in English
| MEDLINE | ID: covidwho-2020485
ABSTRACT
The purpose of this study was to assess e-learning during Corona epidemic regarding advantages, limitations, and their recommendations for managing learning during the epidemic. Based on a case study, this study used qualitative research. Sixteen students from King Saud University's College of Education were invited to take part. These students receive their online lectures via the "Zoom" application. A 20-minute WhatsApp one-on-one semiorganized interview was likewise utilized. To guarantee the reliability, iCloud was utilized to record gatherings and meetings for direct record (adaptability, constancy, confirmability, and validity). Results were presented in three themes advantages of employing distance education, limitations of usages, and recommendations for improvements. Analyzing the feedbacks collected from students by the four interviewers, important characteristics of distance education emerged. They were student-centered learning, which included comfortable, self-directed learning, asynchronous learning, and flexibility. The most common limitations associated with distance education, in general, included inefficiency, that is, lack of student feedback, and lack of attentiveness. As for recommendations for improvements the most obvious characteristics that became evident in students' responses were teaching and assessment and quality enhancement.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Students
/
Algorithms
Type of study:
Prognostic study
/
Qualitative research
Limits:
Humans
Language:
English
Journal:
Comput Intell Neurosci
Journal subject:
Medical Informatics
/
Neurology
Year:
2022
Document Type:
Article
Affiliation country:
2022
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