A machine learning-based analysis for the effectiveness of online teaching and learning in Pakistan during COVID-19 lockdown.
Background: The COVID-19 pandemic has significantly disrupted daily life and education, prompting institutions to adopt online teaching. Objective: This study delves into the effectiveness of these methods during the lockdown in Pakistan, employing machine learning techniques for data analysis. Meth...
| Publicado en: | Work Vol. 81; no. 1; pp. 2340 - 2359 |
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| Autores principales: | , , , , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
May2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=185232262&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 185232262 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10519815 3RC jtl: Work issn: 10519815 maglogo: N pubinfo: dt: May2025 vid: 81 iid: 1 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 185232262 182227043 185232262 185232262 10.1177/10519815241308161 185232262 ppf: 2340 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A machine learning-based analysis for the effectiveness of online teaching and learning in Pakistan during COVID-19 lockdown. aug: au: Zeeshan, Hafiz Muhammad Sultana, Arshiya Bin Heyat, Md Belal Akhtar, Faijan Parveen, Saba Bin Hayat, Mohd Ammar Sayeed, Eram Sayed Abdelgeliel, Asmaa Muaad, Abdullah Y. affil: Department of Computer Science, National College of Business Administration & Economics, Lahore, Pakistan sug: subj: COVID-19 Pandemic Psychosocial Factors Stay-at-Home Orders Teaching Methods Learning Methods Online Education Machine Learning Outcomes of Education Human Adolescence Adult Middle Age Male Female Pakistan Cross Sectional Studies Nonexperimental Studies Structured Questionnaires Artificial Intelligence Sensitivity and Specificity Descriptive Statistics Learning Environment Student Placement Personal Satisfaction Psychological Well-Being Data Analysis Software Qualitative Studies Quantitative Studies Pearson's Correlation Coefficient Chi Square Test Fisher's Exact Test Decision Trees Logistic Regression Algorithms Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: Background: The COVID-19 pandemic has significantly disrupted daily life and education, prompting institutions to adopt online teaching. Objective: This study delves into the effectiveness of these methods during the lockdown in Pakistan, employing machine learning techniques for data analysis. Methods: A cross-sectional online survey was conducted with 300 respondents using a semi-structured questionnaire to assess perceptions of online education. Artificial intelligence methods analyzed the specificity, sensitivity, accuracy, and precision of the collected data. Results: Among participants, 42.3% expressed satisfaction with online learning, while 49.3% preferred using Zoom. Convenience was noted with 72% favoring classes between 8 AM and 12 PM. The survey revealed 87.33% felt placement activities were negatively impacted, and 85% reported effects on individual growth. Additionally, 90.33% stated that online learning disrupted their routines, with 84.66% citing adverse effects on physical health. The Decision Tree classifier achieved the highest accuracy at 86%. Overall, preferences leaned toward traditional in-person teaching despite satisfaction with online methods. Conclusions: The study highlights the significant challenges in transitioning to online education, emphasizing disruptions to daily routines and overall well-being. Notably, age and gender did not significantly influence perceptions of growth or health. Finally, collaborative efforts among educators, policymakers, and stakeholders are crucial for ensuring equitable access to quality education in future crises. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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