| Literature DB >> 35818392 |
Farooq Abdullah1, Sumera Kauser2.
Abstract
This research provides an insight into the students' perspective on online learning during the pandemic. We conducted this research in one of the universities of Azad Jammu and Kashmir (AJK). A quantitative research design was employed, and cross-sectional research method was used. An online survey form was administered by using Google survey forms on Likert scale (N = 405). The online survey and use of social media tools were adopted owing to the pandemic. The Google survey form was disseminated among the students by means of teachers through social media tools using convenient sampling technique. Chi-square results showed highly significant association among the variables. Regression analysis found that lack of technology, learning skills, and disconnectedness of internet, marking and grading issues, and mental growth are the predictors of the bad educational performance of the students. It is, thus, concluded that the students' educational performance is badly affected due to the online learning amidst the COVID-19 pandemic in AJK. It is suggested to the higher educational institutions to take the radical measures of preparedness during any such crisis to ensure the smooth online educational and learning environment to the students.Entities:
Keywords: COVID-19; Grades; Mental issues; Online learning; Pandemic; Performance
Year: 2022 PMID: 35818392 PMCID: PMC9258470 DOI: 10.1007/s11135-022-01470-1
Source DB: PubMed Journal: Qual Quant ISSN: 0033-5177
The demographic characteristics of the students
| Sr. no. | Variables | Referents | Count | Percentage |
|---|---|---|---|---|
| 1 | Age | 20–25 | 281 | 69.4 |
| 26–31 | 105 | 25.9 | ||
| 32 and Above | 19 | 4.7 | ||
| Total | 405 | 100.0 | ||
| 2 | Faculty | Arts | 120 | 29.6 |
| Science | 104 | 25.6 | ||
| Engineering | 101 | 25 | ||
| Health Sciences | 80 | 19.7 | ||
| Total | 405 | 100.0 | ||
| 3 | Residence | Rural | 251 | 62.0 |
| Urban | 154 | 38.0 | ||
| Total | 405 | 100.0 | ||
| 4 | Educational Level | BS | 273 | 67.4 |
| MSc/MA | 80 | 19.8 | ||
| MS | 38 | 9.4 | ||
| PhD | 14 | 3.5 | ||
| Total | 405 | 100.0 |
Chi-Square statistical test (dependent variable = educational performance)
| No. | Variable/s | Pearson value | df | |
|---|---|---|---|---|
| i | Lack of Technology | 222.661a | 6 | .000 |
| ii | Low Grades | 217.023a | 8 | .000 |
| iii | Effect on Mental Growth | 325.455a | 8 | .000 |
| iv | Marking Issues | 260.286a | 8 | .000 |
| v | Low Learning Skills | 58.790a | 6 | .000 |
| vi | Internet Issues | 309.314a | 8 | .000 |
| Total number of observations (n) = 405 | ||||
An OLS multiple regression predicting educational performance of students (standard errors and parameter estimates)
| Sr. no. | Unstandardized coefficients | Standardized coefficients | ||||
|---|---|---|---|---|---|---|
| Variables | B | Std. error | Beta | t | Sig. | |
| i | Technology | .170 | .013 | .312 | 11.016 | .000 |
| ii | Grades | .140 | .011 | .240 | 8.613 | .000 |
| iii | Mental Growth | .154 | .012 | .277 | 9.983 | .000 |
| iv | Marks Criteria | .113 | .016 | .167 | 6.043 | .000 |
| v | Learning Skills | − .270 | .023 | − .314 | − 10.766 | .000 |
| vi | Internet Issues | − .142 | .014 | − .303 | − 11.374 | .000 |
| (Constant) | 1.191 | .046 | 20.821 | .000 | ||
| F = 106.473, Sig. = .000 | R Square = 0.429, Adjusted R Square = 0.425. df = 6 | |||||
| Total number of Observation (n) = 405 | ||||||
Fig. 1An OLS multiple regression predicting educational performance of students