Pharmacy Students’ Attitudes Toward Distance Learning After the COVID-19 Pandemic: Cross-Sectional Study From Saudi Arabia
Bibliographic record
Abstract
BACKGROUND: Electronic learning refers to the use of assistive tools in offline and distance learning environments. It allows students to access learning tools and materials anytime and anywhere. However, distance learning courses depend on several factors that affect the quality of learning, which consequently affect students' preferences in the settings and tools used to deliver educational materials. OBJECTIVE: This study aimed to evaluate students' preferences for continuing distance learning after the pandemic and to assess the distance educational environment after the pandemic. It also aimed to identify the factors affecting distance learning and evaluate students' preferences regarding modes of communication with instructors. METHODS: A web-based survey was used to conduct this cross-sectional study. The target participants of this study were students in the doctor of pharmacy program at Unaizah College of Pharmacy, Qassim, Saudi Arabia. All students enrolled from December 2022 to January 2023 received an invitation with a link to the web-based survey. RESULTS: The survey was completed by 141 students (58 female students and 83 male students). The research results showed that most students (102/141, 72.3%) did not wish to continue distance education for laboratory courses, and 60.3% (85/141) did not wish to continue taking distance team-based learning after the pandemic. Additionally, 83.7% (118/141) of the students indicated that distance courses were simple. More than half of the participants (79/141, 56%) stated that having a camera on during class negatively impacted their learning, and only 29.1% (41/141) of the students stated that nonvisual communication with their fellow students impacted their learning. A large proportion of students (83/141, 58.9%) reported impairment of social engagement on campus, 44% (62/141) in-person interactions during classes, and 73.7% (104/141) were relieved that their classes were not disrupted. CONCLUSIONS: Similar to all types of education, distance learning is characterized by advantages and disadvantages, as reported by students. Students felt that the course material was intelligible, and the distance course was uncomplicated. Moreover, they expressed relief that their studies were not disrupted. However, they also reported the loss of face-to-face contact during courses as the most significant drawback of distance learning versus face-to-face learning, followed by a lack of social connection on campus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".