Evidence map›Paper›PMID 35002820›Full record

ArticleFrontiers in psychology2021

COVID-19 and Rapid Course Adaptations in Saudi Arabia: An Experiential Learning and Recommendations for Online Education.

Basim Sulaiman Alatni, Ismaila Rimi Abubakar, Saad Arslan Iqbal

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Basim Sulaiman AlatniDepartment of Landscape Architecture, College of Architecture and Planning, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Ismaila Rimi AbubakarCollege of Architecture and Planning, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Saad Arslan IqbalDepartment of Landscape Architecture, College of Architecture and Planning, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 Pandemic has severely impacted educational systems around the globe, necessitating rapid modifications to the educational milieu while safeguarding human health and wellbeing. Following the closure of universities in Saudi Arabia, the instructors of all theory courses were mandated to switch from face-to-face course delivery to remote teaching and learning. This research examines the challenges and impacts of the COVID-19 Pandemic on the mode of teaching and learning and the numerous adaptations in the pedagogical framework of the Landscape Architecture program at Imam Abdulrahman Bin Faisal University, Saudi Arabia. It also explores the opportunities the transition to online education presents to faculty and students moving forward. The data were collected using an online questionnaire survey and focus group discussions. Data analyses consisted of descriptive statistics and thematic content analysis. The research finds that the sudden transition to online teaching and learning disrupted academic activities and had negatively affected the existing teaching and learning framework. Therefore, the research recommends an adaptable and dynamic teaching framework agile enough to cope with sudden disruptions. It concludes with lessons for future teaching and learning frameworks and amendments for upcoming sessions to deal with similar situations.

Indexed as

course adaptationsCOVID-19emergency remote educationexperiential learninghigher educationonline educationstudent satisfaction

Identifiers

PMID35002820
PMCPMC8733659

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.