Evidence map›Paper›PMID 38975208›Full record

ReviewHeliyon2024

M-Learning in education during COVID-19: A systematic review of sentiment, challenges, and opportunities.

Atika Qazi, Javaria Qazi, Khulla Naseer, Najmul Hasan, Glenn Hardaker, Dat Bao

Abstract readReview
In one paragraph

Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Atika QaziCentre for Lifelong Learning, Universiti Brunei Darussalam, Brunei Darussalam.
Javaria QaziFaculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan.
Khulla NaseerFaculty of Biological Sciences, Quaid-i-Azam University, Islamabad, Pakistan.
Najmul HasanBRAC Business School, BRAC University, Dhaka, Bangladesh.
Glenn HardakerKing Abdullah University of Science and Technology, Saudi Arabia.
Dat BaoFaculty of Education, Monash University, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The flexibility and relatively low cost of mobile devices make educational systems more accessible for learners and educators worldwide. When incorporated with the internet, it creates a better learning environment than the conventional classroom lecture. Many studies have been done to shed insight into the existing state of mobile learning (M-learning) studies. However, further research is needed into this topic at a specific time, i.e., during the COVID-19 pandemic. This study aims to retrieve, review, investigate, and critically assess the existing literature on M-learning that was conducted during the COVID-19 concerning our research theme. This study considered publications from four databases, narrowed our initial search results of 4056 articles down to 83 that are relevant to our research questions, and did an in-depth analysis based on the systematic review protocol. The findings explored the major focusing areas of M-learning applications, the regional sentiment of M-learning users, the determinants and perceptions of M-learning, as well as the benefits, challenges, and opportunities associated with M-learning. This systematic literature review (SLR) was performed to apportion a contribution toward an improved understanding of the basic principles that underpin the rethinking of M-learning applications for policymakers, online course designers, and blended learning facilitators.

Indexed as

ChallengesCOVID-19Education researchM-learningOpportunitiesSentimentSystematic literature review

Identifiers

PMID38975208
PMCPMC11225771

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.