Evidence map›Paper›PMID 37361802›Full record

ArticleEducation and information technologies2023

Willingness of university students to continue using e-Learning platforms after compelled adoption of technology: Test of an extended UTAUT model.

Harshali Patil, Swapnil Undale

Abstract read
In one paragraph

Article in Education and information technologies, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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

2 authors.

Harshali PatilSchool of Business, Dr. Vishwanath Karad MIT World Peace University, Pune, India.ORCID 0000-0001-5097-7459
Swapnil UndaleSchool of Business, Dr. Vishwanath Karad MIT World Peace University, Pune, India.ORCID 0000-0003-4533-7953

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has prompted the adoption of an e-Learning pedagogy. This forced teachers and students to shift to online learning and thus was compelled to adopt online educational technology. Educational institutes have been facing challenges like insufficient infrastructure and a shortage of quality teachers. Online learning can help to address these challenges as online classes can accommodate more students. However, before implementing e-Learning technology management of institutes wants to be sure whether students will adopt new technology. Therefore, the purpose of this study was to unveil which factors are important to adopt new technology if implemented mandatorily. We tested the most popular technology acceptance model the UTAUT to understand students' intentions to continue using the e-Learning system in a mandatory environment. The study used a quantitative approach of research. The participants for this study were selected from a private university in India. The questionnaire for the study was adapted from previous studies. The survey was conducted by sharing an online link while students were attending classes online during the pandemic. Thus, the study utilized a convenience sampling technique. The data were analyzed using structural equation modelling. The findings revealed that the UTAUT model can partially explain the forceful adoption of technology. The study found 'Performance expectancy' and the 'availability of resources' as significant indicators of 'intention for continued usage'. This study recommends educational institutes should ensure students attain academic goals by using e-Learning platforms and ensuring the availability of essential resources to use the e-Learning technology.

Indexed as

Compelled adoptione-LearningHigher educationMandatory adoptionOnline learningUTAUT Model.

Identifiers

PMID37361802
PMCPMC10116094

What OpenQuestion holds

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Registered trials

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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.