Evidence map›Paper›PMID 36532789›Full record

ArticleEducation and information technologies2022

Longitudinal study of teacher acceptance of mobile virtual labs.

Vysakh Kani Kolil, Krishnashree Achuthan

Open access · bronzeAbstract read
In one paragraph

Article in Education and information technologies, 2022. 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
13.0field-weighted citation impact, top 2% of its field
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, 30 citations in OpenAlex.

  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

2 authors at 1 institution in 1 country.

Vysakh Kani KolilCenter for Cybersecurity Systems and Networks, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, 690525 Kerala India.ORCID 0000-0003-2035-3439
Krishnashree AchuthanCenter for Cybersecurity Systems and Networks, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, 690525 Kerala India.
Amrita Vishwa Vidyapeetham · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Synthesizing the advancements in technology with classroom practices depends considerably on teachers acceptance of such internet and communication technology (ICT) tools. Adequate teacher training and upgrading of their IT skills are not prioritized in developing economies leading to poor adoption of emerging technology assisted pedagogic interventions. This paper investigated the underlying characteristics of teachers acceptance of mobile friendly virtual laboratories (M-VLs) as part of a longitudinal study conducted over 5 years covering both pre-pandemic and pandemic periods. Systematic analysis of quantitative data from 650 chemistry teachers was carried out. Viewing through the theoretical lens of Unified Theory of Acceptance and Use of Technology (UTAUT2) theory, the effects of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM) and habit (HA) on the behavioral intention (BI) and use behavior (UB) were scrutinized. Structural Equation Modeling (SEM) analysis revealed that PE, SI, and HA are the considerable predictors of the BI to use M-VLs and HA is the predictor of UB. The present study found HM influencing teacher's BI and UB before COVID-19. However during COVID-19 the FC influenced usage. Moreover, we found that the technology training focused on enhancing knowledge, skill and, access leads to teachers' are critical to empowering teachers and causing wider adoption.

Indexed as

Mobile technology adoptionUser intentionUTAUT2 modelVirtual labs

Identifiers

PMID36532789
PMCPMC9742037
OpenAlexW4311123373

What OpenQuestion holds

Textmetadata
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.