Evidence map›Paper›PMID 40477649›Full record

ArticleSmart learning environments2021

University academics' perceptions regarding the future use of telepresence robots to enhance virtual transnational education: an exploratory investigation in a developing country.

Hanaa Ouda Khadri

Abstract read
In one paragraph

Article in Smart learning environments, 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

1 author.

Hanaa Ouda KhadriFaculty of Education, Ain Shams University, Cairo, Egypt.ORCID 0000-0002-1227-6624

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a growing interest in employing telepresence robots in different educational contexts due to their great potentials to enhance and improve educational experiences for remote learners. However, there is little use of telepresence robots in virtual transnational education contexts in developing countries. There is a lack of knowledge about university academics' perceptions regarding the future use of telepresence robots to enhance virtual transnational education contexts. This exploratory research aims to fill this gap by seeking to have evidence-based information on whether telepresence robots as a new emerging technology is perceived among university academics as a useful tool for enhancing virtual transnational education or not. This study also seeks to better understand university academics' perceptions of obstacles that may hinder them from using telepresence robots and the support that they will need. A sample of 46 Egyptian university academics participated in this study. The results of the study revealed that the academics perceived telepresence robots to have a great potential to enhance virtual transnational education. The academics also perceived telepresence robotics to have positive effects on educational activities. Furthermore, the participants indicated a number of barriers regarding integrating telepresence robotics into the teaching and learning activities and identified the types of support they will need. The uptake of telepresence robots to enhance virtual transnational education could lead to a larger international learner population, better virtual transnational education, and more university revenue. Recommendations for future research are also presented. Supplementary Information: The online version contains supplementary material available at 10.1186/s40561-021-00173-8.

Indexed as

Academics’ perceptionsRobotic telepresenceTelepresence robotsVirtual students’ mobilityVirtual transnational education

Identifiers

PMID40477649
PMCPMC8561341

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.