Evidence map›Paper›PMID 37809667›Full record

ArticleHeliyon2023

Chatbot for communicating with university students in emergency situation.

Antonio Balderas, Roberto Fermín García-Mena, Milagros Huerta, Nestor Mora, Juan Manuel Dodero

Abstract read
In one paragraph

Article in Heliyon, 2023. 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. Review
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

5 authors.

Antonio BalderasDepartamento de Ingeniería Informática, Escuela Superior de Ingeniería, Puerto Real, 11519, Cádiz, Spain.
Roberto Fermín García-MenaDepartamento de Ingeniería Informática, Escuela Superior de Ingeniería, Puerto Real, 11519, Cádiz, Spain.
Milagros HuertaDepartamento Ingeniería Mecánica y Diseño Industrial, Escuela Superior de Ingeniería, Puerto Real, 11519, Cádiz, Spain.
Nestor MoraDepartamento Ingeniería en Automática, Electrónica, Arquitectura y Redes de Computadores, Escuela Superior de Ingeniería, Puerto Real, 11519, Cádiz, Spain.
Juan Manuel DoderoDepartamento de Ingeniería Informática, Escuela Superior de Ingeniería, Puerto Real, 11519, Cádiz, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chatbots have arrived in higher education, and professors are trying to make the most of them. Typically, chatbots are used to help students learn academic subjects. In times of crisis, such as the COVID-19 pandemic, students who were not living with their families during the course, especially international students, were isolated and in critical situations. The student services offices were in constant contact with these students to solve problems, advise them and support them during their stay, within the constraints of confinement and the guidelines dictated by the country at the time. The student services offices were overwhelmed trying to help these students because, although the students' problems were very recurrent, the government guidelines changed from one day to the next. This article proposes the use of a chatbot to provide initial support to students during crisis situations, and facilitate communication between them and the university. The chatbot was tested by more than 160 students and student services staff. The findings support the use of chatbots as a potential tool to facilitate communication with students in emerging emergency situations, and encourage universities to adopt these types of smart tools to be prepared to respond quickly and efficiently to students in times of crisis.

Indexed as

00001111ChatbotCOVID-19Emergency situationStudents

Identifiers

PMID37809667
PMCPMC10558753

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.