ArticleJournal of healthcare engineering2021
The Effect of Introducing Infographic Pattern on Developing Cognitive Understanding by Using AI Technology for University Students during the COVID-19 Pandemic.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 11 citations in OpenAlex.
- Enhancing Evidence-Based Practice Competence and Professional Skills Using Infographics as a Pedagogical Strategy in Health Science Students: Insights from the InfoHealth Project.European journal of investigation in health, psychology and education · 2024Article
- An analysis of retracted COVID-19 articles published by one medical publisher with multiple journals.Proceedings (Baylor University. Medical Center) · 2024Article
- Use of infographics for facilitating learning of pharmacology in the nursing degree.Nursing open · 2023Article
- Retracted: The Effect of Introducing Infographic Pattern on Developing Cognitive Understanding by Using AI Technology for University Students during the COVID-19 Pandemic.Journal of healthcare engineering · 2023Article
Corrections and comments
- Retraction · 2023-05-24Concerns/Issues about Data · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the COVID-19 pandemic, this study sought to determine the impact of AI-supported infographic templates (static versus animated) on academic achievement, visual thinking skills, and willingness to learn among a sample of university students. The researcher created two distinct AI-supported instructional infographic templates to determine the effect of such an independent variable on his three other primary dependent variables, namely, academic accomplishment, visual thinking skills, and willingness to learn, in order to meet his study goals. An achievement exam, a visual thinking test, and a willingness to learn scale were among the research methods used. The quasiexperimental method was used to provide the research instruments, and experimental therapy was used to a select group of students at Umm Al-Qura University. According to the findings, AI-assisted static and animated infographic templates had a favorable impact on the development of all learning aspects studied. AI-assisted animated infographics, on the other hand, had a more significant impact than AI-assisted static infographics. In light of this, the researcher concluded his research by making a number of recommendations and suggesting additional research, such as maximizing the use of AI emerging technologies and their practical application in an adaptive manner suitable for education.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.