ArticlePloS one2024
Application of multimedia technology to innovative vocational education on learning satisfaction in China.
Article in PloS one, 2024. 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 It has been retracted, and should not be counted.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 5 papers, 1 of them a synthesis that pooled 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.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A scoping review of school-based oral health interventions among adolescents in Nigeria.Frontiers in oral health · 2025Pooled it
- The serial mediating effects of learning motivation and learning engagement on the relationship between gen AI literacy and EFL perceived proficiency among vocational students.Frontiers in psychology · 2026Article
- Impact of integrating flipped classroom model and multi-functional camera system on practical skills and satisfaction in musculoskeletal rehabilitation education among health professional students.BMC medical education · 2025Article
- Enhancing employee job satisfaction through organizational climate and employee happiness at work: a mediated-moderated model.BMC psychology · 2024Article
- Retraction: Application of multimedia technology to innovative vocational education on learning satisfaction in China.PloS one · 2024Article
Corrections and comments
- Retraction · 2024-09-05Concerns/Issues about Authorship/Affiliation · Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Human Subject Welfare · Investigation by Journal/Publisher ·
- Retracted
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multimedia technology holds paramount importance in driving innovation within vocational education, significantly influencing learning satisfaction. Its integration facilitates dynamic and interactive learning environments, catering to diverse learning styles and preferences. Moreover, multimedia technology enables educators to simulate real-world scenarios, providing practical and hands-on training opportunities. This aspect is particularly valuable in vocational education, where practical skills and application are required. The paper investigates the impact of multimedia technology in enhancing learning satisfaction within innovative vocational education. It delves into the utilization of multimedia tools and their correlation with learner satisfaction, exploring how these technologies augment engagement and comprehension in vocational training. The primary data from 515 students of vocational colleges of China has been collected and regression analysis is applied for empirical analysis. The findings of the study highlight that multimedia technology has positive relationship with innovative vocational education and learning outcome. The findings contribute valuable insights for policymakers regarding significant role multimedia plays in fostering enhanced learning experiences and overall satisfaction among vocational learners.
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.