ArticleJournal of environmental and public health2022
Monitoring and Sharing of Music Teaching Environment Resources Using Big Data Technology.
Article in Journal of environmental and public health, 2022. 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 It has been retracted, and should not be counted.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 1 paper.
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
1 citing paper in PubMed, 4 citations in OpenAlex.
- Retracted: Monitoring and Sharing of Music Teaching Environment Resources Using Big Data Technology.Journal of environmental and public health · 2023Article
Corrections and comments
- Retraction · 2023-06-28Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/2CFB21D7C5CCA2CA7C5155843B616B
- Retracted
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The teaching materials for different music courses in schools are getting more and more plentiful as education continues to become more and more digitised. This paper develops a resource monitoring and recommendation algorithm for the music teaching environment based on big data analysis technology, achieves the unified management and parallel retrieval of large music teaching resources, and completes the construction and sharing of music teaching resources with the goal of promoting online music teaching courses and increasing the efficiency of instruction. According to the experimental findings, the algorithm's recall and precision may both approach 95.84% and 95.19%, respectively. This demonstrates the benefits of this strategy. With the ability to analyse and retrieve large teaching resources and data quickly and accurately, this model can offer an advantageous solution for the storage and sharing of existing and future massive teaching resources. In order to effectively integrate music curriculum materials into our lessons, music teachers need to have a thorough awareness of not just the knowledge found in textbooks but also the adaptable use of music resources both within and outside of the classroom.
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.