Evidence map›Paper›PMID 30603646›Full record

ArticleAnnals of translational medicine2018

The comparison of teaching efficiency between massive open online courses and traditional courses in medicine education: a systematic review and meta-analysis.

Fei Zhao, You Fu, Qi-Jie Zhang, Yue Zhou, Peng-Fei Ge, Hua-Xing Huang, Yuan He

Abstract read
In one paragraph

Article in Annals of translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. Learning Design Strategies in MOOCs for Physicians' Training: A Scoping Review.International journal of environmental research and public health · 2022
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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

7 authors.

Fei ZhaoDepartment of Cardiothoracic Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
You FuDepartment of Supervision, Nanjing Medical University, Nanjing 210029, China.
Qi-Jie ZhangDepartment of Urology Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Yue ZhouDepartment of Cardiothoracic Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Peng-Fei GeDepartment of Cardiothoracic Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Hua-Xing HuangNanjing Medical University, Nanjing 211166, China.
Yuan HeNanjing Medical University, Nanjing 211166, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis systematic review and meta-analysis aimed to investigate and compare the passing rates of Massive Open Online Courses (MOOCs) with Traditional Courses to indicate how to improve the teaching efficiency in Medicine Education.

methodsA systematic search of relevant published literature was conducted to collect relevant retrospective cohort studies that compared the teaching efficiency of MOOCs and Traditional Courses.

resultsThere are three retrospective cohort studies included in the final meta-analysis. There were no significant differences in the passing rates of MOOCs and Traditional Courses.

conclusionsit is necessary for universities to invest in online education to promote the development of MOOCs, which will probably have an advantage over Traditional Courses for postgraduate medical education in the near future.

Indexed as

Massive Open Online Course (MOOC)Medicine Educationmeta-analysisTraditional Course

Identifiers

PMID30603646
PMCPMC6312816

What OpenQuestion holds

Textmetadata
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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.