Evidence map›Paper›PMID 40282104›Full record

ArticleBehavioral sciences (Basel, Switzerland)2025

Dropout in Online Education: A Longitudinal Multilevel Analysis of Elementary Students' Extracurricular English Course Engagement in China.

Haotian Tan, Xueting Li

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2025. 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. Article
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

2 authors.

Haotian TanDepartment of Psychology, Renmin University of China, Beijing 100872, China.ORCID 0009-0006-2245-4953
Xueting LiDepartment of Psychology, Renmin University of China, Beijing 100872, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While high dropout rates hinder the success of online education, little is known about the patterns of dropout beyond adult education, particularly regarding time-related variables. This study aims to address this gap by analyzing data from 219 online extracurricular English courses, involving approximately 300,000 Chinese elementary students. We employed a multilevel modeling technique and found that the dropout rate increased throughout the semester and peaked at chapter transitions. Furthermore, we also found that the dropout rate varied with grades and semesters. Younger students and those in the second semester were more likely to drop out from online education and exhibited a higher dropout rate during chapter transitions. These findings highlight the temporal dynamics of dropout in elementary online education in China and the variations across grade and semester, providing valuable implications for educators in designing more effective online learning environments. Future studies should further explore the generalizability of these patterns in other educational and cultural contexts.

Indexed as

class-level dropoutcliff effecthierarchical linear modelonline elementary education

Identifiers

PMID40282104
PMCPMC12024346

What OpenQuestion holds

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Registered trials

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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.