Evidence map›Paper›PMID 38429769›Full record

ArticleBMC psychology2024

Chinese English language learners' vocabulary retention: Investigating the effectiveness of neuro/metacognitive and socio-cultural strategies.

Wei Hu, Yipeng Luo

RetractedAbstract readRetracted Publication
In one paragraph

Article in BMC psychology, 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 It has been retracted, and should not be counted.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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Wei HuSchool of Foreign Language, Hunan University of Science and Engineering, 425199, Yongzhou, Hunan, China. weihu4890@outlook.com.
Yipeng LuoSchool of Information Science and Engineering, Hunan Women& apos; University, 410004, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe acquisition of a rich vocabulary is foundational to language proficiency. In the pedagogical pursuit of effective vocabulary teaching, educators explore diverse methodologies. Researchers investigated the impact of different neurocognitive, metacognitive, and socio-cultural strategies on enhancing vocabulary learning, particularly among Chinese English Language Learners.

objectivesThe study aims to determine the effectiveness of techniques derived from these theories compared to traditional teaching methods in enhancing vocabulary recall and recognition among English language learners. METHODOLOGY: A quasi-experimental pre-test/post-test design was employed for the experimental and control groups, comprising 90 Chinese EFL learners selected from educational institutions in 2022-2023. The experimental group (n = 45) received instruction involving visual imagery, multisensory rotation, circle rotation, and mind mapping over eight sessions, while the control group (n = 45) received traditional teaching methods.

findingsStatistical analysis, utilizing covariance and analysis of variance with SPSS software version 22, revealed significant improvements in recall and vocabulary recognition within and between the experimental and control groups.

conclusionsThe results indicate that incorporating techniques based on Neuro-Cognitive, Multimedia, Socio-Cultural, and Metacognitive theories positively influences vocabulary recall and recognition. This suggests the efficacy of these innovative methods in enhancing English language learning, highlighting their potential for broader integration into EFL instruction.

Indexed as

MultilingualismVocabularyChinaHumansLanguageLearningChinese English Language LearnersMetacognitive strategiesNeurocognitive strategiesSocio-Cultural strategiesVocabulary learning

Identifiers

PMID38429769
PMCPMC10908038

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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.