Evidence map›Paper›PMID 38667067›Full record

ArticleBehavioral sciences (Basel, Switzerland)2024

What Contributes to Student Language Learning Satisfaction and Achievement with Learning Management Systems?

Hanxue Li, Aohua Ni

Open access · goldAbstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2024. 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
10.5field-weighted citation impact, top 2% of its field
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, 5 citations in OpenAlex.

  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 at 2 institutions in 1 country.

Hanxue LiCollege of Education, Hunan First Normal University, Changsha 410205, China.
Aohua NiGraduate School of Education, Peking University, Beijing 100871, China.
Hunan First Normal University · CNPeking University · CN

Funding

National Social Science Foundation 20CSH042
6 · The paper itself

Abstract

Learning management systems (LMSs) have received substantial global attention and have undergone extensive research, with most discussions focusing on users' acceptance and continuation of LMS use in the higher education sector. However, research is scarce in terms of identifying the factors that are advantageous to K-12 students' learning and satisfaction when using LMSs for language learning. This study aims to examine the impacts of internal and contextual factors on secondary students' learning satisfaction and English achievement when using LMSs. Data were collected from 289 students through an online survey. The results of the structural equation modeling showed that satisfaction had the most significant impact on English achievement. Furthermore, both internal and contextual factors, including technology self-efficacy, interest, task value, teacher support, and technology facilitation, positively impacted learning satisfaction with LMSs. In addition, teacher support exerted the strongest impact on satisfaction, followed by interest and technology self-efficacy. However, only internal factors, such as interest and task value, were positively associated with English achievement. Neither teacher support nor technology facilitation significantly impacted English performance. Given the increasing availability of LMS usage, the findings of this study can facilitate the more effective implementation of LMSs in China and globally. The study contributes to the theory and practice of LMSs use in K-12 English education. The limitations and implications of the study were discussed as well.

Indexed as

achievemente-learningEnglish language learninglearning management systemlearning satisfactionsecondary education

Identifiers

PMID38667067
PMCPMC11047611
OpenAlexW4393164147

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.