Effects of game-based learning on academic outcomes: A study of technology acceptance and self-regulation in college students.

Fang Zhang

Abstract read

In one paragraph

Article in Heliyon, 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

–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.

Effects of a game-based learning ıntervention on self-reported learning strategies and professional attitudes in kinesiophobia management education: a parallel-group randomized controlled trial.BMC medical education · 2026
Trial

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

1 author.

Fang ZhangCenter of Smart Campus Construction, Central University of Finance and Economics, Beijing, 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study investigates the interplay between the Technology Acceptance Model (TAM), self-regulation strategies, and academic self-efficacy, and their collective impact on academic performance and perceived learning among college students engaged in remote education. Methods: A sample of 872 university students from Southern China participated in this study. Structural Equation Modeling (SEM) was employed to analyze the theoretical relationships among the variables. The research focused on two primary areas: the connection between academic self-efficacy and gameful self-regulation strategies within the framework of TAM, and the influence of TAM's three dimensions on students' perceived learning and academic performance. Results: Findings highlight self-efficacy and gameful self-regulation strategies, in enhancing technology acceptance. Improved acceptance of technology is shown to positively affect academic performance and the perceived learning experience of students in classes using game-based online resources. Conclusion: The study emphasizes the significance of self-efficacy and gameful self-regulation strategies in shaping students' perceptions and attitudes towards technology. These factors are found to be key determinants of both perceived learning and academic achievement in the context of game-based online resource classes.

Indexed as

Academic performanceAcademic self-efficacyGameful self-regulation strategiesGamificationTechnology acceptance model (TAM)

Identifiers

PMID39247299

DOI10.1016/j.heliyon.2024.e36249

PMCPMC11379982

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC

Read underepoch 390

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.