Evidence map›Paper›PMID 41200061›Full record

ArticleFrontiers in psychology2025

Dynamic pathways to academic engagement in university students: a mixed-methods study on growth mindset, grit, and academic self-efficacy with ecological momentary assessment.

Haizhen Liang, Shimin Wu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

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

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

  1. Pooled it
  2. 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.

Haizhen LiangSchool of Literature and Media Communication, Lingnan Normal University, Zhanjiang, Guangdong, China.
Shimin WuDepartment of Mathematics, Zhanjiang Preschool Education College, Zhanjiang, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This mixed-methods study investigated the predictive influence of growth mindset, academic grit, and academic self-efficacy on the academic engagement of undergraduate students in mainland China. A key ancillary goal was to explore the real-time dynamics and psychological mechanisms underpinning these relationships. Methods: We surveyed 593 students from three diverse Chinese universities to assess the core constructs. The quantitative data were analyzed using Structural Equation Modeling (SEM). To provide qualitative depth, we conducted focus group interviews ( Results: The SEM analysis showed that both growth mindset and academic grit positively predicted academic self-efficacy and engagement. Importantly, academic self-efficacy was found to partially mediate these relationships. Qualitative findings corroborated the model, revealing three key themes: (a) embracing challenges as learning opportunities, (b) self-efficacy as a cornerstone for proactive engagement, and (c) the role of cultural factors in shaping motivation. The EMA diaries provided granular, Discussion: This study underscores the importance of fostering growth mindset, grit, and especially self-efficacy to enhance academic engagement among Chinese undergraduates. The findings highlight the value of a mixed-methods approach in developing a dynamic, culturally-grounded understanding of student motivation and point toward implications for creating culturally sensitive and moment-aware educational interventions.

Indexed as

academic engagementacademic gritacademic self-efficacyecological momentary assessment (EMA)growth mindsetmediationmixed-methodsreal-time dynamics

Identifiers

PMID41200061
PMCPMC12586190

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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.