Factors influencing the college students’ effectiveness in discipline competitions
An integrated analysis from SEM and FsQCA
Bibliographic Data
| ID | 15699583 |
|---|---|
| Authors | Maoyan She (0000-0001-7133-4073, Chengdu University of Information Technology), Dengzhou Zeren (Sichuan University, corresponding author), Zexi Zhang (Chengdu University of Information Technology), Yuqiu Wang (0000-0002-2790-4689, Chengdu University of Technology) |
| Year | 2026 |
| Volume | 14 |
| Issue | 1 |
| Publication date | 2026-02-17 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Psychology (JOURNAL) |
| Journal identifiers | ISSN: 2050-7283 • E-ISSN: 2050-7283 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s40359-026-04162-9 |
| PMID | 41703641 |
| OpenAlex | W7129405948 |
| Language | EN |
| References cited | 66 |
Discipline competitions play an important role in higher education, as they drive innovation. Despite recognition of their educational value, little is known about the psychological mechanisms that determine students’ efficacy in these settings. The relationship between internal cognitive effects and outside help needs further study. This study developed the model based on an extended Unified Theory of Acceptance and Use of Technology 2 framework with self-efficacy theory. Perceived instructor support and self-efficacy were included in the model as key predictors. An online questionnaire was administered to 506 Chinese university students with competition experience. The model was tested using Covariance-Based Structural Equation Modeling. Fuzzy-set Qualitative Comparative Analysis was used to identify pathways within the complex set of causes leading to high effectiveness. The results of the CB-SEM analysis indicate that performance expectancy, effort expectancy, social influence, and facilitating conditions significantly enhanced competition intention. In addition, competition intention had a strong positive impact on competition effectiveness (β = 0.429, p < 0.001). Self-efficacy and perceived instructor support also proved direct, significant positive predictors of effectiveness (β = 0.227, p < 0.001; β = 0.131, p = 0.013). The fsQCA revealed three distinct yet equal paths to high effectiveness: the Motivation-Support pathway, the Social-Driven pathway, and the Resource-Guided pathway. As per the findings, competition intention acts as a mediator for self-efficacy, which is a vital resource of the mind. Their results show that effectiveness is not the product of one variable, but rather specific combinations of motivational, social, and resource-based conditions. This research offers a sophisticated psychological understanding of competitive performance outcomes based on evidence from successful competitors. Its completion has implications for educators to tailor mechanisms of support and develops agency. Competitors, the bid team, and their tailor have implications for a wide range of students
Cognition · Competition (biology · Product (mathematics · Qualitative comparative analysis · Resource (disambiguation · Set (abstract data type · Social cognitive theory · Structural equation modeling · Competency Development and Evaluation · Management and Marketing Education · Qualitative Comparative Analysis Research
Redesigning Social Inquiry
Social Support Measurement and Intervention
Unified Theory of Acceptance and Use of Technology
The influence of academic self-efficacy on academic performance
Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model
Perceived teacher support, student engagement, and academic achievement
Dynamic Interaction between Student Learning Behaviour and Learning Environment
Cutoff criteria for fit indexes in covariance structure analysis
User Acceptance of Information Technology
Consumer Acceptance and Use of Information Technology
An Index of Factorial Simplicity
Technology Acceptance Model 3 and a Research Agenda on Interventions
Unveiling factors affecting college students’ online self-directed learning
Technology adoption in a hybrid learning environment
The influence of intrinsic motivation and contextual factors on Mooc students’ social entrepreneurial intentions
Roles of computer agents in digital games
Set-Theoretic Methods for the Social Sciences
Confidence Limits for the Indirect Effect
Impact of Organizational Support on Students’ Information and Communication Technology Self-Efficacy, Engagement, and Satisfaction in a Blended Learning Environment
Students’ perception of teachers’ two-way feedback interactions that impact learning
Why so serious? Gamification impact in the acceptance of mobile banking services
Drivers of generative AI adoption in higher education through the lens of the Theory of Planned Behaviour
Activating Patients for Smoking Cessation Through Physician Autonomy Support
Stress, social support, and the buffering hypothesis
Teacher Autonomy Support Influence on Online Learning Engagement
The Effects of Blended Learning Environment on College Students' Learning Effectiveness
Factors Influencing the Acceptance of ChatGPT in High Education
| Citation velocity | historical |
|---|---|
| Highly cited | No |