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Predictive Analysis of College Students' Creative Self-Efficacy Based on Decision Tree Modeling.
Minyue Hong1, Xueli Wan2, Leixiao Fu3
1Faculty of Arts and Social Sciences, University of Malaya; hmy.lexi@outlook.com.
Journal of Visualized Experiments : Jove
|August 25, 2025
Summary
This study used a decision tree model to predict creative self-efficacy in college students. Psychological trust, school membership, academic self-efficacy, and innovative behavior were identified as key predictors.
Area of Science:
- Psychology
- Educational Psychology
- Data Science in Social Sciences
Background:
- Creativity is a key area in psychological research.
- Understanding college students' self-perception of creativity is crucial for development.
- Limited research exists on predicting creative self-efficacy (CSE) in this demographic using computational models.
Purpose of the Study:
- To evaluate a modified C5.0 decision tree model for predicting CSE in college students.
- To identify significant predictors of CSE among college students.
- To enhance understanding and support for college student creativity.
Main Methods:
- A modified C5.0 decision tree model (DTM) was developed.
- 607 college students completed the Strengths and Difficulties Questionnaire (SDQ) with sub-scales for psychological resilience, academic self-efficacy, school membership, innovative behavior, and CSE.
- The DTM was trained, cross-validated, and evaluated using accuracy and F1-score.
Main Results:
- The revised C5.0 DTM effectively predicted CSE.
- Key predictors of CSE, in order of importance, were psychological trust, psychological sense of school membership, academic self-efficacy, and innovative behavior.
- The model demonstrated a 10-fold improvement after cross-validation.
Conclusions:
- The decision tree model proves effective for predicting college students' creative self-efficacy.
- Identified predictors offer insights into factors influencing CSE.
- This research supports interventions to enhance creativity and CSE in higher education.
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