Developing Management Model of Student Servant Leadership at Hubei Engineering University, China
Bibliographic record
Abstract
This study aimed to: 1) examine the components of student servant leadership, 2) assess the current status and expectations for developing student servant leadership, and 3) design and validate a management model to enhance student servant leadership. A three-phase Research and Development (R&D) design was adopted. The sample included 306 students from Hubei Engineering University, selected via stratified random sampling. Data collection involved document analysis, theoretical frameworks, a 5-level scale questionnaire, and focus groups. Statistical analyses included frequency, percentage, mean, standard deviation, and PNI Modified. Key findings revealed that student servant leadership comprises Selfless Love, Humility, Trust, Empowerment, and Vision. The management model includes five components: Planning, Implementation, Controlling, Evaluation, and Optimizing. Regarding objective 2, the current status of all components was low, while expectations were high. The needs assessment prioritized Evaluation with key factors “University support for leadership goals” (PNImodified = 0.98). Controlling followed, with factors “Regular feedback collection” (PNImodified = 0.95). Optimizing focuses on innovation, “Introduction of new teaching methods” (PNImodified = 0.91). Planning is foundational, “Clarity of long-term planning” (PNImodified = 0.69). Implementation centers on execution, with “Use of diverse teaching methods” (PNImodified = 0.78). For objective 3, the management model demonstrated strong validation: expert ratings averaged >4.5/5, with CFI = 0.996 and RMSEA = 0.016, indicating excellent fit. Discriminant validity was confirmed across all components, with AVE values above 0.66 and CR values above 0.90. This study provides a validated framework for developing student servant leadership through targeted management strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".