Education Technology
Research on the Construction of Evaluation Index System for Teaching Innovation Teams of Vocational College Teachers Based on CIPP Model
This study addresses evaluation challenges for teaching innovation teams in vocational colleges by integrating the CIPP evaluation model with Delphi and Analytic Hierarchy Process. It constructs a comprehensive system of 4 primary, 14 secondary, and 40 tertiary indicators to provide a scientific framework for assessing teacher innovation ability across planning, practice, achievements, and characteristic innovation.
Executive Impact: Quantifying AI's Role in Education Excellence
Our AI-powered analysis reveals how structured evaluation, like that proposed for vocational teaching teams, drives measurable improvements in educational innovation and teacher development. By leveraging data-driven insights, organizations can optimize strategies for human capital development and institutional effectiveness.
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Refined Evaluation Metrics
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Minimum Expert Consensus
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CIPP Framework Dimensions
Deep Analysis & Enterprise Applications
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Integrated Evaluation Framework
This research meticulously combined the CIPP evaluation model (Context, Input, Process, Product) with the Delphi method for expert consensus and the Analytic Hierarchy Process (AHP) for systematic weight allocation. This multi-pronged approach ensures a robust, quantitative, and expert-validated evaluation system.
Enterprise Process Flow
CIPP Model Integration
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Delphi for Preliminary Selection
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AHP for Weight Calculation
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Final Index System Definition
Rigorous Indicator Validation
Indicators underwent a stringent validation process using a Likert scale survey with statistical analysis (median, mean, coefficient of variation, interquartile range) and consensus level checks. This ensured only highly relevant and agreed-upon indicators were retained.
| Validation Aspect | Initial Screening | Delphi & AHP Refinement |
|---|---|---|
| Indicator Scope | Broad categories, existing standards | Specific, measurable elements aligned with CIPP |
| Validation Method | Literature review & expert input | Likert scale survey with statistical analysis (SPSS) |
| Consistency Metric | Qualitative expert grouping | Median ≥ 4, IQR ≤ 0.5, Cumulative Freq. ≥ 51% |
| Expert Feedback Rounds | Initial expert opinions | Multi-round anonymous inquiry (Delphi) |
| Outcome | Preliminary 42 tertiary indicators identified | Final 40 validated and refined tertiary indicators |
Strategic Weight Allocation
The Analytic Hierarchy Process (AHP) was used to assign scientific weights to each indicator, reflecting their relative importance. This quantitative approach allows for a balanced and objective evaluation, prioritizing key areas such as "Practice and Reform".
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Primary Indicator Weight: Practice and Reform (C2)
This high weighting indicates the critical importance placed on the actual implementation of innovative teaching methods and continuous development within the vocational education context.
Calculate Your Potential ROI
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Estimated Annual Savings
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Your AI-Powered Implementation Roadmap
A structured approach to integrating advanced evaluation and development frameworks into your organization for sustained innovation.
Phase 1: Discovery & Assessment
Conduct a comprehensive audit of existing evaluation processes and innovation initiatives. Identify key stakeholders, current challenges, and strategic objectives for teacher development teams.
Phase 2: Framework Customization
Tailor the CIPP-based evaluation index system to your institution's specific context, culture, and goals. Define KPIs and integrate AI tools for data collection and initial analysis.
Phase 3: Pilot Implementation & Feedback
Launch a pilot program with selected teaching innovation teams. Gather continuous feedback, refine indicators, and adjust the evaluation methodology based on real-world application and expert insights.
Phase 4: Full-Scale Deployment & Training
Roll out the refined evaluation system across all relevant teams. Provide extensive training for team leaders and members on data interpretation, performance monitoring, and leveraging AI for continuous improvement.
Phase 5: Continuous Optimization & Scalability
Establish a cycle of ongoing evaluation, performance review, and system enhancement. Explore opportunities to scale the framework to other departments and integrate with broader institutional strategic planning.
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