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Advances in Social Sciences Research Journal – Vol. 12, No. 2

Publication Date: February 25, 2025

DOI:10.14738/assrj.122.18280.

Chen, K.-Y., & Chang, J.-C. (2025). Using CIPP Model Evaluation Data to Drive School Innovation Management: A Case Study of

Technical Senior High School in Taiwan. Advances in Social Sciences Research Journal, 12(2). 126-143.

Services for Science and Education – United Kingdom

Using CIPP Model Evaluation Data to Drive School Innovation

Management: A Case Study of Technical Senior High School in

Taiwan

Kun-Yi Chen

ORCID: 0009-0008-0888-8717

National Lo-Tung Commercial Vocational High School, No. 360,

Sec. 4, Zhongshan Rd., Luodong Town, Yilan County 265, Taiwan

Jen-Chia Chang

ORCID: 0000-0002-7082-6022

Graduate Institute of Technological and Vocational Education,

National Taipei University of Technology No. 1, Sec. 3,

Zhongxiao East Rd., Taipei City 10608, Taiwan

ABSTRACT

Despite the growing importance of evaluation in educational management,

technical high schools often struggle to effectively utilize evaluation data for

innovation. This study examines how evaluation data influence the innovative

management of technical high schools using the CIPP model (Context, Input,

Process, Product). Employing a qualitative case study approach, this research

integrates document analysis, field interviews, and observations to explore how

schools leverage evaluation data for educational decision-making, resource

allocation, and curriculum reform. Findings indicate that evaluation mechanisms

play a crucial role in optimizing faculty development, strengthening industry- academia collaboration, and enhancing data-driven decision-making. Technical

high schools that effectively apply evaluation data demonstrate improvements in

student advancement rates, skills competition performance, and graduate

employability. However, challenges persist, including the limited adaptability of

evaluation frameworks tailored primarily for academic high schools, as well as the

insufficient capacity of administrators and teachers to interpret and utilize

evaluation results. To address these issues, this study suggests implementing a

PDCA (Plan-Do-Check-Act) cycle to refine policy adjustments and strengthen data- driven decision-making processes. Furthermore, expanding external collaboration

networks and adopting international evaluation practices can enhance school

adaptability and competitiveness. Rather than being merely a performance

monitoring tool, evaluation should serve as a key driver for continuous school

innovation and sustainable development.

Keywords: technical high schools, educational evaluation, CIPP model, innovation, data- driven decision-making, PDCA cycle.

INTRODUCTION

Research Background

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127

Chen, K.-Y., & Chang, J.-C. (2025). Using CIPP Model Evaluation Data to Drive School Innovation Management: A Case Study of Technical Senior High

School in Taiwan. Advances in Social Sciences Research Journal, 12(2). 126-143.

URL: http://dx.doi.org/10.14738/assrj.122.18280

In the face of globalization and rapid technological advancements, technical high schools must

continuously innovate to remain competitive. However, the application of evaluation data in

driving school improvement remains a major challenge. While school evaluation is widely

implemented, its effectiveness in informing strategic decision-making and fostering innovation

is often limited. Many technical high schools struggle to translate evaluation results into

actionable insights due to rigid evaluation frameworks, resource constraints, and a lack of data

literacy among administrators and educators. This raises a critical question: How can technical

high schools effectively utilize evaluation data to enhance educational quality and institutional

sustainability?

Educational Challenges Under Globalization and Declining Birth Rates:

Given the urgent need for technical high schools to leverage evaluation data for innovation, it

is crucial to examine the broader educational challenges they face. Globalization has driven

industrial upgrading and technological innovation, leading to a growing demand for skilled

professionals. However, Taiwan's declining birth rate has intensified challenges in school

enrollment and management, particularly for technical high schools, which serve as key

institutions for vocational education and skill development. The continuous decline in the

school-age population has placed unprecedented pressure on technical high schools regarding

enrollment stability, resource allocation, and educational effectiveness. According to the latest

population statistics released by the Ministry of the Interior (2025) [1], Taiwan recorded a

historic low in newborns in 2023, indicating that demographic shifts are directly affecting the

sustainability of technical high schools. Under these circumstances, technical high schools must

maintain competitiveness despite limited resources to ensure high-quality education and

equitable learning opportunities for students. Educational evaluation has been recognized as a

crucial mechanism for improving education quality, allowing schools to assess their

management models, teaching effectiveness, and resource allocation in response to

development needs [2]. Moreover, innovative management strategies enable schools to adapt

to changes and strengthen their competitive advantages. Tan (2024) emphasized that effective

management strategies can enhance schools' responsiveness to market demands, ensuring

their continued development in a dynamic environment [3]. Innovation in technical high school

management extends beyond teaching and administrative adjustments; it also involves

leadership and strategic management, fostering an open learning culture to enhance school

competitiveness. Therefore, educational evaluation should not be merely a monitoring tool but

should serve as a strategic driver for continuous improvement and innovation in technical high

schools. This study explores how evaluation mechanisms influence the management and

educational quality of technical high schools and analyzes their practical value in school

development.

The Necessity of Educational Evaluation for School Innovation and Management:

Despite the pivotal role TSHSs play in developing skilled workers, they continue to face multiple

challenges in practice. First, the use of evaluation data remains suboptimal: although schools

collect large volumes of administrative data, they often struggle to convert these data into

concrete decisions, leading to subpar resource distribution and directional planning. Second,

insufficient integration of internal and external resources hampers cooperation with industry

and community partners, limiting the sharing of educational resources and broader

collaborative development [2]. Moreover, gaps persist between school policy and industry

needs, undermining TSHSs’ evolution. If policy cannot be aligned with the unique requirements

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Advances in Social Sciences Research Journal (ASSRJ) Vol. 12, Issue 02, February-2025

Services for Science and Education – United Kingdom

of technical–vocational education, it becomes difficult to leverage evaluation data for effective

reforms. In this context, understanding how school evaluation can facilitate cross-department

and cross-organizational resource integration is crucial for enhancing school operations and

driving educational reforms [7]. An effective evaluation system must align with the institution’s

governance structure, using evaluation indicators not just for performance monitoring but also

as a basis for strategy adjustments. This alignment ensures that administrative and teaching

staff can make evidence-based decisions [8]. By refining administrative efficiency, promoting

industry–academia collaboration, and enhancing students’ career competencies, a robust

evaluation mechanism helps TSHSs manage resources effectively and achieve dual aims:

organizational innovation and sustainable development.

Existing Challenges and Research Motivation:

Despite the pivotal role TSHSs play in developing skilled workers, they continue to face multiple

challenges in practice. First, the use of evaluation data remains suboptimal: although schools

collect large volumes of administrative data, they often struggle to convert these data into

concrete decisions, leading to subpar resource distribution and directional planning. Second,

insufficient integration of internal and external resources hampers cooperation with industry

and community partners, limiting the sharing of educational resources and broader

collaborative development [2]. Moreover, gaps persist between school policy and industry

needs, undermining TSHSs’ evolution. If policy cannot be aligned with the unique requirements

of technical–vocational education, it becomes difficult to leverage evaluation data for effective

reforms. In this context, understanding how school evaluation can facilitate cross-department

and cross-organizational resource integration is crucial for enhancing school operations and

driving educational reforms [7]. An effective evaluation system must align with the institution’s

governance structure, using evaluation indicators not just for performance monitoring but also

as a basis for strategy adjustments. This alignment ensures that administrative and teaching

staff can make evidence-based decisions [8]. By refining administrative efficiency, promoting

industry–academia collaboration, and enhancing students’ career competencies, a robust

evaluation mechanism helps TSHSs manage resources effectively and achieve dual aims:

organizational innovation and sustainable development.

The Value of Applying Evaluation Data:

In recent years, data-driven educational decision-making has gained significant attention. By

integrating evaluation data, schools can better assess institutional performance and quickly

identify areas for improvement [9]. When principals and school teams receive real-time

feedback from evaluation results, they can dynamically adjust resource allocation and

curriculum structures to enhance school performance. Furthermore, evaluation data fosters

teaching innovation, helping schools identify gaps in subject development, teaching

inefficiencies, and administrative bottlenecks. By incorporating emerging technologies and

industry case studies, schools can enhance students' employability [6]. An effective evaluation

framework should integrate both quantitative data analysis and qualitative inquiry, ensuring

its practical application in educational decision-making [10, 11]. By combining quantitative and

qualitative evaluation methods, schools can develop more precise strategies to maximize the

value of evaluation mechanisms. For technical high schools, evaluation data can also be

leveraged to optimize internship programs and career counseling, bridging the gap between

education and industry needs. This approach enhances students’ workplace adaptability and

contributes to the long-term sustainability of technical education. Additionally, evaluation data