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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