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The traditional perspective on evaluation has historically been rooted in the theory of unitary intelligence, which posits that intelligence is a singular ability centered around linguistic and logical-mathematical skills (Ochigame, 2021). This concept has shaped educational assessment practices, emphasizing scientific, quantitative evaluation through testing scores, with college entrance exams serving as both the starting point and ultimate goal of education (De Los Reyes & Uddin, 2021; Zhong et al., 2023). Consequently, this approach tends to focus heavily on students' knowledge and logical-mathematical intelligence, often overlooking individual diversity and the role of evaluation in fostering student growth (Almuhur & Al-Labadi, 2022; Sharma, 2023).
However, societal and employer demands for well-rounded talent have shifted the paradigm. Vocational education plays a vital role in training skilled professionals and becomes a critical platform for enhancing overall qualities and implementing vocational training systems (Phakamach et al., 2023). As economic development transforms and workers' employability and job performance require boosting, vigorously advancing vocational colleges and cultivating skilled personnel become essential (Kayyali, 2024). Moreover, improving competitiveness, appeal, and influence, and achieving sustainable development are necessary steps for vocational institutions in today's context (Zhang & Zhao, 2023).
Advancements in cognitive theories and brain science have led to a more nuanced understanding of human intelligence, recognizing its multifaceted nature beyond the traditional emphasis on left-brain development (Chan & Luo, 2021). Multiple intelligences (MI) theory offers a framework for positive and equitable assessments tailored to students' distinct intellectual orientations, ensuring self-affirmation and recognition of diverse talents (Shearer, 2020). MI theory supports developmental evaluations by identifying and nurturing students' interests and potentials across various domains, thus providing a theoretical foundation for measuring academic achievement and inspiring curriculum reform (Rajaram, 2023).
According to MI theory, students possess a unique combination of intelligences—linguistic, logical-mathematical, spatial, bodily-kinesthetic, musical, interpersonal, intrapersonal, and naturalist—that form the cornerstone of comprehensive development (Cavas & Cavas, 2020). Therefore, student evaluation should encompass a broader range of criteria, assessing multiple angles and dimensions such as moral conduct, interpersonal relationships, learning aptitude, and personal interests alongside knowledge acquisition (Aguayo et al., 2021). Teaching strategies should stimulate these MI to promote comprehensive development, incorporating activities like project-based learning, group collaboration, and situational simulations, which enhance cognitive abilities, social adaptability, innovation, and critical thinking (Oktarina et al., 2021).
This paper evaluates the impact of integrating MI theory into vocational education, specifically examining how it can transform evaluation systems to better support comprehensive student development. By introducing MI theory as a robust framework, the paper proposes practical strategies for designing inclusive and holistic evaluation systems that recognize and nurture diverse talents. Case studies illustrate real-world implementations, offering valuable insights for educators and policymakers. Finally, concrete policy recommendations are provided to support vocational colleges and educational institutions in adopting MI-based practices, ultimately aiming to foster well-rounded, skilled professionals.
Through these contributions, the paper serves as a comprehensive guide for designing and implementing effective and equitable evaluation systems in vocational education, contributing to the development of high-quality talent. The study also explores specific challenges and outcomes, such as the difficulty in applying natural observation intelligence within the context of tennis instruction, providing deeper insights into the benefits and limitations of MI-based teaching models.