Journal of Research in Education Sciences (Jun 2024)
跨領域設計思考者特質量表之建構 Development of a Cross-Disciplinary Design Thinker Trait Scale
Abstract
本研究旨在建立一份跨領域設計思考者特質量表，並應用Rasch模式檢驗其心理計量特性，同時探討這些特質在不同背景變項下的關係。研究對象主要為大學生以上的成年人，包括預試樣本的208位受試者和正式樣本的529位受試者。這份量表共包含了八個向度的特質，分別為以人為本、同理心、整合思維、創意思維、動力心態、容忍不確定性與失敗、跨領域協作，以及原型製作與迭代實驗等向度，為五點量表，共計37題。為提供多元的效度證據，資料分析採用Rasch部分給分模式。研究結果顯示，八個向度皆具有良好的模式資料適配度，且大部分題目在性別上沒有明顯的差異試題功能（Differential Item Functioning, DIF），八個向度的信度介於.81至.86之間。在差異分析方面，結果顯示在性別、年級及舊經驗等背景變項下，部分向度的設計思考者特質有顯著差異。最後，本研究提供客觀的評量觀點，探討設計思考者特質、性別和年級之間的關係，並提出推動設計思考教育重要的基礎研究和實務應用價值的相關建議。 Background and Purpose The cultivation of interdisciplinary talent is a global trend, with design thinking emerging as a crucial approach to interdisciplinary learning (Mehalik & Schunn, 2006). However, challenges arise when the definition or process of design thinking varies across fields (Chesson, 2017), leading to difficulties in establishing consistent measurement tools for assessing design thinking. Currently, the analysis employed in the development of design thinking tools primarily relies on factor analysis, which often results in an unstable factor structure and relatively subjective measurements related to design thinking. The aim of this study was to develop a scale named the Cross-Disciplinary Design Thinker Trait Scale with sufficient reliability and validity. Specifically, experts in the field reexamined the traits of design thinkers based on the relevant literature, and similar concepts were integrated into a single dimension. The Rasch Partial Credit Model was applied to examine the developed scale’s psychometric properties, providing multiple forms of evidence to establish the scale’s reliability and validity. This tool is intended to support the assessment and enhancement of design thinking abilities in both educational and professional contexts. Literature Review Throughout the late 2010s and early 2020s, design thinking gained widespread recognition as a highly effective approach for fostering innovation and creativity within corporate and organizational contexts. This surge in the popularity of design thinking can be partially attributed to vigorous promotion by influential entities such as IDEO, a prominent design company based in the United States, and the d.school at Stanford University. As a practical approach, design thinking is considered capable of addressing complex problems and enhancing various aspects related to work culture, communication, innovation, and overall organizational success. As design thinking evolves into an interdisciplinary, human-centered approach to innovation, scholars have identified key factors for its success. With design thinking becoming increasingly central to future talent development in educational institutions and professional skill enhancement in workplaces, educators now face the challenge of effectively assessing teaching and learning outcomes. In this context, understanding learners’ inherent design thinking traits is essential. Empirical investigations into the definitions of design thinking and the traits of design thinkers have consistently highlighted several dimensions, including human-centeredness, empathy, integrative thinking, innovative thinking, a motivational mindset, tolerance for uncertainty and failure, interdisciplinary collaboration, prototyping, iteration, optimism, positive beliefs, visualization of ideas, problem solving, and a willingness to embrace risks. A review of existing scales related to design thinking reveals overlap in the trait components of design thinkers; however, a variety of factor structures emerge. This inconsistency arises from exploratory factor analyses being data driven and thus leading to the extraction of common factors based on correlations in respondents’ reactions to each item. Factor structure determination relies entirely on respondent reactions and thus overlooks the theoretical foundation of the measured constructs. Consequently, problems related to sample dependence may lead to inconsistent factor structures (Gorsuch, 1983). In other words, existing design thinking measurement tools have exhibited a degree of subjectivity in their development and analytical methods. The Rasch model in item response theory (Rasch, 1960) is regarded as effective for addressing problems related to test dependence and sample dependence because of its properties of item independence, sample independence, and equidistance. The Rasch model has been widely applied in various fields— including education, psychology, and health care (Wang, 2004)— a nd is particularly suitable for examining the psychometric properties of measurement scales. On the basis of these considerations, the primary objective of this study was to develop a reliable and valid scale named the Cross-Disciplinary Design Thinker Trait Scale. The Rasch model was employed to examine the psychometric properties of this scale and to validate the scale. Method This study focused on college students in Taiwan and recruited two samples: a pilot sample and a formal sample. The pilot sample, comprising 208 participants, was used to assess the quality of the Cross-Disciplinary Design Thinker Trait Scale’s items. The formal sample, comprising 529 college students, was utilized to examine the scale’s reliability and validity. Following the method of expert review and revision to examine item contents, the traits of design thinkers were categorized into eight dimensions: human-centeredness; empathy; integrative thinking; creative thinking; dynamic mindset; tolerance of ambiguity and failure; interdisciplinary collaboration; and prototyping, iteration, and experimentation. The scale consisted of 37 items, each rated on a 5-point Likert scale ranging from 0 (completely inconsistent) to 4 (completely consistent). ConQuest software (Wu et al., 2007) was used for all Rasch analyses. This study examined the Design Thinker Trait Scale’s reliability and validity to provide evidence of its content validity, structural validity, generalizability validity, interpretability validity, substantive validity, and external evidence validity (Wolfe & Smith, 2007). Results In the preliminary data analysis, the results indicated that most items demonstrated strong fit. The formal data analysis revealed that the aforementioned eight dimensions of design thinker traits exhibited strong model fit, providing evidence of content and structural validity. Regarding generalizability validity, most items on the Cross-Disciplinary Design Thinker Trait Scale retained consistent meaning in relation to students of different genders, except for one item in the empathy dimension, which revealed a significant difference in interpretation between male and female students. Furthermore, the person separation reliabilities of the eight dimensions were all appropriate, ranging from .81 to .87. The evidence regarding interpretative validity revealed that the level of design thinking traits among university students exceeded the difficulty of the test items in all eight dimensions, indicating a relatively high level of design thinking traits among the participants. Regarding evidence of substantive validity, each of the items measured on a 5-point Likert scale to assess students’ trait levels appeared suitable. Additionally, regarding external evidence validity, a significantly high correlation existed between the Cross-Disciplinary Design Thinker Trait Scale and the Creative Self-Efficacy Scale, suggesting that the Cross-Disciplinary Design Thinker Trait Scale demonstrated sufficient criterion-related validity. Discussion and Suggestions Regarding future scale application and development, given the correlation between organizational culture and the use of design thinking tools, researchers should investigate variations in design thinking trait tendencies across multiple disciplines (Elsbach & Stigliani, 2018). In education, integrating design thinking into curriculum design, teaching methodologies, and teacher training is recommended (Lor, 2017). Such integration could include planning strategies and learning materials responsive to the aforementioned eight traits of design thinking with a view to cultivating students’ abilities and fostering innovation and interdisciplinary competencies. In addition, schools should consider offering courses that inspire design thinking, enhance elective options, and encourage cross-disciplinary sharing among students to balance or amplify their potential for design thinking. Moreover, using the Cross-Disciplinary Design Thinker Trait Scale in teacher training could provide insights into students’ thought processes and facilitate the design of interdisciplinary collaborative learning experiences. Future efforts should involve more systematic investigations and comparisons of design thinking traits among Taiwanese students to contribute to a deeper understanding of such traits and to establish comprehensive links among curriculum, teaching, and assessment.
Keywords
