빅데이터 기반 텍스톰 분석을 활용한 디자인 씽킹 동향분석

Abstract

Objectives This study aims to investigate the design thinking research trends in Korea and suggest future research directions. To achieve this purpose, a total of 337 papers related to design thinking published since 2000 were collected. Methods Based on the collected research papers, research trends were examined by year and journal status and research methods, and networks between keyword-related words were analyzed through Big Data analysis program Textom and Ucinet6 NetDraw functions. visualized. In addition, CONCOR analysis was performed to derive similar clusters of derived words. Results The study results are summarized as follows. First, design thinking research began in earnest in mid-2010, and the number of related studies has increased rapidly since then. became Among the 337 studies, quantitative research was the most prominent with 80.7%, followed by theoretical research (11.8%), mixed research (3.85%), and qualitative research (2.67%). Second, through keyword network analysis, the most used Key words were ‘creativity’, ‘convergence’, ‘problem solving’, ‘process’, ‘education’, and ‘learning’. In the cluster through Ucinet6 NetDraw, the defining keyword that refers to design thinking was the main group, and the need for interdisciplinary convergence and justification areas were gathered into the surrounding group. Conclusions The implication of this is that, although related studies are published every year, most studies are still microscopic and one-off program types are the main focus, so from a long-term perspective, reorganization of the curriculum is inevitable, and methodological reliability is required. As can be seen from the textom analysis, design thinking is emphasized in terms of creativity, convergence, and problem solving, and although there is a definition of design thinking in a broad sense, it is standardized in that the implementation method is different depending on the researcher's point of view. Attempts and follow-up studies are needed.