Does design thinking training increase creativity? Results from a field experiment with middle-school students

Fatores críticos de sucesso em inovação de serviços por meio do Design Thinking

O serviço possui papel de protagonista no contexto mercadológico atual. Para manter este destaque, o foco em inovação e sucesso são pontos essenciais para o desenvolvimento dos serviços. O design thinking surge como uma estrutura para aperfeiçoar os serviços e promover a inovação. Porém, faz-se necessário verificar o sucesso que essa metodologia proporciona aos serviços. Sendo assim, esta pesquisa buscou avaliar quais são os fatores críticos de sucesso presentes em casos de desenvolvimento de serviços que utilizaram a metodologia do design thinking. Treze fatores críticos de sucesso foram avaliados por meio da técnica de análise de conteúdo em vinte quatro casos de desenvolvimento de serviços que usaram a metodologia do design thinking. Como resultado, foi verificada a presença de todos os fatores críticos nos casos, reforçando a grande orientação para sucesso que o design thinking possui em inovação de serviços. Destaca-se ainda o foco nas necessidades de mercado, a utilização de recursos tecnológicos e a orientação para gestão de projetos como os principais fatores. Esta pesquisa contribuiu para o âmbito prático da inovação em serviços, tendo como limitações a definição de outros fatores críticos de sucessos não abarcados na teoria e casos não analisados de outras consultorias.

Factors Influencing the Creativity of Chinese Upper-Secondary-School Students Participating in Programming Education

Purpose: This study explored whether instructional characteristics, learner characteristics, family socioeconomic status, and gender influence creativity in the context of programming education in China. Methods: A total of 851 upper-secondary-school students in Beijing, China, were surveyed using the Creativity Scale, Programming Learning Scale, Programming Teaching Scale and Family Socioeconomic Status Questionnaire. SPSS (version 22) was used for correlation analysis, t-test and regression analysis. Results: (1) Teachers' programming teaching method and management; students' programming learning approach, attitude, and engagement; gender; and family economic capital were all significantly associated with creativity. (2) There were significant differences between males and females in terms of creativity, programming learning approach and programming learning attitude. (3) Learner attitudes, engagement, and approach, and their family economic capital, were strong predictors of creativity, with the strongest influence of learners' attitudes to programming learning and weaker influence of family economic capital. Conclusion: The main factors that influence creativity in the context of programming education are programming teaching method, programming teaching management, programming learning approach, programming learning attitude, programming learning engagement and family economic capital. Among these, learner factors (attitude, engagement, and approach) and family economic capital are the key factors influencing creativity. These findings provide a basis for improving the creativity of Chinese programming learners and inspire teachers to consider learner factors and gender differences as they design and manage their instruction. Furthermore, the influence of family economic capital on the creativity of learners cannot be ignored.

Design Training and Creativity: Students Develop Stronger Divergent but Not Convergent Thinking

Design training programs that teach creativity often emphasize divergent thinking (generation of ideas) more than convergent thinking (evaluation of ideas). We hypothesized that training would lead to more both types of creativity, but especially divergent thinking. Three groups of university students (N=120; n=40 in each group) were recruited to participate: senior design students (graduate students with at least 4years of design training as undergraduates); junior design students (undergraduates in their first year of design training); and undergraduate students in majors unrelated to design. The students completed three tasks in a classroom setting to assess divergent thinking (Alternate Uses Task), convergent thinking (Remote Associates Task), and nonverbal abstract reasoning (Raven's Progressive Matrices Test). The results of one-way ANOVAs showed that as expected, senior design students significantly outperformed junior design students and non-design majors in divergent thinking. However, contrary to expectations, senior design students had significantly lower scores than the non-design group on convergent thinking; the junior design students' scores fell in the middle but were not significantly different from either of the other groups. There were no group differences in nonverbal abstract reasoning. These findings suggest that design training significantly improves students' ability to generate ideas but does not improve, or may even hinder, their ability to evaluate whether the ideas are useful for the task at hand. The results have implications for developing a research-based curriculum in design training programs.