A Minimal Theory of Creative Ability

Entrepreneurs' creativity, information technology adoption, and continuance intention: Mediation effects of perceived usefulness and ease of use and the moderation effect of entrepreneurial orientation

Despite the potential of information technology (IT) to enhance business efficiency and productivity, many entrepreneurs still refuse to adopt it. Their low adoption rate of IT is often attributed to a lack of awareness of its potential benefits. Extending the technology acceptance model, this study aimed to investigate the effect of creativity mediated by perceived usefulness (PU) and perceived ease of use (PEOU) on the intention to adopt and continue using IT. Additionally, the study explores how entrepreneurial orientation (EO) functions as a contextual factor in the relationship between creativity, PU, and PEOU. In contrast to extant studies, EO is a better-suited variable for our study as it is more extensive. Data were collected through questionnaires distributed to individual entrepreneurial taxpayers registered in tax offices in the Special Region of Yogyakarta, Indonesia. The study employed not only a quasi-experimental method with coarsened exact matching to reduce the degree of model dependence, inefficiency, and bias but also a causal mediation analysis to explore the proposed relationships. The study focused on the adoption of DJP Online, an e-tax service provided by the Directorate General of Taxes as the Indonesian tax authority, and the e-marketplace. In contrast with the factors identified in extant studies, we explain that the variance in PU is attributed to a greater extent to creativity. Similarly, we find that creativity explains a larger portion of the variance in PEOU than that found in extant studies. Our findings thoroughly explain how creativity influences entrepreneurs' willingness to adopt and continue using new technologies. Other studies could employ a more diverse and representative sample to extend these findings.

Memory and creativity: A meta-analytic examination of the relationship between memory systems and creative cognition

Increasing evidence suggests that specific memory systems (e.g., semantic vs. episodic) may support specific creative thought processes. However, there are a number of inconsistencies in the literature regarding the strength, direction, and influence of different memory (semantic, episodic, working, and short-term) and creativity (divergent and convergent thinking) types, as well as the influence of external factors (age, stimuli modality) on this purported relationship. In this meta-analysis, we examined 525 correlations from 79 published studies and unpublished datasets, representing data from 12,846 individual participants. We found a small but significant (r = .19) correlation between memory and creative cognition. Among semantic, episodic, working, and short-term memory, all correlations were significant, but semantic memory - particularly verbal fluency, the ability to strategically retrieve information from long-term memory - was found to drive this relationship. Further, working memory capacity was found to be more strongly related to convergent than divergent creative thinking. We also found that within visual creativity, the relationship with visual memory was greater than that of verbal memory, but within verbal creativity, the relationship with verbal memory was greater than that of visual memory. Finally, the memory-creativity correlation was larger for children compared to young adults despite no impact of age on the overall effect size. These results yield three key conclusions: (1) semantic memory supports both verbal and nonverbal creative thinking, (2) working memory supports convergent creative thinking, and (3) the cognitive control of memory is central to performance on creative thinking tasks.

Divergent semantic integration (DSI): Extracting creativity from narratives with distributional semantic modeling

We developed a novel conceptualization of one component of creativity in narratives by integrating creativity theory and distributional semantics theory. We termed the new construct divergent semantic integration (DSI), defined as the extent to which a narrative connects divergent ideas. Across nine studies, 27 different narrative prompts, and over 3500 short narratives, we compared six models of DSI that varied in their computational architecture. The best-performing model employed Bidirectional Encoder Representations from Transformers (BERT), which generates context-dependent numerical representations of words (i.e., embeddings). BERT DSI scores demonstrated impressive predictive power, explaining up to 72% of the variance in human creativity ratings, even approaching human inter-rater reliability for some tasks. BERT DSI scores showed equivalently high predictive power for expert and nonexpert human ratings of creativity in narratives. Critically, DSI scores generalized across ethnicity and English language proficiency, including individuals identifying as Hispanic and L2 English speakers. The integration of creativity and distributional semantics theory has substantial potential to generate novel hypotheses about creativity and novel operationalizations of its underlying processes and components. To facilitate new discoveries across diverse disciplines, we provide a tutorial with code (osf.io/ath2s) on how to compute DSI and a web app ( osf.io/ath2s ) to freely retrieve DSI scores.

Scientific creativity and innovation ability and its determinants among medical postgraduate students in Fujian province of China: a cross sectional study

BACKGROUND

Graduate education is the main approach to training high-level innovative elites. With the expansion of the scale of graduate education in China, it has gradually emerged that the lack of innovation ability of graduate students is recognized as the primary problem in graduate education. How to comprehensively improve the quality of postgraduate teaching has become the core task of educational reform and development. However, data about the current cultivation and development of the innovative ability of graduate students in China is limited.

METHODS

A questionnaire survey was conducted among medical postgraduate students. Descriptive statistics and multiple regression analysis methods were used to analyze the data to describe the current innovation ability in advanced medical education and potential influence factors.

RESULTS

A total of 1241 medical students were surveyed, according to the results of questionnaire data analysis. The proportion of subjects who participated in the College Student's Entrepreneurship and Innovation program or any other scientific research programs are fairly high which are 46.82% and 29.20% respectively. Most of the participants are observed with high levels of self-motivation and active learning and have good performance in creative thinking. However, only a small number of participants (16.6%) reported academic achievements such as publications. Most of the students are satisfied with the current scientific research environment and think that the current postgraduate training system is qualified for the cultivation of innovation ability, and expects the inclusion of course specialized in systemic medicine and medical informatics in the curricula. Multiple logistic regression results showed that among the factors studied, gender, medical specialties, and types of master's degrees are associated with cognition & skills, academic performance, and creativity.

CONCLUSIONS

It will be important to incorporate more techniques for creating and improving creativity in the curricula of the current postgraduate education, especially for courses such as systemic medicine and informatics. Guidance in earlier school life can stimulate creativity and an early introduction to scientific research work will facilitate innovative thinking and behavior. Scientific research programs such as the National Innovation and Entrepreneurship Training for the universities of PRC have been widely implemented in the undergraduate education system throughout the country. However, the training effectiveness of the current scientific research programs is worth improving.

A Supervised Machine Learning Approach to Classify Brain Morphology of Professional Visual Artists versus Non-Artists

This study aimed to investigate whether there are structural differences in the brains of professional artists who received formal training in the visual arts and non-artists who did not have any formal training or professional experience in the visual arts, and whether these differences can be used to accurately classify individuals as being an artist or not. Previous research using functional MRI has suggested that general creativity involves a balance between the default mode network and the executive control network. However, it is not known whether there are structural differences between the brains of artists and non-artists. In this study, a machine learning method called Multi-Kernel Learning (MKL) was applied to gray matter images of 12 artists and 12 non-artists matched for age and gender. The results showed that the predictive model was able to correctly classify artists from non-artists with an accuracy of 79.17% (AUC 88%), and had the ability to predict new cases with an accuracy of 81.82%. The brain regions most important for this classification were the Heschl area, amygdala, cingulate, thalamus, and parts of the parietal and occipital lobes as well as the temporal pole. These regions may be related to the enhanced emotional and visuospatial abilities that professional artists possess compared to non-artists. Additionally, the reliability of this circuit was assessed using two different classifiers, which confirmed the findings. There was also a trend towards significance between the circuit and a measure of vividness of imagery, further supporting the idea that these brain regions may be related to the imagery abilities involved in the artistic process.