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Torrance Test of Creative Testing (TTCT)

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Torrance Test of Creative Testing, TTCT

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The App GenerationPerhaps the most widely used creativity test is the Torrance Test of Creative Thinking (TTCT). Developed in 1966 and currently used worldwide, the TTCT measures several dimensions of creative potential, including intellectual curiosity, open-mindedness, verbal expressiveness, and originality. Though not without its critics, the TTCT has been found to predict creative achievement better than other standard measures of creative or divergent thinking.7 Empirical evidence suggests that high scores on the test successfully predict subsequent creative careers and accomplishments.8
Von Howard Gardner, Katie Davis im Buch The App Generation (2013)
The TTCT offers a suite of authentic activities that prompt the test-taker to engage in various types of thinking that mirror the kinds of creativity required for real-life and daily human operations, including asking questions, guessing causes and consequences, improving a product, and utilizing imagination (STS, 2017). In total, the TTCT includes six distinct creative activities designed to evaluate the operation of creativity as it is often used in business and everyday life. In addition to a standard Alternative Uses Task (Unusual Uses), the TTCT also includes tasks to evaluate Asking Questions, Guessing Causes, Guessing Consequences, and Product Improvement.
Von Erik E. Guzik, Christian Byrge, Christian Gilde im Text The originality of machines (2023)

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The strength of the TTCT is its large database of historical human responses that can be used as a control and comparison group. This has become possible because of its consistency in using the same demographic makeup of test-tasker for decades and because responses have been systematically collected for scoring.
Von Erik E. Guzik, Christian Byrge, Christian Gilde im Text The originality of machines (2023)
The TTCT is a commercially protected assessment instrument, therefore prompts are not accessible to ChatGPT or any other AI system, or publicly available in general. This offers a unique opportunity to test ChatGPT using specific prompts that it likely has never been asked before. ChatGPT will have to generate the responses, not simply retrieve them from ist database.
Von Erik E. Guzik, Christian Byrge, Christian Gilde im Text The originality of machines (2023)
Current product-based measures like the TTCT also raise interesting questions about creativity assessment in general. For example, which human raters are capable of best measuring human creativity? And which of these raters are capable of measuring AI creativity? In addition, is a truly accurate and unbiased assessment of creativity and originality possible within current assessments? A study by Licuanan et al. (2007) found that participants preferred ideas of low originality when evaluating highly original ideas. They also found that ideas of high originality were discounted because raters lacked the knowledge for accurately recognizing the originality of these ideas.
Von Erik E. Guzik, Christian Byrge, Christian Gilde im Text The originality of machines (2023)
While the TTCT has long been considered a valid and reliable measure of creativity, the results of GPT-4 testing may simply highlight the limitations of existing creativity assessments. Although GPT-4 demonstrated high fluency, flexibility, and originality, assessments such as the TTCT may not fully capture the nuances and complexities of human creativity especially as related to person, process, and press—in this respect, current human scores on tests such as the TTCT may understate or incompletely measure human creativity. Further, the performance of GPT-4 could suggest that traditional creativity assessments need to be revised to differentiate between human and AI-generated creative outputs and evaluate other aspects of creativity beyond those currently assessed, including processes of convergent thinking.
Von Erik E. Guzik, Christian Byrge, Christian Gilde im Text The originality of machines (2023)

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