Technology to the Rescue: The Rise of Divergent Thinking Tests

SparcIt
SparcIt Blog
Published in
4 min readSep 14, 2016

Creativity is thinking up new things. Innovation is doing new things. The relationship between the two is clear: Innovation is the practical application of creativity. Both are necessary for business to succeed and grow. Ever since J.P Guilford and Paul Torrance pioneered the studies in 1950s, one’s creative potentials have been associated with Divergent Thinking abilities — the process or method used to create many unique ideas in order to solve a problem.

As discussed in one of the previous posts, divergent thinkers can think outside-of-the-box and find unordinary solutions. To measure one’s creative abilities, open-ended stimuli need to be administered and graded. It is extremely costly and time-consuming to grade divergent thinking stimuli. Hence (as discussed in previous post), they are not as widely used in recruiting or training employees.

Due to inefficiencies in grading divergent thinking assessments, such tests are not as widely used.

Technology is changing the assessments. With advancements in machine learning, deep learning, data mining and natural language processing, we are seeing new opportunities in administering open-ended assessments in both high-stake and low-stake settings.

With advancements in technology, we are seeing the rise of creative thinking assessments and its incorporation within the organizations’ recruiting and training processes.

SparcIt has applied techniques in machine learning, data mining and natural language processing to develop a novel methodology for grading unstructured responses in divergent thinking assessments. Using such techniques, the participants are given open-ended stimuli where they are asked to generate various ways of solving a problem using their own words. Then the engine parses the participants’ responses, clusterize and categorize them as needed and determines each solutions’ novelty. Next, the four dimensions of divergent thinking methodology is generated.

Over the last year, SparcIt has performed over 50,000 divergent thinking assessments.

SparcIt uses machine learning, data mining to scoring open-ended unstructured responses. We use techniques in dimension-reduction to crunch structured and unstructured data. We have created one giant data reservoir where all words and phrases are interlinked with each other. An algorithmic assessment applies statistical models to participants’ responses to predict the likelihood of important business outcomes (e.g., innovativeness, implementation). By using machine learning in the algorithm development process, predictive features can be discovered through a process that mirrors what recruiters and hiring managers try to do when they look at a candidate’s background — but without the element of human bias.

Funded by NSF, SparcIt took the research-based approach in designing an automated Watson-like engine.

Funded by National Science Foundation (NSF), SparcIt’s scientists took the research approach in validating the work. In one of our recent peer-reviewed study, the team proves that one’s divergent thinking abilities can be measured and graded via an automated engine. The engine is as accurate as human graders. It is however faster and less expensive. The table below shows the correlation between the engine and human graders. As shown, the correlations between human-grader and the engine is high.

Note: Table has been obtained from this study.

With grading automation of divergent thinking assessments, such assessments can be given to entry-level employees to senior-level managers.

In order to accurately measure one’s divergent thinking abilities, one must be given a set of open-ended stimuli, scenarios and exercises. Furthermore, the responses must be graded efficiently for a large group of participants. One of the well-researched and well-known assessments is SparcIt’s Creative Thinking assessment. Unlike traditional assessment, SparcIt’s unique feature is the use of open-ended exercises and automated scoring. Using a Watson-like engine, SparcIt’s patent-pending engine, accurately and efficiently grades the participants’ responses and provide a detailed report to the participants and the test administrators. Hence, it eliminates the major factors for not using such assessments.

SparcIt’s Creative Thinking assessment is fun, fast, automated, affordable and scalable.

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SparcIt
SparcIt Blog

Technology company with focus on developing the future of the workforce