When faced with a challenging problem, we are often forced to choose between two cognitive strategies: stay focused on that problem until we arrive at an answer, or divert our attention elsewhere and return to the problem later. Malcolm Gladwell wrote Blink supporting the former strategy and intuition, while numerous famous creators such as Picasso, Poincare, and Cleese have all publicly noted the efficacy of skipping a problem and returning to it later.
In the classroom, students often encounter test problems that they cannot answer immediately. They then face the integral decision about what to do next. In this situation, some will argue for a ‘gut-feeling’ approach, implying that students should input an answer then and there. Others claim it is best to leave the problem and return to it later. Which of these techniques will further increase the likelihood of arriving at a correct answer?
There exists a substantial base of literature on incubation. When leaving a problem and returning to it later, incubation refers to the cognitive processes that occur in the meantime and assist in problem solving. This literature touches on mathematical, creative, and linguistic problem solving. Based on the literature, it seems evident that leaving explicitly and returning momentarily (or L.E.R.M.ing) assists problem solving across a wide domain of problem types, likely by harnessing the power of incubation.
Thus, I will argue that substantial evidence indicates that it is advantageous for students who are unsure of an answer to leave problems explicitly and return to them momentarily (or, to L.E.R.M), rather than to force an answer based on gut feeling. In my pilot study, I apply these findings for the first time to reading comprehension problems. I then conduct a study on anagrams to test incubation effects on solve rates as well as on persistence in seeking alternative answers on anagram puzzles.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/2wrj-b713 |
Date | January 2024 |
Creators | Lerman, Daniel |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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