No abstract

There are two common approaches to researching insight: the study of the emotional response to a solution (Aha! experience) and the study of the restructuring of representations. The relationship between them can be found by comparing functions they perform relative to each other. For the experimental investigation of insight, problems that are typically being used can be solved within a little amount of time and are highly similar in their structure. We believe that such laboratory designs of the tasks often lead to researchers missing out on the moments of impasse and initial restructuring of the search space. In the current study, using the method of multimodal corpora constructed from individual solutions, we gained partial confirmation of the key statements of the model of emotional regulation of the representational change. According to the model, an insight solution process is accompanied by emotions regulating the process of representational change. A feeling of impasse is a response to the lack of progress towards the solution. An Aha! experience appears in response to solvers performing actions that bring them a huge step closer to the solution of a problem. We believe that these emotional responses are experienced before the solution reaches consciousness and they motivate the solver to adapt their search space accordingly. The model we propose is a development of the ideas of Ya.A. Ponomarev on the role of emotions in regulating of insight problem solving andmodel of M. Ollinger and colleagues describing the phases of insight problem solving.

Процесс инсайтного решения неоднороден и имеет скрытую динамику, которую следует учитывать при анализе полученных в результате исследования данных. Классические методы исследования инсайта, ориентированные только на результативные показатели или вербальные отчёты, не являются оптимальными для исследования процессуальной составляющей. Методы, изучающие процесс косвенно через связанные процессы (загрузка рабочей памяти, физиологические процессы, поведенческие паттерны), выглядят наиболее перспективными. Анализ поведения испытуемого позволяет изучать инсайт без вмешательства в процесс решения задач.

The main goal of the work is to examine possibilities and limitations of solver’s metacognitive monitoring using emotional feedback in the process of insight problem solving. In the research participants solved Katona’s Five-Square problem. During the solution participants received feedback as emotional stimuli: negative or positive. To control nonspecific influence of emotions on problem solving emotional feedback was given only when participants made moves. Feedback was either congruent (for example, positive — correct move, negative — incorrect) or non-congruent (for example, positive — incorrect, negative — correct). We did not reveal the effect of emotional congruency, but showed that positive emotional feedback facilitates solution of the insight problem. The paper discusses possible limitations of experimental design that do not allow making unambiguous conclusions about emotional feedback in the process of insight problem solving.

The paper explores an option to expand the model of mechanisms of insight problem solving proposed by S. Ohlsson. The proposed mechanisms of insight problem solving — chunk decomposition and constraint relaxation — considered within the framework of high-level and low-level processes. Chunk decomposition described as low-level mechanism and constraint relaxation as high-level mechanism. We assume that difficulty of the different insight problems can be explained by high level chunk decomposition and low-level constraint relaxation. The paper describes two experiments dedicated to verify the assumption. The first experiment examines process of solving anagrams (with word) as high-level chunk decomposition. The main results of the experiment show the prospect of distinguishing the semantic chunk decomposition as insight problem solving mechanism. The second experiment use nine-dot insight problem to examine its solution process as relaxation of low-level (perceptual) constraints. Based on the results of the experiments, it can be considered possible to conclude that the expansion of S. Ohlsson’s model of mechanisms of insight problem solving allows to deem the solutions of various problems in a unified system.