Harada Tsutomu
Graduate School of Business Administration, Kobe University, Kobe, Japan.
Front Psychol. 2024 Jan 8;14:1287624. doi: 10.3389/fpsyg.2023.1287624. eCollection 2023.
Despite the fact that insight is a crucial component of creative thought, the means by which it is cultivated remain unknown. The effects of learning traits on insight, specifically, has not been the subject of investigation in pertinent research. This study quantitatively examines the effects of individual differences in learning traits estimated using a Q-learning model within the reinforcement learning framework and evaluates their effects on insight problem solving in two tasks, the 8-coin and 9-dot problems, which fall under the umbrella term "spatial insight problems." Although the learning characteristics of the two problems were different, the results showed that there was a transfer of learning between them. In particular, performance on the insight tasks improved with increasing experience. Moreover, loss-taking, as opposed to loss aversion, had a significant effect on performance in both tasks, depending on the amount of experience one had. It is hypothesized that loss acceptance facilitates analogical transfer between the two tasks and improves performance. In addition, this is one of the few studies that attempted to analyze insight problems using a computational approach. This approach allows the identification of the underlying learning parameters for insight problem solving.
尽管洞察力是创造性思维的关键组成部分，但其培养方式仍然未知。具体而言，学习特质对洞察力的影响尚未成为相关研究的调查对象。本研究定量考察了在强化学习框架内使用Q学习模型估计的学习特质个体差异的影响，并评估了它们对“空间洞察力问题”这一总括术语下的两个任务（8枚硬币问题和9点问题）中洞察力问题解决的影响。尽管这两个问题的学习特征不同，但结果表明它们之间存在学习迁移。特别是，洞察力任务的表现随着经验的增加而提高。此外，与损失厌恶相反，冒险行为对两项任务的表现都有显著影响，这取决于个人的经验量。据推测，接受损失有助于两项任务之间的类比迁移并提高表现。此外，这是少数几项尝试使用计算方法分析洞察力问题的研究之一。这种方法能够识别洞察力问题解决的潜在学习参数。
