Andrew F. Jarosz

What Are the Odds? A Practical Guide to Computing and Reporting Bayes Factors

The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the Journal of Problem Solving. The Bayes factor provides information with a similar purpose to the p-value – to allow the researcher to make statistical inferences from data provided by experiments. While the p-value is widely used, the Bayes factor provides several advantages, particularly in that it allows the researcher to make a statement about the alternative hypothesis, rather than just the null hypothesis. In addition, it provides a clearer estimate of the amount of evidence present in the data. Building on previous work by authors such as Wagenmakers (2007), Rouder et al. (2009), and Masson (2011), this article provides a short introduction to Bayes factors, before providing a practical guide to their computation using examples from published work on problem solving.

Uncorking the muse: Alcohol intoxication facilitates creative problem solving

That alcohol provides a benefit to creative processes has long been assumed by popular culture, but to date has not been tested. The current experiment tested the effects of moderate alcohol intoxication on a common creative problem solving task, the Remote Associates Test (RAT). Individuals were brought to a blood alcohol content of approximately .075, and, after reaching peak intoxication, completed a battery of RAT items. Intoxicated individuals solved more RAT items, in less time, and were more likely to perceive their solutions as the result of a sudden insight. Results are interpreted from an attentional control perspective.

Working Memory Capacity, Attentional Focus, and Problem Solving:

Attentional focus is important for many cognitive processes, including problem solving. In this article, we discuss working memory capacity (WMC), a construct related to the ability to focus attention, and its differential effects on analytic and creative problem solving. One of the main ways in which WMC benefits analytic problem solving seems to be that it helps problem solvers to control their attention, resist distraction, and narrow their search through a problem space. Conversely, several lines of recent evidence have shown that too much focus can actually harm performance on creative problem-solving tasks.

New Rule Use Drives the Relation Between Working Memory Capacity and Raven's Advanced Progressive Matrices

The correlation between individual differences in working memory capacity and performance on the Ravens Advanced Progressive Matrices (RAPM) is well documented yet poorly understood. The present work proposes a new explanation: that the need to use a new combination of rules on RAPM problems drives the relation between performance and working memory capacity scores. Evidence for this account is supported by an item-based analysis of performance during standard administration of the RAPM and an experiment that manipulates the need to use new rule combinations across 2 subsets of RAPM items. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Chapter Six - How Working Memory Capacity Affects Problem Solving

Abstract Working memory capacity (WMC) is important for many cognitive processes including problem solving. This chapter compiles the current literature regarding WMC and problem solving, and discusses the various ways in which WMC can help and hinder people as they go about solving problems of varying types. In particular, three types of problem solving are examined: mathematical problem solving, problem solving as it relates to the Raven Progressive Matrices (RPM), and creative problem solving. One of the main benefits across both math and RPM problem solving seems to be that WMC helps solvers to focus their attention, resist distraction, or narrow their search through a problem space. Conversely, several lines of evidence are now showing that too much focus can actually harm performance on creative or insightful problem-solving tasks. It is suggested that in order to account for the differing relationships between WMC and different types of problem solving, a dual-process, analytical/insightful model of problem solving is required.

Firing the Executive: When an Analytic Approach to Problem Solving Helps and Hurts

There is a general assumption that a more controlled or more focused attentional state is beneficial for most cognitive tasks. However, there has been a growing realization that creative problem solving tasks, such as the Remote Associates Task (RAT), may benefit from a less controlled solution approach. To test this hypothesis, in a 2x2 design, we manipulated whether solvers were given the RAT before or after an implicit learning task. We also varied whether they were told to “use their gut” as part of either initial task. The results suggest that a less analytic approach engendered by a “use your gut” instruction benefits performance on the RAT for monolingual solvers. The same benefit was not found for bilingual speakers suggesting that more controlled solution processes may be needed when speakers with multiple lexicons perform this task, which relies heavily on accessing common phrases in a particular language.