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«5-14-2014 Memory and Decision Processes: The Impact of Cognitive Loads on Decision Regret Elan Ariel University of Pennsylvania Follow this and ...»

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University of Pennsylvania

ScholarlyCommons

Wharton Research Scholars Journal Wharton School

5-14-2014

Memory and Decision Processes: The Impact of

Cognitive Loads on Decision Regret

Elan Ariel

University of Pennsylvania

Follow this and additional works at: http://repository.upenn.edu/wharton_research_scholars

Part of the Business Commons, and the Cognition and Perception Commons

Ariel, Elan, "Memory and Decision Processes: The Impact of Cognitive Loads on Decision Regret" (2014). Wharton Research Scholars Journal. Paper 108.

http://repository.upenn.edu/wharton_research_scholars/108 This paper is posted at ScholarlyCommons. http://repository.upenn.edu/wharton_research_scholars/108 For more information, please contact repository@pobox.upenn.edu.

Memory and Decision Processes: The Impact of Cognitive Loads on Decision Regret Abstract Every day, people both make decisions and regret decisions. Whether it is second-guessing a major life choice like one’s career or bemoaning the purchase of a particular shirt, the phenomenon of regret is familiar and tangible. It is important to learn more about this psychological occurrence in order to help people avoid regret by making better decisions in the future (Das & Kerr, 2010; Pieters & Zeelenberg, 2007). Learning about regret necessitates both learning how the inherent mechanism of regret works, and also what external circumstances affect the degree of the regret. Does being distracted on a cell phone while shopping at the grocery store make you more or less regretful? Can other disturbances actually help you make more satisfactory decisions? We hypothesize that the less attention an individual dedicates to a decision, the less regret he or she will experience.

In this research paper we will explore the intersection of two large bodies of research on the topics of cognitive load theory and decision regret and investigate whether individuals subject to a cognitive load during a decision will subsequently experience more or less decision regret. Before discussing our experiment, though, we will conduct an in-depth research analysis on each of these topics. This literature review will include a general introduction to cognitive load theory and regret, various frameworks through which to understand both topics, and some practical applications and implications for each body of research. We will then synthesize the information and construct the hypothesis that an individual under a cognitive load will experience less regret than an unrestrained individual. Following that, we will go through the mechanics of the experiment and present the results of the data obtained. Lastly, we will discuss the results and develop some conclusions.

Keywords cognitive load, memory, decision regret Disciplines Business | Cognition and Perception | Psychology | Social and Behavioral Sciences This working paper is available at ScholarlyCommons: http://repository.upenn.edu/wharton_research_scholars/108

Memory and Decision Processes:

The Impact of Cognitive Loads on Decision Regret

–  –  –

Faculty Advisor: Professor Adam Grant

Introduction:1

Every day, people both make decisions and regret decisions. Whether it is secondguessing a major life choice like one’s career or bemoaning the purchase of a particular shirt, the phenomenon of regret is familiar and tangible. It is important to learn more about this psychological occurrence in order to help people avoid regret by making better decisions in the future (Das & Kerr, 2010; Pieters & Zeelenberg, 2007). Learning about regret necessitates both learning how the inherent mechanism of regret works, and also what external circumstances affect the degree of the regret. Does being distracted on a cell phone while shopping at the grocery store make you more or less regretful? Can other disturbances actually help you make more satisfactory decisions? We hypothesize that the less attention an individual dedicates to a decision, the less regret he or she will experience.

In this research paper we will explore the intersection of two large bodies of research on the topics of cognitive load theory and decision regret and investigate whether individuals subject to a cognitive load during a decision will subsequently experience more or less decision regret. Before discussing our experiment, though, we will conduct an in-depth research analysis on each of these topics. This literature review will include a general introduction to cognitive load theory and regret, various frameworks through which to understand both topics, and some practical applications and implications for each body of research. We will then synthesize the information and construct the hypothesis that an individual under a cognitive load will experience less regret than an unrestrained individual. Following that, we will go through the I would like to sincerely thank Professor Adam Grant for his mentorship both within this research project and outside of it. His leadership by example and willingness to always give is an inspiration for me as a student and as a new researcher. I would also like to thank Katherine Milkman, Joseph Simmons, and Sheena Iyengar for their advice and help with the construction of my hypothesis and experiment. Lastly, I would like to thank Professor Martin Asher and the Wharton Research Scholars program for providing me with the academic and financial support necessary to complete this project.





mechanics of the experiment and present the results of the data obtained. Lastly, we will discuss the results and develop some conclusions.

Cognitive Load:

The first dimension of this study is based on existing literature discussing the various memory processes. There are three main stages of memory: the sensory memory, the working memory, and the long-term memory. Broadly speaking, the sensory memory deals with shortlived incoming sensory inputs and the long-term memory holds dormant information for long periods of time (Schachter & Tulving, 1994). The working memory, which is the middle step in the process, is defined as “a brain system that provides temporary storage and manipulation of the information necessary for such complex cognitive tasks as language comprehension, learning, and reasoning“ (Baddeley, Logie, Bressi, Sala, & Spinnler, 1986). The working memory functions as a medium through which the sensory interactions with our surroundings are eventually encoded as long-term memories. Information must be processed through the bottleneck working memory.

The working memory has limited bandwidth with which to process information. Data processed in the working memory can be lost in less than 20 seconds (Peterson & Peterson, 1959). Certain types of rehearsal can keep information in the working memory for longer than the 20 seconds and correlate to better long-term recall (Craik & Watkins, 1973), yet this exercise of the working memory requires effort that can come at the expense of other tasks (Salvucci & Beltowska, 2008). The scope of the working memory can also be extended using various sensory channels; Baddeley discusses how directing information through both visual and auditory stimuli can increase the total capacity of the working memory (Baddeley et al., 1986). In the field of education, for example, teachers who want to increase their students’ retention should use various different modes of communication during instruction.

The reason students can struggle with processing information is because, as mentioned before, the working memory has a limited capacity. The amount of information that can be held in the working memory has been debated for decades. Groundbreaking research published in the book The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information by George Miller argued that the average individual can remember approximately seven pieces of information, give or take two pieces (Miller, 1956). This result is

also referred to as Miller’s law. He also famously noted that information is stored in chunks:

hence the ability to remember seven words instead of just seven letters. The brain is able to use this chunking heuristic to remember more bits of information.

Ensuing research challenged Miller’s conception of the average size of an individual’s working memory. In 1974, Simon published an article claiming that the capacity of the human working memory is actually five to seven pieces of information (Simon, 1974), while Broadbent later argued that the capacity is only three chunks of information (Broadbent, 1975). Bettman and Hayes both asserted that one can process about six chunks (Bettman, 1979; Hayes, 1962) while Streufert mentions that the mind can retain ten separate chunks of information (Streufert, Suedfeld, & Driver, 1965). Malhotra analyzes the capacity by looking at how many disparate pieces of information can be processed at the same time, and determines that an average working memory can support forty five total comparisons across choices (Malhotra, 2014).

The discussions between these academics all operate within the vacuum of an unoccupied memory; they discuss how much potential internal capacity exists within the working memory.

However, there are an unlimited number of distractions that can inhibit the potential capacity of the mind. Listening to music has been shown by Salamé to place a strain on the working memory (Salamé & Baddeley, 1989), while Luethi discusses how external stress can also limit the working memory capacity (Luethi, Meier, & Sandi, 2008). Sleep deprivation also has been shown to impede working memory processing capacity (Chee & Choo, 2004; Mu et al., 2005).

Cognitive load theory emerged from the conception that it would be possible to positively affect people’s information processing capacities by consciously studying and manipulating external circumstances and variables. By extension, cognitive loads can also impact people’s capacities to learn and make decisions. There are two main types of cognitive loads: intrinsic loads, which are triggered by the nature of the task itself, and extraneous loads, which are caused by the instruction design (Schnotz & Kürschner, 2007). For example, an intrinsic load would be the complexity of a math question on an exam while the extraneous load would be the clarity of the question instructions. Before the 1990s, cognitive load theory “almost exclusively focused on instructional designs” in the education field (Schnotz & Kürschner, 2007, page 472), but more recently it has been applied to a broader range of fields.

Given the foundations of cognitive load theory explained above, the question remains regarding what precisely is the mechanism that makes cognitive loads work. There are many lenses through which to approach this topic, and we will briefly discuss how cognitive loads manifest in various decision strategies and in affect versus cognition.

Decision strategies can be divided into two main categories: similarity-based strategies and rule-based strategies (Erickson & Kruschke, 1998; Juslin, Karlsson, & Olsson, 2008; von Helversen & Rieskamp, 2008). Similarity-based strategies superficially analyze a decision to fit it into an existing decision model, while rule-based strategies

Abstract

a rule to make an informed, specific decision. Similarity-based strategies therefore draw on existing decision frameworks, while rule-based strategies attempt to create a new particular framework. People tend to switch between these two frameworks depending on the situation (Juslin et al., 2008; von Helversen, Mata, & Olsson, 2010).

In the local subject of cognitive loads, Hoffman, von Helversen and Rieskamp describe that individuals under a cognitive load were more likely to switch to use a similarity-based strategy while individuals not under a cognitive load would dedicate more working memory to a rule-based strategy (Hoffmann, von Helversen, & Rieskamp, 2013). Their experiments show that cognitive loads made subjects less effective at tasks well-suited for rule-based strategies while cognitive loads were helpful in situations well-suited for similarity-based strategies. These results are corroborated by other research showing that decision strategies that require a high amount of working memory are less effective, and even impaired, while under a cognitive load (Beilock & Decaro, 2007; J. W. Payne, Bettman, & Johnson, n.d.; Rieskamp & Hoffrage, 2008).

Thus, one mechanism through which cognitive loads have an effect is by crafting the decision strategy an individual uses in a given task.

Another framework useful in analyzing how cognitive loads work is affect and cognition during decision making. There are two large categories of decision processes of low-order affect and higher-order cognition. A similar dichotomy of two parallel systems of decision strategies with a rapid experiential process or a rational deliberate system is highlighted in Epstein’s Cognitive-Experiential Self-Theory (Epstein, 1993). Zajonc proposes that affect can circumvent cognitive processes to make quick decisions (Zajonc, 1980) while Hoch and Loewenstein discuss how impulses and desires can cause consumers to make purchase decisions mindlessly without rational deliberation (Hoch & Loewenstein, 1991).

Shiv and Fedorikhin researched the prevalence of these two main strategies under various degrees of cognitive load (Shiv & Fedorikhin, 2014). They describe how automatic-affective processes are relied upon when under a cognitive load, while deliberate cognitive processes are relied upon when not under a cognitive load. Their experiment highlights this concept very clearly. First, they randomly assigned participants to either be subject to a cognitive load or not.

After this random assignment, the participants were presented with both chocolate cake and fruit salad. The subjects not under a cognitive load relied on their deliberate cognitive processes and rationally decided to consumer the healthier fruit salad, while the subjects under a cognitive load relied more on their automatic-affective processes and decided to eat the ostensibly less healthy chocolate cake. Shiv and Fedorikhin frame this discussion as a struggle between the mind and the heart; given an appropriate amount of cognitive bandwidth, people can make positive rational decisions and not succumb to the temptations of the heart (or stomach).



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