Sci Eng Ethics DOI 10.1007/s11948-014-9544-x ORIGINAL PAPER

The Capacity for Ethical Decisions: The Relationship Between Working Memory and Ethical Decision Making April Martin • Zhanna Bagdasarov Shane Connelly



Received: 18 December 2013 / Accepted: 7 April 2014 Ó Springer Science+Business Media Dordrecht 2014

Abstract Although various models of ethical decision making (EDM) have implicitly called upon constructs governed by working memory capacity (WMC), a study examining this relationship specifically has not been conducted. Using a sense making framework of EDM, we examined the relationship between WMC and various sensemaking processes contributing to EDM. Participants completed an online assessment comprised of a demographic survey, intelligence test, various EDM measures, and the Automated Operation Span task to determine WMC. Results indicated that WMC accounted for unique variance above and beyond ethics education, exposure to ethical issues, and intelligence in several sensemaking processes. Additionally, a marginally significant effect of WMC was also found with reference to EDM. Individual differences in WMC appear likely to play an important role in the ethical decision-making process, and future researchers may wish to consider their potential influences. Keywords Ethical decision-making  Working memory capacity  Sensemaking  AOSPAN  Individual differences

Introduction Great attention has been paid to the way people engage in ethical decision making (EDM), and various models explaining these processes have been proposed A. Martin (&)  Z. Bagdasarov  S. Connelly Department of Psychology, University of Oklahoma, 455 W. Lindsey St., Dale Hall Tower, Room 705, Norman, OK 73019, USA e-mail: [email protected] Z. Bagdasarov e-mail: [email protected] S. Connelly e-mail: [email protected]

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(Mumford et al. 2008; Sonenshein 2007; Trevin˜o 1986). Furthermore, efforts to increase EDM and improve the quality of ethical decisions have also been an important area of focus (Bagdasarov et al. 2012, 2013; Caughron et al. 2011; Harkrider et al. 2012, 2013; Johnson et al. 2012, 2013; Peacock et al. 2013; Stenmark et al. 2010; Thiel et al. 2013). What is much less frequently the subject of examination is the potential influence that individual differences in cognitive ability may have on both EDM processes and outcomes. Although previous literature has investigated individual differences in personality such as narcissism, cynicism, emotion regulation, and the Big Five personality dimensions (Antes et al. 2007; Ford and Richardson 1994; Kligyte et al. 2013), covarying out the influence of IQ, not much attention has been paid to the specific underlying cognitive mechanisms that may moderate EDM outcomes. It is, perhaps, uncomfortable to suggest that some individuals come equipped with individual cognitive traits that make them more intrinsically capable of quality ethical decisions than others, but such a proposal is well-reasoned. Specifically, the impact of individual working memory capacity (WMC) on EDM and its processes is a critical consideration.

Working Memory Capacity It becomes important then, to establish a useful definition of WMC from which the discourse of this paper may proceed. WMC refers to the capability that an individual possesses for holding memory items in active consciousness and for mentally manipulating or transforming this information (Becker and Morris 1999). Thus, it simultaneously references an individual’s capacity for and skill at information processing. It is distinct from the storage space implicated by the concept of shortterm memory (the capacity to remember one or more chunks of information for durations on the order of seconds (Atkinson and Shiffrin 1968; Baddeley et al. 1975; Cowan 2001; Miller 1956; Nairne 2002), in that WM requires an individual to somehow manipulate the information in consciousness and direct attention toward a goal (Becker and Morris 1999). To further elucidate this distinction: Attempting to remember someone’s ten-digit phone number relies on traditional short-term memory, whereas trying to recite the phone number in reverse order relies on WMC. Research generally suggests that working memory is the result of an interplay between temporarily stored information of various formats (e.g., auditory and visual), temporarily activated long-term memory items, and control processes (Ilkowska and Engle 2010; Unsworth and Engle 2007). While multiple models of working memory which differ in structure and explanatory mechanisms have been proposed, a common element to many of these models is an executive or attention control process responsible for the coordination, composition, and maintenance of working memory items (Baddeley and Hitch 1974; Cowan 1997; Norman and Shallice 1986; Schneider and Chein 2003; Unsworth and Engle 2007). Attentional control is the effortful and constrained executive process by which relevant information is maintained and distracting or irrelevant information is inhibited in working memory and is frequently invoked as the catalyst for working memory processes (Conway and Engle 1994; Unsworth and Engle 2007). Thus depletion or

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taxation of this control resource can lead to working memory errors of both commission and omission. Working memory capacity has been found to play a crucial role in a variety of mental tasks ranging from basic perceptual recollection to complex cognitive reasoning (Baddeley and Logie 1999) and is principally agreed upon to be a domain general construct (Conway et al. 2002; Kane et al. 2004). More recently, and more directly relevant to our study, WMC has been implicated as a moderator of performance in a variety of hypothesis generation and decision-making tasks (Dougherty et al. 2010; Thomas et al. 2008). Crucial to the present work, in these studies, it is both the failure to generate new information from long-term memory into working memory and the limited capacity of working memory which lead to sub-optimal decisions (Dougherty et al. 2010; Thomas et al. 2008). That is, by failing to come up with or store within working memory high quality hypotheses on which to base one’s decisions, it is difficult to make those decisions optimally. Measures of WMC are frequently obtained through the use of complex span tasks (dual tasks designed to target individuals’ storage and processing capabilities), usually requiring participants to maintain some goal-relevant information in the face of competing or distracting stimuli or divide their attention across multiple tasks (Ilkowska and Engle 2010). Examples of complex span tasks include dichotic listening tasks (Conway et al. 2001), operation span (Turner and Engle 1989), reading span (Daneman and Carpenter 1980), and symmetry span (Shah and Miyake 1996) among others. These seminal studies as well as decades of subsequent research employing measures of WMC have demonstrated that WMC exists as an individual difference, with those exhibiting higher WMC performing better in situations that require greater allocation of mental resources or cognitive control (see Ilkowska and Engle 2010 for one review). In essence, the greater an individual’s WMC, the more capable and efficient they are in terms of processing memory contents and directing mental activity toward further goals. Additionally, WMC appears to be a vital component of general decision-making processes (Dougherty et al. 2010; Thomas et al. 2008). It is therefore reasonable to expect these same mental capabilities will be important in the more specific domain of ethical decision-making. We believe WMC can be important in the framework of a number of models of EDM, although their necessity is acknowledged to different degrees (including ignoring it entirely) by EDM researchers.

Ethical Decision-Making Models Rationalist approaches to ethical dilemmas are popular and characterize EDM as being ‘‘always based on deliberate and extensive moral reasoning’’ (Sonenshein 2007, p. 1022). While it is relatively easy to see that deliberation and reasoning may be supported by various cognitive capabilities (e.g., WMC), there are aspects of some rationalist approaches where connections to cognitive processes are slightly more obscure. For example, Kohlberg’s (1969) theory of moral development suggests that an individual’s behavior during an ethical dilemma is constrained by

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progression through distinct stages of moral reasoning. While it may be useful to use this conceptualization to explain the development of ethical considerations generally, this approach fails to recognize the impact of individual cognition on moral reasoning and EDM outcomes specifically. Consider two drivers faced with deciding whether or not to run a red light at an empty intersection at three in the morning. The first driver decides not to run the light because there is a social convention (a law) not to do so, and believes it is good to follow these rules because society has deemed them right (Kohlberg’s conventional stage). The second driver also decides not to run the red light but reaches this decision based on the belief that there might be a police officer monitoring the intersection and is afraid of getting a ticket (Kohlberg’s preconventional stage). Consider also that the second driver, too, has internalized society’s rules as being inherently right (conventional reasoning) while still having personally reasoned that it is not morally wrong to run a red light when the intersection is empty (postconventional reasoning). This same driver would therefore choose to run the red light if the driver failed to consider the presence of a police officer. Thus, the second driver appears to be reasoning within multiple stages, but it is the individual’s cognitions that determine the outcome of the ethical decision. That is, the ethicality of the decision made by the driver is dependent not upon the stage of morality he or she may occupy, but rather by the amount and content of information the individual has generated into active memory. Clearly, it is possible to reach the same EDM outcomes while reasoning from different moral stages, and to reach different outcomes despite reasoning from the same moral stage but relying upon different considerations. This reasoning brings into question the value of the distinction between stages of moral reasoning or the idea of progression through them, and underscores the importance of individual cognitive capabilities and other factors in moderating EDM outcomes. In addition to explaining EDM outcomes, accounting for individual differences in cognition may be essential for developing a thorough understanding of EDM processes. Rest (1986) expanded Kohlberg’s (1969) ideas of moral reasoning by delineating four psychological processes which occur when encountering ethical issues: Individuals (1) recognize a moral issue exists, then (2) make judgments as to what is right or wrong using moral reasoning. Next, they (3) develop intentions to engage in behaviors consistent with that reasoning and, finally, actually (4) carry out the behavior. The potential impact of individual differences in cognition is, perhaps, even clearer under this framework. Making a judgment as to what is right or wrong, as during the second process identified by Rest (1986), inherently involves considering information. Depending on the type, quantity, and relevance (actual and perceived) of the information being considered, different judgments may be rendered given the same moral issue. The extent to which each of these considerations actually contributes to the rendered judgment is governed by the individual’s capacity to consider them (i.e., cognitive abilities). Similarly, in the third process of developing intended behavior, the list of potential behaviors that an individual might engage in is constrained by his or her ability to generate those options. This again is dependent upon the individual’s capacity for doing so. Thus, although these rationalist approaches each feature unique explanations of EDM, they are also underspecified in terms of explaining both EDM processes and

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Working Memory and EDM

outcomes, and de-emphasize how ethical events are individually constructed as well as the constraints (cognitive or otherwise) operating over those constructions. Researchers proposing more recent models of EDM have recognized a few of the shortcomings associated with rationalist approaches and make a more explicit appeal to the role of cognitive capabilities in EDM (Sonenshein 2007; Mumford et al. 2008). Additionally, considering the multifaceted nature of ethical events, several researchers have proposed moving beyond rationalist models to those that address intuitive and interpersonal components of EDM (Detert et al. 2008; Gaudine and Thorne 2001; Haidt 2001; Mumford et al. 2008; Woiceshyn 2011). One such model is the Sensemaking-Intuition (S-I) model proposed by Sonenshein (2007). Sensemaking is a complex cognitive process that involves gathering relevant information, integrating/interpreting it, and taking action. Both the processes of integrating/interpreting and gathering information rely upon working memory (Thomas et al. 2008). Furthermore, the S-I model accounts for the fact that ethical dilemmas involve an element of uncertainty (Sonenshein 2007). Uncertainty is important in that it requires an individual to mentally generate potential explanations and outcomes for ethical situations, and this generation process relies extensively upon WMC and can change decision outcomes (Thomas et al. 2008). For example, Kohlberg’s (1981) conventional level of moral development suggests individuals consider the moral norms of others and strive to obey the rules; however, in uncertain situations (as allowed for by Sonenshein 2007) it may be unclear which norms are relevant. Thus, the particular norms an individual generates to apply in any given situation may differentially determine the outcome of the ethical decision, and those chosen norms may differ during each encounter with an ethical dilemma. These model features serve to illustrate the constructive nature of EDM and point out the ways in which cognitive biases may influence people’s ethical decisions and behaviors. It should be mentioned that the S-I model also involves an intuitive component that relies on a person’s visceral, affect-laden response to a situation to determine its ethical relevance and reach a judgment. While we certainly recognize a place for such processes in EDM, and even recognize that emotional experience and processing impact WMC (e.g., Schmeichel 2007; Schmeichel et al. 2008), we do not give special consideration to these influences in the presently developing theory. Instead, for the purposes of this treatise, they are considered a part of the aggregate of information that may be competing for limited WM resources. More specifically applicable given the perspective of individual WMC as a determinant of EDM skill and along similar lines as the S-I model, Mumford et al. (2008) proposed the sensemaking model of EDM. This model definitively states that situational constraints influence a person’s appraisal of a problem and that people, following the experience of various emotions, will begin to search memory (selfreflect) for information to help them make a decision. This is exactly the type of activity (recalling, maintaining, and directing information toward a goal) that is the purview of working memory. Additionally, forecasting potential decision outcomes and mentally appraising those outcomes is an important component of the sensemaking model (Mumford et al. 2008). Again, it is plain to see how these processes map directly onto the domain of working memory. Indeed, Mumford et al.

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(2008) identify a number of valuable metacognitive strategies (e.g., framing, forecasting, self-reflection, and emotion-regulation) that are directly dependent upon cognitive processes. Both Sonenshein’s (2007) and Mumford et al.’s (2008) models suggest that people have the capacity to improve EDM by enhancing their sensemaking skills, but neither explores the impact that inherent individual capability has on EDM. Thus, while sensemaking models improve on the rationalist frameworks in a number of ways, they also create a demand for their specified contributing cognitive processes to be elucidated. This paper serves as a response to that demand. Although WMC and intelligence are highly correlated, previous research has shown them to be dissociable (see Conway et al. 2003 for a review). This dissociation along with the specific characteristics of WMC lead to distinct predictions about the impact WMC can be expected to have on EDM processes and, in turn, on the decisions themselves. Ethical dilemmas are complex, often illdefined, and frequently involve high-stakes consequences (Werhane 2002). As implied by the rationalist models of Kohlberg (1969) and Rest (1986), and as suggested directly by the sensemaking models of Sonenshein (2007) and Mumford et al. (2008), in order to successfully handle such dilemmas it is necessary to represent many pieces of information in mind at once. Additionally, the decisionmaker is tasked with determining which factors are important, how they relate to the dilemma and to each other, and sometimes even how various interactions of these factors might come into play. We suggest that individual cognitive capabilities moderate the amount of information being considered, its relevance to the dilemma at hand, and the caliber of decision outcomes. Specifically, we believe that WMC is an individual difference that constrains sensemaking processes and outcome quality. We therefore propose the following hypotheses: H1 WMC will account for unique variance in sensemaking processes (i.e., recognition of critical causes, constraints, and forecast quality) beyond that accounted for by ethics education, exposure to ethical issues, and intelligence. H2 WMC will account for unique variance in both measures of EDM (i.e., decision ethicality and EDM test) beyond that accounted for by ethics education, exposure to ethical issues, and intelligence.

Methods Participants Participants included 208 undergraduate students (152 females and 56 males) enrolled in introductory psychology courses at the University of Oklahoma. Their mean age was 18.6 years (SD = 1.47), 76 % were freshmen, and the majority of the sample possessed B2 years of work experience. Participants were recruited via an online experiment management system using a brief description of the study. All students received course credit for their time and effort.

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Procedure This study was administered online and lasted approximately 2 h. Within 24 h of registering for the study, participants were sent a unique code with a hyperlink to the experiment. All participants were given 1 week to complete the study before their unique code expired. After entering their confirmation code on the first page, individuals read the consent form and agreed or disagreed to participate. Those who agreed to participate were then given the following five tasks in order with instructions and a brief description for each task immediately preceding it: (1) demographic survey, (2) Employee Aptitude Survey (EAS), (3) low-fidelity task, 4) EDM measure, and (5) Automated Operation Span (AOSPAN) task. Measures Demographic Survey A 19-item demographic questionnaire was developed to assess basic demographic characteristics of the sample (e.g., age, gender, academic major, school completed, etc.), as well as other variables of interest. Participants were asked to report the number of face-to-face and online ethics training programs they had completed, and psychology and philosophy courses they took during their college careers. Answers to these four items (questions 7–10) were averaged together to create one score for a construct named ethics education discussed in our hypotheses. Participants were also asked to report the extent to which they discussed ethics when interacting with their friends, family members, and co-workers, as well as how often they considered or encountered ethical issues during recreational activities and during engagement with different forms of media. These final questions were assessed on a 5-point Likert scale (1 = never and 5 = very often). These items (questions 11–15 and 18) were averaged together to create a construct referred to as exposure to ethical issues discussed in the hypotheses. See ‘‘Appendix 1’’ for the complete demographic survey. EAS Participants’ intelligence was measured via a 5-min, timed, 30-item verbal reasoning test; the EAS. Participants were presented with sets of brief, factual statements along with four to five possible conclusions. The task required individuals to indicate whether the conclusions were true, false, or uncertain given the set of statements. Dependent on participants’ performance speed, they were presented up to six sets of statements and conclusions. This analogical reasoning test generally yields positive correlations with other measures of general intelligence. Test–retest reliability commonly lies in the .80s and internal consistency coefficients are typically in the .90s (Vincent et al. 2002). Information regarding the predictive and construct validity of this test can be found in Grimsley et al. (1985) and Ruch and Ruch (1980),

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Low-Fidelity Task Sensemaking processes were assessed using a low-fidelity task. This task consisted of a one-page, ethics case, followed by seven questions designed to tap various sensemaking processes known to be critical to EDM (Mumford et al. 2008). Participants were asked to assume the role of a city council member involved in an ethical dilemma surrounding a new construction project for the city (Appendix 2). Directly following the reading of this case, participants were presented with seven questions requiring the identification of key causes of the dilemma, the challenges and constraints of the situation, and its possible outcomes. A final question asked participants to make a decision about how the ethical dilemma should be handled and to outline the rationale for this chosen course of action. Three graduate students coded participant responses for their use of sensemaking processes according to Mumford and colleagues’ sensemaking model of EDM (2008). All raters underwent a 20-h frame-of-reference training (Woehr and Huffcutt 1994). Raters were provided with a thorough description of each variable of interest and allowed an opportunity to practice by rating 20 randomly chosen responses. Ratings of these responses were used to achieve concordant rater calibration. The details of the variables coded from participant responses are as follows: Causes The extent to which participants identified critical causes of the ethical dilemma was assessed directly via the related questions following the low-fidelity simulation. Cause Criticality was measured using a 5-point Likert scale (1 = few critical causes identified, 5 = many critical causes identified). Inter-rater reliability, assessed using the intra-class correlation coefficient (ICC), was .87. Constraints Two variables were coded for the constraint analysis: Breadth of Constraints and Criticality of Constraints. Breadth of Constraints was defined as the extent to which constraints identified by the participant covered a large number of factors (i.e., both personal and situational constraints) and various elements (i.e., people, tasks, groups, etc.). This variable was measured on a 5-point Likert scale (1 = narrow breadth, 5 = very broad). Criticality of Constraints was defined as the extent to which participants were able to identify crucial constraints to decisions, and was also measured on a 5-point Likert scale (1 = few critical constraints identified, 5 = many critical constraints identified). Inter-rater reliability was high for both variables (ICC = .89 and .88, respectively). Forecasting The extent to which participants’ predicted outcomes applied to the scenario, were detailed and realistic, and demonstrated consideration of critical aspects of the case was indicated via Forecast Quality. This variable was rated on a 5-point Likert scale (1 = poor quality, 5 = very good quality) and resulted in very high inter-rater agreement (ICC = .92). Decision Ethicality Participants’ final decisions were also rated for ethicality on a 5-point Likert scale (1 = poor ethical decision-making, 5 = very good ethical decisionmaking). Decision Ethicality was assessed according to three benchmarks: (1) regard for

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the welfare of others, (2) attention to personal responsibilities, and 3) adherence to/ knowledge of social obligations. Inter-rater agreement was high (ICC = .83). EDM Measure EDM was assessed in two ways: via coding of responses to the low-fidelity simulation, as previously discussed, and also using a validated, reliable EDM measure (Mumford et al. 2006, 2008). The 25 multiple-choice question ethical decision-making measure was comprised of five overarching scenarios that were each followed by five question items reflecting ethical dilemmas. Each question was followed by eight answer options and participants were asked to choose the two most appropriate answers to each ethical dilemma. The answer items were constructed by subject matter experts on ethics and experts from various fields in the social sciences and were structured to differentially reflect high (3), moderate (2), and low (1) levels of ethical decision-making. Participant answers were scored by averaging the two selected responses for each question. AOSPAN Task One popular measure used to assess WMC is the AOSPAN task devised by Unsworth, Heitz, Schrock, and Engle (2005). During this task, participants are presented with random arithmetic problems interleaved with random letter sequences that they must recall in correct serial order. Participants are told to answer as quickly as possible while still achieving accuracy. During the introductory phase of the AOSPAN task, a participant’s individual average time for solving arithmetic problems is established and used to assess later performance. If the participant takes longer than this average time to respond to subsequent problems, the problem is scored as incorrect and the next letter in the to-beremembered sequence is automatically flashed and quickly followed by presentation of the next arithmetic problem. Numbers are displayed for one second. After all letters in a sequence have been flashed, a test requests the participant to select the presented letters in correct serial order. When the participant finishes entering an answer, another series of letters and problems begins. Thus, a participant must be able to accurately assess arithmetic problems while simultaneously maintaining the ordered presentation of letters in memory, and do so under time pressure. A trial proceeds as follows: A participant sees a random arithmetic problem (e.g., ‘‘(6*3) - 4 = ?’’). They then click the mouse to advance to the next screen which shows a potential solution to the problem (e.g., ‘‘12’’). The participant must indicate whether he or she believes the solution to be true or false by clicking on either of the displayed corresponding buttons. Following this answer, a random (selected without replacement) letter is displayed for one second before the next arithmetic problem appears and the sequence is repeated. Participants may be required to maintain anywhere from two to seven letters in any given series. All participants are exposed to the same number and lengths of series. Finally, at the conclusion of a series, the participant is presented with a 3 9 4 matrix of letters from which they try to select the letters in the same temporal order in which they were presented during the

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A. A. Martin et al. Table 1 Correlation matrix for all sensemaking processes, EDM, WMC, and intelligence Variables

1

2

3

4

5

6

7

1 Cause criticality



2 Breadth of constraints

.58**

3 Criticality of constraints

.60**

.95**



4 Forecast quality

.46**

.76**

.76**



5 Decision ethicality

.42**

.46**

.47**

.44**

6 EDM ethicality

.29**

.41**

.46**

.40**

.20**



7 WMC

.00

.20**

.20**

.24**

.15*

.18*



8 Intelligence

.30**

.39**

.42**

.32**

.26**

.39**

.21**

8







* Correlations are significant at p \ .05 ** Correlations are significant at p \ .01

series. After entering their answer, the next trial begins. Participants experience 12 trials and usually complete the task within 30–45 min. Participant performance is scored using the total number of perfectly recalled letter sequences. For more details on this measure see Unsworth et al. (2005).

Results Analyses In order to test our hypotheses, we performed hierarchical regression analyses to determine whether WMC accounted for unique variance beyond that provided by ethics education, exposure to ethical issues, and intelligence in sensemaking processes and EDM. Regression analyses were conducted in a similar manner, with the exception of the dependent variables. We entered ethics education and exposure to ethical issues into Step 1, followed by intelligence in Step 2, and finally WMC in Step 3. Table 1 presents a correlation matrix for all sensemaking processes, decision ethicality, EDM ethicality, WMC, and intelligence. Table 2 presents a correlation matrix for all demographic variables, decision ethicality, intelligence, EDM ethicality, and WMC. Hypothesis 1: Sensemaking Processes To test the impact of ethics education, exposure to ethical issues, intelligence, and WMC on sensemaking processes, we conducted four separate hierarchical regressions with cause criticality, constraint breadth, constraint criticality, and forecast quality as dependent variables. Findings revealed that aside from cause criticality, WMC accounted for unique variance in breadth of constraints, criticality of constraints, and quality of forecasts. These findings mostly supported our first hypothesis and indicated that WMC is an important individual difference to consider when it comes to the process of sensemaking, which is essential to EDM. Tables 3, 4 and 5 provide detailed summaries of each hierarchical regression.

123



.20*

.24**

.23**

-.06

.05

.06

-.02

.11

.14*

-.01

.07

.16*

.09

-.02

.09

1 Face-to-face ethics T

2 Online ethics T

3 Number of psych classes

4 Number of phil classes

5 Ethics w/friends

6 Ethics with family

7 Ethics at work

8 Ethics in media

9 Consider ethical implic.

10 Prepared to deal

11 Ethics in education

12 Ethics importance

13 Decision ethicality

14 Intelligence

15 EDM ethicality

16 WMC

-.11

-.03

.06

.02

-.002

.16*

-.01

-.05

.02

.07

.04

.04

.03

.20**



2

** Correlations are significant at p \ .01

* Correlations are significant at p \ .05

1

Variables

.09

-04

-.05

.11

-.01

.05

-.07

-.01

.05

.14*

.08

.02

.30**



3

.10

.13

.17*

.10

.11

.16*

.03

.11

.06

.03

.08

-.11



4

-.10

.05

-.01

.11

.34**

.31**

.33**

.29**

.37**

.44**

.62**



5

-.06

.04

-.02

.03

.48**

.47**

.31**

.42**

.40**

.43**



6

-.10

-.08

-.18**

-.04

.16*

.25**

.23**

.21**

.28**



7

Table 2 Correlation matrix for demographic variables, EDM, intelligence, and WMC

.09

.24**

.03

.20**

.49*

.42*

.33**

.55**



8

.08

.16*

.07

.11

.57**

.36**

.41**



9

.003

.14

.10

.16*

.51**

.37**



10

-.04

.03

-.03

.06

.46**



11

.08

.22**

.14*

.20**



12

.15*

.20**

.26**



13

.21**

.39**



14

.18*



15



16

Working Memory and EDM

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A. A. Martin et al.

Hypothesis 2: Ethical Decision Making Decision Ethicality The results of step one of the hierarchical regression predicting decision ethicality from ethics education, exposure to ethical issues, intelligence, and WMC indicated that the variance accounted for (R2) by ethics education and exposure to ethical issues equaled .04, which was significantly different from zero, F(2, 202) = 4.10, p \ .05. Next, intelligence scores were entered into the regression equation. The change in variance accounted for (DR2) was equal to .06, which was a statistically significant increase in variance accounted for over the step one model [DF(1, 201) = 14.18, p \ .001]. In step 3, WMC was entered in the regression equation. The change in variance accounted for (DR2) was equal to .01, which was not statistically significant [DF(1, 200) = 2.42, p [ .05]. EDM The results of step one of the hierarchical regression predicting EDM from ethics education, exposure to ethical issues, intelligence, and WMC indicated that the variance accounted for (R2) by ethics education and exposure to ethical issues equaled .01, which was not significantly different from zero, F(2, 204) = .90, p [ .05. The change in variance accounted for (DR2) by intelligence was equal to .16, which was a statistically significant increase in variance accounted for over the step one model [DF(1, 203) = 37.78, p \ .001]. In step 3, the change in variance accounted for by WMC (DR2) was equal to .01, which was marginally significant [DF(1, 202) = 2.92, p = .08]. Thus, it appears that we partially supported hypothesis 2 with the marginal results related to the second assessment of EDM. This indicates that WMC has a marginally significant impact on EDM over and above the influence of ethics education and exposure to ethical issues, as well as general intelligence.

Discussion The outcomes of this study suggest that it may be important to consider the influences that individual cognitive abilities in the form of WMC have on EDM outcomes through the sensemaking process. Specifically, within the framework of Mumford et al.’s (2008) sensemaking model, we demonstrated, via a set of hierarchical regressions, that WMC accounted for unique variance above and beyond ethics education, exposure to ethical issues, and intelligence in both measures of constraint identification and forecast quality, as well a marginally significant impact on EDM. This not only showed that WMC is an important variable to consider in the processes necessary for EDM, but it also indicated that WMC has an effect distinct from intelligence in at least some of those processes. Although we did not find support for one sensemaking process involving the identification of the most critical causes of an ethical dilemma, one potential explanation is that an individual’s ability to do so based on WMC is necessarily

123

Working Memory and EDM Table 3 Hierarchical regression analyses evaluating predictors of constraint breadth Variables

R2

DR2

Step 1

.02

.02

DF2 2.13

df 2, 202

Ethics education

-.01

Exposure to ethical issues Step 2

.14* .18

.16

38.85***

1, 201

.20

.02

4.24*

1, 200

Intelligence Step 3

b

.40***

WMC

.13*

* p \ .05; *** p \ .001

Table 4 Hierarchical regression analyses evaluating predictors of constraint criticality Variables

R2

DR2

Step 1

.03

.03

DF2 2.64

df 2, 202

Ethics education

.00

Exposure to ethical issues Step 2

.16* .21

.19

47.57***

1, 201

.23

.02

4.48*

1, 200

Intelligence Step 3

b

.44***

WMC

.13*

*** p \ .001

Table 5 Hierarchical regression analyses evaluating predictors of forecast quality Variables

R2

DR2

Step 1

.02

.02

DF2 2.21

df 2, 202

Ethics education

.05

Exposure to ethical issues Step 2

.13 .13

.10

23.75***

1, 201

.16

.03

7.69**

1, 200

Intelligence Step 3 WMC

b

.32*** .18**

*** p \ .001

restricted due to the format of the task we used. To wit, while identifying potential constraints and forecasting outcomes require a participant to speculate about and generate these items on their own (presumably tapping working memory abilities), identifying the causes of the dilemma is more a matter of recognizing the appropriate information already supplied within the scenario (which should not tax memory capacity and information manipulation aptitude to the same extent, if at all). This hints at a potential limitation to our study and suggests room for future research. For instance, a scenario that is more ambiguous and which does not provide

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unlimited opportunity for review may elicit the impact of WMC in identifying ethical dilemma causes. It could also be that our choice of using AOSPAN as a measure of WMC may be limiting in terms of our findings. While operation span has been extensively used in WM research and WMC is a domain general construct, there are other measures of WMC available which might allow future scientists to uncover more statistically powerful findings. For example, AOSPAN relies on letter-string memorization in the face of distractors, whereas a test of verbal fluency (Rosen and Engle 1997) or reading span (which have also been shown to demonstrate WMC limitations) might more closely resemble the actual task performed on the EDM measures. Additionally, while we were initially disappointed that our predictions of an advantage for higher WMC individuals across all sensemaking processes did not pan out, we did recognize another possible explanation for this outcome that is important. This outcome is important because it suggests that, despite any endogenous advantages in EDM they may possess due to cognitive capacity, individuals are not necessarily well-endowed with skills in all aspects of EDM, and therefore training is still of critical importance in helping decision-makers reach their full potential. Despite this finding, however, it remains relatively clear that WMC differences do have an effect on the rest of the sensemaking processes. We also predicted that WMC would have an effect above and beyond ethics education, exposure to ethical issues, and intelligence on EDM. We made this prediction based on the influence that we presumed WMC would have on the previously discussed underlying factors (sensemaking processes) contributing to EDM outcomes. Similar to a chess player’s capacity to predict an opponent’s potential sequence of moves, if individuals with higher WMC are able to consider a greater amount of relevant information or are more adept at maintaining and manipulating it for the purposes of predicting and evaluating, the resultant decisions made from these processes should be of a higher quality than those made by lower capacity individuals. This prediction was only marginally supported for one of our two measures of EDM. Our study sample consisted of a relatively young group of people. Additionally, most participants (76 %) were college freshmen. These statistics indicate that our sample may be difficult to generalize from and may signify a general lack of real-world exposure to processing ethical dilemmas among the sample. One potential positive to these sample characteristics, however, is that it suggests our data may be the result of relatively ‘‘pure’’ relationships between our variables of interest due to lack of interference from extensive life experience or professional training. Future research might aim to determine if our findings are robust across multiple samples of various age and experience compositions. Because our study was administered online, participants were not monitored during task completion. It is possible that some participants had outside assistance or that the same individual did not complete all aspects of the study. This potentiality is limited due to the timed nature of some of the tasks, the relatively short duration of the entire set of tasks, and the fact that all measures had to be completed in one session, but it nonetheless exists. Another potential limitation is that all measures were administered in the same sequence to each participant. We have not completed any analyses to test for the presence of order effects. It might be helpful to conduct further research under more directly monitored conditions and with varying test order. While the sensemaking model we discussed in

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this paper is certainly useful, it could be that the general model only applies under certain conditions (e.g., depending on the severity of the ethics involved) or that there may be other, as of yet, unidentified strategies and processes which show that WMC may not have the relationship to EDM that we are suggesting. As mentioned, we found that the impact of WMC on identification of critical causes and one measure of EDM was not significant and briefly discussed the importance of EDM training in helping individuals realize their full potential. Although we demonstrated a significant influence of WMC on sensemaking processes and outcomes as delineated by WMC, it would be interesting to see the effect that EDM training might have in mitigating this influence. It could be that the initial advantage for making high-quality ethical decisions seen in individuals with higher WMC than to those with lower WMC would disappear after both groups underwent training. Alternatively, training may serve to give higher WMC individuals an even greater advantage. For example, it may be possible to provide individuals with compensatory strategies which eliminate the reliance on WMC. A simple example of this might be teaching people to create a written record of their thoughts related to an ethical conundrum so that they can alleviate the cognitive burden of maintaining all the thoughts simultaneously. Individuals could also be encouraged to avoid making hasty decisions where possible, instead deliberating over the involved information over a number of days in order to prevent biased or ill-informed decisions. Future research could shed light on the viability of such strategies and may prove to be a fruitful pursuit. Additionally, future researchers may wish to explore the utility of EDM screening tests with which individual differences—such as WMC—that have been identified as potential contributors to EDM processes and outcomes can be evaluated. Another line of research could investigate whether high and low span individuals perform similarly (or even whether trend reverses) when EDM tasks are performed under constraints such as time pressure (which would presumably eliminate the high span advantage). An important area of research as pertains to the current study is the role of affect in cognition. Though it was not central to the study at hand, we recognize that emotions have strong influences on information processing. First, memories are stored with affective tags which influence their retrieval (Blaney 1986; Christianson 1992; Kensinger and Schacter 2006). Additionally, previous literature has demonstrated extensively the impact of emotion on both working memory (Baddeley 2007; Bagozzi et al. 2003; Bagozzi and Pieters 1998; Kensinger and Corkin 2003; Linnenbrink et al. 1999; Mikels et al. 2008; Perugini and Bagozzi 2001) and EDM (Angie et al. 2011; Kligyte et al. 2013; Thiel et al. 2011). As ethical situations frequently involve elements which may inspire various emotions, affect and levels of arousal, researchers may wish to consider these factors explicitly in future studies. Finally, as the presence of digital assistants and technological information processing capacities increases, is a distinction based on human processing limitations something that can be easily overcome? Given the present findings, researchers might at least pause to consider the impact of individual cognitive capabilities on EDM. It is not a surprise to think that the greater an individuals’ capacity for processing information, the greater his or her capacity for employing sensemaking processes and making higher quality decisions. Here we have demonstrated clear relationships between WMC and most sensemaking processes and EDM. Higher WMC does appear to share an association with improved EDM.

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Appendix 1: Demographic Survey 1.

Age:________

2.

Major:________________

3.

Year in College: Freshman

4.

Years of Work Experience: ________

5.

Current GPAs

6.

Is English your first language? (circle)

7.

How many face-to-face ethics training programs have you completed? _______

8.

How many online ethics training programs have you completed? ______

9.

How many psychology courses have you completed? ______

10.

How many philosophy courses have you completed? ______

11.

How often do you discuss ethics with your friends?

1 Never 12. 1 Never

Gender:________

Sophomore

Junior SeniorOther

Overall_________

2 Rarely

In Major _________ Y

3 Sometimes

N

4 Often

How often do you discuss ethics with your family? 2 Rarely

3 Sometimes

4 Often

1 Never

2 Rarely

3 Sometimes

4 Often

1 Never

2 Rarely

3 Sometimes

4 Often

13.

5 Very Often

5 Very Often How often do you discuss ethics with people at work (e.g., co-workers, supervisors)?

5 Very Often 14. How often do you consider ethical issues when engaging in recreational activities (e.g., sports, volunteer/civic organizations, hobbies)? 5 Very Often

How often do you consider ethical issues when interacting with different forms of media (e.g., internet, music, movies, games, literature, social networks)? 1 Never 15.

2 Rarely

3 Sometimes

4 Often

5 Very Often

How likely are you to consider ethical implications during a crisis?

1 Very Unlikely

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2 Somewhat Unlikely

3 Neutral

4 Somewhat Likely

5 Very Likely

Working Memory and EDM

16.

How prepared to do you feel to deal with an ethical problem?

1 Not Prepared At All

17.

3 Neutral

4 Somewhat Prepared

5 Very Prepared

How often do you discuss ethics in your education (e.g., psychology, philosophy, law, medicine, religious education, political science)?

1 Never

18.

2 Somewhat Unprepared

2 Rarely

3 Sometimes

4 Often

5 Very Often

How important is ethical behavior to you?

1 Very Unimportant

2 3 Unimportant Neutral

4 Important

5 Very Important

Appendix 2: Friendswood City Council You are an expert building contractor. You have a master’s degree in civil engineering, and after 20 years of working as a licensed contractor, you decided to retire. You and your spouse live in Friendswood, a small community in which you are very active. You often volunteer your services and expertise to local organizations that need your help. For instance, when city structures are being built, you often volunteer your expertise as a contractor free of charge, so that the city can save money. Whenever such opportunities arise, you are pleased to help because no one will place restrictions on you or your ‘‘vision’’. Most of the time, you enjoy full autonomy to proceed with the projects as you see fit. You are on the board of the Friendswood city council. There are twelve people that make up the council, including you. Members of the city council are elected by the residents of the city. You feel like the city council elections have become somewhat of a popularity contest, and it seems like the members of the council are the wealthiest members of the community, not necessarily the people who would benefit the community most. You feel like some of the members of the city council have no interest in giving back to the community; they just want to feel important by being a part of this organization. Recently, two of the members of the council have begun to feud. Bill Knight and John Cosby got into an argument over which of them owns a lake that borders both of their property. The council members have begun to take sides, and the council is dividing into two factions. It is getting to the point where city council meetings are not productive. The meetings always turn into a political forum for Bill and John to voice why each is right in their arguments. Furthermore, the in-fighting has caused the members not to communicate well. There are subcommittees in the council for various projects, including community fundraising, maintenance of Main Street, and community social events. The subcommittees have turned into cliques that are not communicating their progress to

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each other, and communication is essential for productive functioning of the city council. You think the whole argument is silly, and you refuse to take sides. You are still able to talk to most of the council members and the community still thinks highly of you. You are worried you won’t be able to prevent these conflicts and are doing what you can to prevent public opinion from turning against you too. Recently, the city council began looking to fund a renovation project of your local community center. Because you are an expert in construction, you designed the application for constructing companies to bid on this project. Furthermore, because you did not want to work closely with your colleagues on projects, given the in-fighting, you decided to design the application by yourself. You were given full autonomy in designing the application and you applied your expertise to do what would be best for the community. You are now a part of the committee reviewing and approving the proposals. The city has expressed a desire for the renovations to begin as soon as possible, and you feel like the committee is rushing the process a little. You are concerned that you will miss something important in the review that will result in critical errors that may result in the city hiring a contractor that is less than satisfactory. Nine proposals have passed a first screen by meeting the criteria outlined in the application you designed. You and several others conducted more extensive reviews of the nine proposals. The team of reviewers has identified the winning proposal, which has many outstanding features. As you scan it one more time, however, you notice that it does not meet one of the ten criteria used in the initial screening process; this proposal should never have even made it past the first round of evaluations. No one else has caught this. Now you wonder what you should do. Case Questions What is the ethical dilemma in this situation? ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ List and describe the causes of the problem. ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ What are the key factors and challenges of this ethical dilemma? ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ What should you consider in solving this problem? ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________

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What are some possible outcomes of this ethical dilemma? ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ What is your final decision? ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ What was your rationale for making this decision? ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________ ______________________________________________________________________________

References Angie, A. D., Connelly, S., Waples, E. P., & Kligyte, V. (2011). The influence of discrete emotions on judgment and decision-making: A meta-analytic review. Cognition and Emotion, 25(8), 1393–1422. Antes, A. L., Brown, R. P., Murphy, S. T., Waples, E. P., Mumford, M. D., Connelly, S., et al. (2007). Personality and ethical decision-making in research: The role of perceptions of self and others. Journal of Empirical Research on Human Research Ethics, 2, 15–34. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. Spence & J. Spence (Eds.), The psychology of learning and motivation (Vol. 2, pp. 89–195). New York: Academic Press. Baddeley, A. (2007). Working memory, thought, and action. Oxford: Oxford University Press. Baddeley, A. D., & Hitch, G. (1974). Working memory. In G. A. Bower (Ed.), The psychology of learning and motivation (Vol. 8, pp. 47–89). New York: Academic Press. Baddeley, A. D., & Logie, R. H. (1999). Working memory: The multiple component model. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 28–61). New York: Cambridge University Press. Baddeley, A. D., Thomson, N., & Buchanan, M. (1975). Word length and the structure of short term memory. Journal of Verbal Learning and Verbal Behavior, 14(6), 575–589. doi:10.1016/S00225371(75)80045-4. Bagdasarov, Z., Harkrider, L. N., Johnson, J. F., Thiel, C. E., MacDougall, A. E., Devenport, L. D., et al. (2012). An investigation of case-based instructional strategies on learning, retention, and ethical decision-making. Journal of Empirical Research on Human Research Ethics, 7(4), 79–86. Bagdasarov, Z., Thiel, C. E., Johnson, J. F., Connelly, S., Harkrider, L., Devenport, L. D., et al. (2013). Case-based ethics instruction: The influence of contextual and individual factors in case content on ethical decision-making. Science and Engineering Ethics, 19(3), 1305–1322. doi:10.1007/s11948012-9414-3. Bagozzi, R. P., Dholakia, U. M., & Basuroy, S. (2003). How effortful decisions get enacted: The motivating role of decision processes, desires, and anticipated emotions. Journal of Behavioral Decision Making, 16(4), 273–295. Bagozzi, R. P., & Pieters, R. (1998). Goal-directed emotions. Cognition and Emotion, 12(1), 1–26. Becker, J. T., & Morris, R. G. (1999). Working memory(s). Brain and Cognition, 41, 1–8. Blaney, P. H. (1986). Affect and memory: A review. Psychological Bulletin, 99(2), 229–246. Caughron, J. J., Antes, A. L., Beeler, C. K., Thiel, C. E., Wang, X., & Mumford, M. D. (2011). Sensemaking strategies for ethical decision making. Ethics and Behavior, 21, 351–366. Christianson, S. A. (Ed.). (1992). The handbook of emotion and memory: Research and theory. Hillsdale, NJ: Lawrence Erlbaum.

123

A. A. Martin et al. Conway, A. R. A., Cowan, N., & Bunting, M. E. (2001). The cocktail party phenomenon revisited: The importance of working memory capacity. Psychological Bulletin & Review, 8, 331–335. Conway, A. R. A., Cowan, N., Bunting, M. F., Therriault, D. J., & Minkoff, S. R. B. (2002). A latent variable analysis of working memory capacity, short-term memory capacity, processing speed, and general fluid intelligence. Intelligence, 30, 163–183. Conway, A. R. A., & Engle, R. W. (1994). Working memory and retrieval: A resource-dependent inhibition model. Journal of Experimental Psychology: General, 123, 354–373. Conway, A. R., Kane, M. J., & Engle, R. W. (2003). Working memory capacity and its relation to general intelligence. Trends in Cognitive Sciences, 7(12), 547–552. doi:10.1016/j.tics.2003.10.005. Cowan, N. (1997). Attention and memory. An integrated framework (Oxford Psychology Series 26). New York: Oxford University Press. Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 1–185. Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19(4), 450–466. Detert, J. R., Trevin˜o, L. K., & Sweitzer, V. L. (2008). Moral disengagement in ethical decision making: A study of antecedents and outcomes. Journal of Applied Psychology, 93(2), 374–391. Dougherty, M., Thomas, R., & Lange, N. (2010). Toward an integrative theory of hypothesis generation, probability judgment, and hypothesis testing. Psychology of Learning and Motivation, 52, 299–342. Ford, R. C., & Richardson, W. D. (1994). Ethical decision making: A review of the empirical literature. Journal of Business Ethics, 13, 205–221. Gaudine, A., & Thorne, L. (2001). Emotion and ethical decision-making in organizations. Journal of Business Ethics, 31, 175–187. Grimsley, G., Ruch, F. L., Warren, N. P., & Ford, J. S. (1985). Manual for the employee attitude survey, test of verbal reasoning. Glendale, CA: Psychological Services. Haidt, J. (2001). The emotional dog and its rational tail: A social intuitionist approach to moral judgment. Psychological Review, 108, 814–834. Harkrider, L. N., MacDougall, A. E., Bagdasarov, Z., Johnson, J. F., Thiel, C. E., Mumford, M. D., et al. (2013). Structuring case-based ethics trainings: How comparing cases and structured prompts influence training effectiveness. Ethics and Behavior, 23(3), 179–198. doi:10.1080/10508422.2013. 774865. Harkrider, L. N., Thiel, C. E., Bagdasarov, Z., Mumford, M. D., Johnson, J. F., Connelly, S., et al. (2012). Improving case-based ethics training with codes of conduct and forecasting content. Ethics and Behavior, 22, 258–280. doi:10.1080/10508422.2012.661311. Ilkowska, M., & Engle, R. (2010). Trait and state differences in working memory capacity. In A. Gruszka, G. Matthews, & B. Szymura (Eds.), Handbook of individual differences in cognition: Attention, memory, and executive control (pp. 295–320). New York, NY: Springer. doi:10.1007/978-1-44191210-7_18. Johnson, J. F., Bagdasarov, Z., Harkrider, L. N., MacDougall, A., Connelly, S., Devenport, L. D., et al. (2013). The effects of note-taking and review processes on sensemaking and ethical decision making. Ethics and Behavior, 23(4), 299–323. doi:10.1080/10508422.2013.774275. Johnson, J. F., Thiel, C. E., Bagdasarov, Z., Connelly, S., Harkrider, L., Devenport, L. D., et al. (2012). Case-based ethics education: The impact of cause complexity and outcome favorability on ethicality. Journal of Empirical Research on Human Research Ethics, 7(3), 63–77. doi:10.1525/jer. 2012.7.3.63. Kane, M. J., Hambrick, D. Z., Tuholski, S. W., Wilhelm, O., Payne, T. W., & Engle, R. W. (2004). The generality of working memory capacity: A latent variable approach to verbal and visuospatial memory span and reasoning. Journal of Experimental Psychology: General, 133, 189–217. Kensinger, E. A., & Corkin, S. (2003). Effect of negative emotional content on working memory and long-term memory. Emotion, 3(4), 378–393. Kensinger, E. A., & Schacter, D. L. (2006). Amygdala activity is associated with the successful encoding of item, but not source, information for positive and negative stimuli. Journal of Neuroscience, 26, 2564–2570. Kligyte, V., Connelly, S., Thiel, C. E., & Devenport, L. D. (2013). The influence of anger, fear, and emotion regulation strategies on ethical decision-making. Human Performance, 26(4), 297–326. doi:10.1080/08959285.2013.814655. Kohlberg, L. (1969). Stages in the development of moral thought and action. New York, NY: Holt, Rinehart and Winston.

123

Working Memory and EDM Kohlberg, L. (1981). Essays on moral development: Vol. 1. The philosophy of moral development. San Francisco: Harper & Row. Linnenbrink, E. A., Ryan, A. M., & Pintrich, P. R. (1999). The role of goals and affect in working memory functioning. Learning and Individual Differences, 11(2), 213–230. Mikels, J. A., Reuter-Lorenz, P. A., Beyer, J. A., & Fredrickson, B. L. (2008). Emotion and working memory: Evidence for domain-specific processes for affective maintenance. Emotion, 8(2), 256–266. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97. doi:10.1037/h0043158. Mumford, M. D., Connelly, S., Brown, R. P., Murphy, S. T., Hill, J. H., Antes, A. L., et al. (2008). Sensemaking approach to ethics training for scientists: Preliminary evidence of training effectiveness. Ethics and Behavior, 18, 315–339. doi:10.1080/10508420802487815. Mumford, M. D., Devenport, L. D., Brown, R. P., Connelly, M. S., Murphy, S. T., Hill, J. H., et al. (2006). Validation of ethical decision-making measures: Evidence for a new set of measures. Ethics and Behavior, 16(4), 319–345. doi:10.1207/s15327019eb1604_4. Nairne, J. S. (2002). Remembering over the short-term: The case against the standard model. Annual Review of Psychology, 53, 53–81. Norman, D. A., & Shallice, T. (1986). Attention to action: Willed and automatic control of behavior. In R. J. Davidson, G. E. Schwartz, & D. Shapiro (Eds.), Consciousness and self-regulation: Advances in research and theory (Vol. 4, pp. 1–18). New York: Plenum. Peacock, J., Harkrider, L. N., Bagdasarov, Z., Connelly, S., Johnson, J. F., Thiel, C. E., et al. (2013). Effects of alternative outcome scenarios and structured outcome evaluation on case-based ethics instruction. Science and Engineering Ethics, 19(3), 1283–1303. doi:10.1007/s11948-012-9402-7. Perugini, M., & Bagozzi, R. P. (2001). The role of desires and anticipated emotions in goal-directed behaviours: Broadening and deepening the theory of planned behaviour. British Journal of Social Psychology, 40(1), 79–98. Rest, J. R. (1986). Moral development: Advances in research and theory. New York, NY: Praeger. Rosen, V. M., & Engle, R. W. (1997). Forward and backward serial recall. Intelligence, 25, 37–47. Ruch, F. L., & Ruch, W. W. (1980). Employee aptitude survey. Los Angeles, CA: Psychological Services. Schmeichel, B. J. (2007). Attention control, memory updating, and emotion regulation temporarily reduce the capacity for executive control. Journal of Experimental Psychology: General, 136, 241–255. Schmeichel, B. J., Volokhov, R. N., & Demaree, H. A. (2008). Working memory capacity and the selfregulation of emotional expression and experience. Journal of Personality and Social Psychology, 95, 1526–1540. Schneider, W., & Chein, J. M. (2003). Controlled and automatic processing: Behavior, theory, and biological mechanisms. Cognitive Science, 27, 525–559. Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of Experimental Psychology: General, 125, 4–27. Sonenshein, S. (2007). The role of construction, intuition, and justification in responding to ethical issues at work: The sensemaking-intuition model. Academy of Management Review, 4, 1022–1040. Stenmark, C., Antes, A. L., Wang, X., Caughron, J., Thiel, C. E., & Mumford, M. D. (2010). Strategies in forecasting outcomes in ethical decision-making: Identifying and analyzing the causes of the problem. Ethics and Behavior, 20, 110–127. Thiel, C. E., Connelly, S., & Griffith, J. A. (2011). The influence of anger on ethical decision making: Comparison of a primary and secondary appraisal. Ethics and Behavior, 21(5), 380–403. Thiel, C. E., Connelly, S., Harkrider, L., Devenport, L. D., Bagdasarov, Z., Johnson, J. F., et al. (2013). Case-based knowledge and ethics education: Improving learning and transfer through emotionally rich cases. Science and Engineering Ethics, 19(1), 265–286. doi:10.1007/s11948-011-9318-7. Thomas, R. P., Dougherty, M. R., Sprenger, A. M., & Harbison, J. I. (2008). Diagnostic hypothesis generation and human judgment. Psychological Review, 115, 155–185. Trevin˜o, L. K. (1986). Ethical decision making in organizations: A person-situation interactionist model. Academy of Management Review, 11(3), 601–617. Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28(2), 127–154. Unsworth, N., & Engle, R. W. (2007). The nature of individual differences in working memory capacity: Active maintenance in primary memory and controlled search from secondary memory. Psychological Review, 114, 104–132.

123

A. A. Martin et al. Unsworth, N., Heitz, R. P., Schrock, J. C., & Engle, R. W. (2005). An automated version of the operation span task. Behavior Research Methods, 37(3), 498–505. Vincent, A. S., Decker, B. P., & Mumford, M. D. (2002). Divergent thinking, intelligence, and expertise: A test of alternative models. Creativity Research Journal, 14(2), 163–178. Werhane, P. H. (2002). Moral imagination and systems thinking. Journal of Business Ethics, 38, 33–42. Woehr, D. J., & Huffcutt, A. I. (1994). Rater training for performance appraisal: A quantitative review. Journal of Occupational and Organizational Psychology, 67, 189–205. Woiceshyn, J. (2011). A model for ethical decision making in business: Reasoning, intuition, and rational moral principles. Journal of Business Ethics, 104(3), 311–323. doi:10.1007/s10551-011-0910-1.

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The capacity for ethical decisions: the relationship between working memory and ethical decision making.

Although various models of ethical decision making (EDM) have implicitly called upon constructs governed by working memory capacity (WMC), a study exa...
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