Stereotype Threat and Learning

Stereotype Threat and Learning

CHAPTER TWO Stereotype Threat and Learning Robert J. Rydell*,1, Kathryn L. Boucher† *Indiana University, Bloomington, IN, United States † University ...

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CHAPTER TWO

Stereotype Threat and Learning Robert J. Rydell*,1, Kathryn L. Boucher† *Indiana University, Bloomington, IN, United States † University of Indianapolis, Indianapolis, IN, United States 1 Corresponding author: e-mail address: [email protected]

Contents 1. 2. 3. 4. 5.

Stereotype Threat and Performance: The Process The Integrated Process Model Stereotype Threat and Executive Functions Stereotype Threat and Procedural Tasks Stereotype Threat Spillover Effects 5.1 Transitioning From Performance to Learning 5.2 Automatic Attention Attraction and Stereotype Threat 6. Visual Search 6.1 Stereotype Threat and Learning Math 6.2 A Process Model for Stereotype Threat-Based Learning Decrements 6.3 Using Feedback When Under Stereotype Threat 7. Seeking Feedback When Experiencing Stereotype Threat 8. How Feedback Is Perceived When Stereotypic Expectations Are Salient 9. Discounting Performance Feedback and Devaluing the Performance Domain 10. How Feedback Can Improve Outcomes Under Stereotype Threat 10.1 Eliminating Learning Deficits Due to Stereotype Threat: Applying Our Knowledge 11. Removing Cues to Stereotype Threat in the Learning Environment 12. Changing the Content and Pedagogical Approach to Foster Better Learning Outcomes 13. Adopting a Growth Mindset When Learning 14. Self-Affirmation and Academic Achievement 15. Conclusion References

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Abstract Extensive research on stereotype threat has examined how worries and concerns about confirming negative performance stereotypes can harm stereotyped individuals’ performance. An impressive body of knowledge about stereotype threat performance effects has accumulated. However, only a handful of studies have shown that stereotype threat can also negatively impact learning. Although much more research is needed, in this chapter, we review and examine the work on stereotype threat and learning to date

Advances in Experimental Social Psychology, Volume 56 ISSN 0065-2601 http://dx.doi.org/10.1016/bs.aesp.2017.02.002

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2017 Elsevier Inc. All rights reserved.

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and present a model about why and how these learning effects occur. We also discuss how stereotype threat can influence reactions to feedback that occurs in learning settings and how interventions that mitigate stereotype threat can improve learning. Understanding how stereotype threat affects learning is a relatively new avenue for research on stereotype threat that has the potential to provide useful information about how to improve skill acquisition and performance for negatively stereotyped individuals.

In the past 20 years, there has been an explosion in research on stereotype threat, or individuals’ worries about confirming negative stereotypes of their ingroup’s ability by performing poorly themselves in the stereotyped domain (see Steele, Spencer, & Aronson, 2002). Ever since Steele and Aronson’s (1995) groundbreaking work on this phenomenon, researchers have been busy documenting and understanding how stereotype threat influences the performance of negatively stereotyped individuals. Researchers have come to understand an impressive amount about how stereotype threat affects performance as well as how its impact may spill over into other domains (see Rydell, Van Loo, & Boucher, in press). We will briefly review that work here. However, we are more concerned with another outcome of stereotype threat that has received much less empirical attention. Specifically, stereotype threat has been shown to reduce or inhibit stereotyped individuals’ ability to learn (Boucher, Rydell, Van Loo, & Rydell, 2012; Rydell, Rydell, & Boucher, 2010; Rydell, Shiffrin, Boucher, Van Loo, & Rydell, 2010; Taylor & Walton, 2011). Work on stereotype threat and learning has the potential to be important for both theory and practice. If stereotype threat impairs learning, then stereotype threat is an even more difficult and larger problem than was previously thought. That is, stereotype threat not only influences performance of learned skills, but it also impairs the actual acquisition of skills. The effect of stereotype threat on learning constitutes an indirect route through which threat can influence performance and has the potential to move the main thrust of stereotype threat work away from performance on “high stakes” tasks (e.g., performance on tests that can affect admission into college, performance at an important athletic competition; see Steele et al., 2002) to other issues. The most pressing issue would be to understand how best to rid educational settings of threat. Although intervention work has been attempting to do just this, it has generally been for somewhat different reasons. For the most part, intervention work has been about helping negatively stereotyped individuals express the knowledge they have, fostering feelings

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of belongingness, or changing people’s perceptions about their potential for growth. It has not been very concerned with reducing stereotype threat as a specific barrier to learning. As work progresses on stereotype threat and learning, not only may we learn more about why stereotype threat impairs learning, but we may also recognize the importance of reducing threat with the express purpose of increasing learning for negatively stereotyped individuals. It may be the case that many interventions that effectively increase performance for those subjected to stereotype threat do so, at least in part, by reducing threat and therefore increasing learning. We know, from copious amounts of research, that stereotype threat can hurt negatively stereotyped individuals’ performance in situations where they may confirm those stereotypes (see Schmader, Johns, & Forbes, 2008). But here, we hope to provide insight into how stereotype threat can affect learning. Nonetheless, we will first review how stereotype threat impairs performance and can even spillover to behaviors that are outside of the stereotyped domain (e.g., taking risks, overeating; e.g., Inzlicht & Kang, 2010). Next, we will review research examining how stereotype threat impairs learning and why this may happen. We will then examine how feedback, which is normally presented during learning (for instance, in school settings), can influence subsequent learning and performance. Finally, we will review interventions that are meant to improve learning for those who can be the targets of stereotype threat.

1. STEREOTYPE THREAT AND PERFORMANCE: THE PROCESS Since the effects of negative performance stereotypes were first shown by Steele and Aronson (1995), researchers investigating this phenomenon have often included measures of various psychological processes that they believed were responsible, at least in part, for stereotype threat effects. Although there have been many potential mediators examined in the stereotype threat literature, the mediators most often examined have been decreased performance expectations and effort (e.g., Spencer, Steele, & Quinn, 1999), increased anxiety and evaluative concern (Gonzales, Blanton, & Williams, 2002), physiological arousal (e.g., Mendes, Blascovich, Lickel, & Hunter, 2002), and reduced working memory capacity (e.g., Beilock, Rydell, & McConnell, 2007; Schmader & Johns, 2003). It should be noted, however, that research on these (and other) mediators have often produced mixed results. It is difficult to test mediators of stereotype threat effectively,

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because performance measures are often not included in experiments, or because measuring the mediator could have itself activated the stereotype threat for all participants, not just those manipulated to experience threat. Nonetheless, Schmader et al. (2008) provided a compelling integration of this work in a model meant to organize the data and clarify the process(es) underlying stereotype threat performance effects (see also Beilock et al., 2007; Steele et al., 2002).

2. THE INTEGRATED PROCESS MODEL Schmader and colleagues (2008) integrated process model, which synthesizes earlier work on mediators of stereotype threat, incorporates a balance theory perspective of self-integrity threat to explain how stereotype threat can trigger a chain of psychological reactions. These psychological reactions ultimately result in reduced performance for stereotyped individuals in the stereotyped domain. According to this model, explicit and situational cues activate the relevant ability stereotype, which serves to activate stereotyped individuals’ self-concept, their concept of the relevant group identity, their concept of the relevant ability domain, and the propositional relations between them (see Nosek, Banaji, & Greenwald, 2002; Rydell, McConnell, & Beilock, 2009). The negative stereotype about the ability of one’s group creates a conflict (or imbalance) between one’s positive view of the self and one’s positive view of the ingroup. Most importantly, the expected negative performance of one’s ingroup is inconsistent with holding a positive view of the self. This conflict or imbalance is unsettling or arousing, which results in motivation to resolve any discrepancies and bring these views into balance. Similar to dissonance arousal (see Cooper & Fazio, 1984), it is the motivation to address this conflict or imbalance that leads to a host of psychological and physiological processes that ultimately reduce the cognitive resources available to solve the focal task (e.g., a woman completing a math problem) that are the proximal cause of stereotype threat performance effects. Individuals experiencing stereotype threat will closely monitor their environment by paying special attention and being sensitive to information or cues, indicating that their performance in that environment will be evaluated in relation to the activated stereotype (e.g., Murphy, Steele, & Gross, 2007). When in situations in which negatively stereotyped individuals’ performance is likely to be evaluated in relation to the activated stereotype, the previously mentioned cognitive imbalance will be particularly arousing and

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unsettling, because this imbalance is made highly accessible (Nosek et al., 2002). As mentioned earlier, stereotype-threatened individuals are motivated to try to alleviate the cognitive imbalance they experience as a result of stereotype threat. This can be done by distancing themselves from the negatively stereotyped group (Steele & Aronson, 1995) or holding a more negative sense of self that is in line with the negative view of the group provided by the performance stereotype (Cadinu, Maass, Rosabianca, & Kiesner, 2005). Another tactic to restore balance is to attempt to have stereotype-threatened individuals associate with a positively stereotyped group membership in the performance domain (McGlone & Aronson, 2007). For example, work from our lab (Rydell et al., 2009) made some college women aware of the negative stereotype that “women are bad at math,” but also made the positive self-relevant stereotype that “college students are good at math” available. When this occurred, women’s college identity was activated and their gender identity was inhibited, thus resolving the cognitive inconsistency and effectively eliminating negative stereotype threat effects on math performance; we also found that this was especially likely for women high in self-esteem (Rydell & Boucher, 2010). The cognitive inconsistency triggered by stereotype threat makes stereotyped individuals feel stressed, uncertain, and alert. Stereotype threat can lead those experiencing threat to be concerned about (a) whether they will confirm or disconfirm the stereotype about their group and/or (b) whether their performance will affect people’s perceptions of their group (see Shapiro & Neuberg, 2007). In this way, stereotype threat can lead to increased anxiety (e.g., Spencer et al., 1999), though research with selfreported anxiety has yielded mixed results (e.g., Gonzales et al., 2002; Schmader & Johns, 2003; Steele & Aronson, 1995; see also Cadinu et al., 2005). However, research with physiological measures of anxiety has been more consistent, with those under threat showing greater physiological indicators of stress and arousal (e.g., Mendes et al., 2002; Murphy et al., 2007). A variety of negative emotions and thoughts also accompany stereotype threat. Those under threat can begin to feel self-doubt (e.g., Steele & Aronson, 1995) and can have negative expectations for their performance (e.g., Stangor, Carr, & Kiang, 1998). Stereotype threat specifically leads to greater negative self and task-relevant ruminations, including reported worries about the task, the stereotype, and one’s ability and performance (e.g., Cadinu et al., 2005). These ruminations presumably make it difficult for those under threat to focus their attention squarely on the task at hand (see Schmader et al., 2008). Further, when under threat, individuals are

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also more likely to perceive signs that they are not performing well as a signal that they are providing confirmation of the negative stereotype with their behavior (Forbes, Schmader, & Allen, 2008). Even worse for performance, those under threat may concurrently be attempting to suppress the negative thoughts and worries they have in order to attempt to focus on the focal task, and these suppression attempts can ironically fail and actually increase negative thoughts and worries (Logel, Iserman, Davies, Quinn, & Spencer, 2009). The aforementioned physiological, psychological, and behavioral consequences of stereotype threat may ultimately reduce individuals’ cognitive resources to be allocated to the focal task (i.e., completing a math question, completing a standardized test question). This reduction in cognitive resources allocated to the focal task is thought to be the proximal cause of stereotype threat-based performance decrements (Beilock et al., 2007; Schmader & Johns, 2003; Schmader et al., 2008). That is, the impact that stereotype threat has on working memory capacity is hypothesized to be responsible for its effects on performance. In the stereotype threat literature, working memory capacity is usually thought of as a general and limited resource of controlled attention and executive processes (e.g., Engle, 2002; Schmader et al., 2008). When working memory capacity is high, people can employ attentional, cognitive, and behavioral regulation processes that are efficient and effective (in terms of performance). With reduced working memory capacity, the efficient coordination of these processes is impaired and, as a result, performance suffers. In stereotype threat, it is thought that the physiological stress, cognitive monitoring, and suppression and regulation processes that are triggered by stereotype threat usurp the working memory capacity that would otherwise be used for successful task performance.

3. STEREOTYPE THREAT AND EXECUTIVE FUNCTIONS Although research in the stereotype threat literature has tended to adopt a unitary, process-general controlled attention definition of working memory (Engle, 2002), there are more complex models of working memory capacity in the literature, which may provide better understanding of its role in stereotype threat effects. One prominent model divides working memory into three specific cognitive subprocesses called executive functions (Miyake et al., 2000): inhibition (i.e., the ability to intentionally override an automatic response), updating (i.e., the ability to retain relevant and

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delete irrelevant information in the face of interference), and switching (i.e., the ability to effectively switch between multiple tasks). We (Rydell, Van Loo, & Boucher, 2014) found that stereotype threat affects some, but not all, executive functions and that specific executive functions mediate threat effects on different outcomes. For women under threat by gender-based math stereotypes, only updating mediated threat-based math performance decrements, whereas only inhibition accounted for threat effects on increased risk taking. By recognizing the diversity of executive functions that make up working memory, more specific predictions can be made regarding stereotype threat effects, and a more nuanced understanding of stereotype threat process can be explored.

4. STEREOTYPE THREAT AND PROCEDURAL TASKS The vast majority of research on stereotype threat has focused on performance tasks that require more controlled and complicated cognitive processes (e.g., solving a difficult math problem). However, performance deficits can also be shown in response to stereotype threat for relatively more automatic, procedural tasks, such as driving a car, putting a golf ball, or kicking a soccer ball, and the process that underlies effects on these types of tasks seems to be different than for more complicated tasks. For welllearned tasks, stereotype threat impairs performance by the initiation of more conscious, controlled attention during performance (e.g., Beilock, Jellison, Rydell, McConnell, & Carr, 2006; Rydell, Shiffrin, et al., 2010). The hallmark of good performance of procedural tasks is being able to perform well without thinking. If anything, thinking too much gets in the way when executing well-learned tasks. When individuals, because of stereotype thereat, are worried about performing poorly and confirming the negative stereotype, they can begin to concentrate and consciously focus too much on these procedural aspects of the well-learned task. This concentration and increased monitoring of a relatively automated performance actually disrupts the execution of the strongly routinized performance. This disruption of the execution of the proceduralized routine due to stereotype threat can actually inhibit performance on automatized tasks. As will become apparent later, learning deficits in response to stereotype threat can also occur as a result of a similar process. Specifically, the increased attention to relatively simple tasks can inhibit people’s ability to automatize them (Rydell, Shiffrin, et al., 2010).

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5. STEREOTYPE THREAT SPILLOVER EFFECTS The vast majority of existing research examining the underlying processes of stereotype threat has focused on stereotypes about women’s math performance. However, there is some research, indicating that stereotype threat “spillover effects” (i.e., the impact of stereotype threat on outcomes outside of the stereotyped domain) may also be due to reduced executive functioning (e.g., Carr & Steele, 2010; Inzlicht & Kang, 2010). Relatively recent work suggests that stereotype threat, related to gender or race, can affect outcomes such as overeating, aggression, persistence, risky choices, financial decisions, and verbal ability (Beilock et al., 2007; Carr & Steele, 2010; Inzlicht & Kang, 2010; Rydell et al., 2014), which are not part of the experimentally activated gender or racial stereotypes. It seems that most of these spillover effects are a result of ineffective self-regulation (Inzlicht & Kang, 2010), and it is well established that greater executive functioning is related to more effective self-regulation (e.g., Hofmann, Schmeichel, & Baddeley, 2012). For example, Carr and Steele (2010) showed that people experiencing stereotype threat, relative to a control group, were more likely to make poor financial decisions, and this effect was mediated by reductions in the executive function of inhibition (see also Rydell et al., 2014). Thus, the research to date seems to imply that stereotype threat spillover effects may occur due to the same or similar processes such as stereotype threat performance effects. That is, temporarily reduced executive functioning or working memory capacity impairs one’s ability to muster the selfcontrol to eliminate unwanted behaviors like overeating or risk taking. However, more work needs to be conducted on spillover effects to understand the psychological processes underlying them, as well as effective ways to eliminate or reduce them.

5.1 Transitioning From Performance to Learning We know a great deal about stereotype threat performance effects because of the vast research attention the topic has received. Compared to research on stereotype threat performance effects, there has been very limited research on how stereotype threat might influence learning, with only a few published papers that we are aware of (Boucher et al., 2012; Mangels, Good, Whiteman, Maniscalco, & Dweck, 2012; Rydell, Rydell, et al., 2010; Rydell, Shiffrin, et al., 2010; Taylor & Walton, 2011). Why has there not been more examination of the impact of

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stereotype threat on learning? As we have noted elsewhere (Rydell, Rydell, et al., 2010), there are at least two important reasons why this outcome hasn’t been given more attention. The first reason is that there are sometimes no performance differences between the stereotyped group (e.g., women) and the nonstereotyped group (e.g., men) when stereotype threat is not evoked or is removed (e.g., Steele et al., 2002). For example, men and women perform equivalently on problems taken from standardized mathematics tests when not under threat (e.g., Spencer et al., 1999). From such findings, it may seem reasonable to assume equivalent learning of mathematical rules and operations for women and men and to conclude that stereotype threat does not affect learning. This reasoning, however, fails to take into account several mitigating factors. The majority of stereotype threat research utilizes college populations, who have performed well enough on the mathematics portion of college entrance exams to be admitted. Also, some stereotype threat experiments have selected members of the stereotyped group (e.g., women) who are highly identified with the performance domain (e.g., math) as participants (e.g., Beilock et al., 2007; Spencer et al., 1999), perhaps obscuring learning differences. In addition, any deficits in learning between stereotyped and nonstereotyped individuals could be obscured by increased preparation in the performance domain (e.g., increased studying, tutoring, preparatory courses, practice tests, one-on-one student-teacher interaction) by members of the negatively stereotyped group who are aware of the stereotype, and increased preparation has not been accounted for in past stereotype threat research. Given these issues, it seems justified to examine the effect of stereotype threat on learning by teaching participants a new skill and then assessing their learning. The second reason why research has rarely examined whether stereotype threat impairs learning is that learning is difficult to distinguish from performance. From the beginning of experimental psychological research, the most common way that investigators have assessed learning is by measuring participants’ ability to perform the learned task (see Thorndike, 1932). However, because stereotype threat reduces performance when learning is equivalent or statistically controlled (e.g., Steele & Aronson, 1995), stereotype threat’s proposed effect on learning is difficult to infer from performance measures alone. For example, the first study outside our lab on stereotype threat and learning utilized memory as a measure of learning (Taylor & Walton, 2011). This is an imperfect measure because memory failures can be due to encoding problems, which might be considered learning, and/or retrieval problems, which might be considered performance.

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Thus, using memory, at least in this way, is not an optimal way to examine learning (see also Rydell, Rydell, et al., 2010, Study 1, for a similar attempt at using memory). The potential dual effect of stereotype threat on both learning and performance makes clearly showing learning deficits a challenging task, but we have attempted to do so by using various methodologies and experimental designs. For example, our first published paper was on learning in a visual search paradigm (see a detailed review of that work later). This paradigm is one where performance and learning can be relatively easily modeled and understood.

5.2 Automatic Attention Attraction and Stereotype Threat As just noted, distinguishing the effects of stereotype threat on generalized performance from effects on learning is difficult. For example, eliminating stereotype threat via self-affirmation reduced the achievement gap between Caucasian and African American middle-school students over a 2-year period (Cohen, Garcia, Purdie-Vaughns, Apfel, & Brzustoski, 2009). However, this narrowing of the achievement gap could have been due to improved performance associated with reductions in stereotype threat, and/or it could have been due to increased learning after stereotype threat was reduced. As another example, Grimm, Markman, Maddox, and Baldwin (2009) showed that stereotype threat reduced performance on a perceptual categorization task that involved learning which category a line belonged to, but only when the task involved avoiding losses. Because this research involved category learning, and women took longer than men to reach a specified criterion under stereotype threat, it could be inferred that stereotype threat impaired learning. Much like Cohen et al.’s (2009) work, however, Grimm et al.’s (2009) results could be due to performance aspects of the categorization task. Given these considerations, we used a visual search paradigm, because this paradigm is well developed and empirically validated, the processes involved are clearly specified in theory, and manipulations such as stereotype threat can be attributed to these processes in a relatively unambiguous fashion. We first describe visual search and then summarize the results of Rydell, Shiffrin, et al. (2010).

6. VISUAL SEARCH In visual search, a “target” object is designated prior to each trial by briefly displaying it on the screen. The task in visual search is to identify

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whether or not the target object is presented in a subsequent display of more than one object, and the participant indicates whether or not this target is or is not in the display via a keypress. After the target object is presented, a display of D objects then appears (in our case either two or four objects). On half the trials, the display contains one target and D-1 “foils” (i.e., the target is present). On the other half of the trials, the display contains only D foils (i.e., the target is absent). Accuracy of identifying the target trials is usually quite high, and reaction time (RT) as a function of D is the primary measure of learning. There are two modes of performing visual search. At one extreme is effortful, attention-demanding, search (searching one by one through each display for the presence of the target object), which is characterized by roughly linear RT functions with a large dependence on D. That is, the more foils that are present, the longer this type of search should take (e.g., it should take longer with four foils than with two foils). For this type of search, each display item is compared one at a time until a target is found, a model called serial terminating search. The comparison time per item is estimated by the “slope” of the RT function when a target is absent (e.g., if display sizes are 2 and 4, as in our studies, then half the RT difference between these two cases is the slope and therefore the estimate of the comparison time). When targets are present, they are found, on average, halfway through the comparisons, so the slope estimated in this way would be half as large. At the other extreme is a parallel, easy search with low demands for attention, characterized by a near zero slope for both target-present and targetabsent trials. That is, RTs are roughly equivalent regardless of the number of foils presented. Parallel search occurs almost instantaneously when targets and foils are very dissimilar (a situation often described as “popout”). As Schneider and Shiffrin (1977), Shiffrin and Schneider (1977), and Shiffrin, Dumais, and Schneider (1981) first demonstrated, search can initially be difficult enough to produce serial search, but a long period of training, with targets always remaining targets and foils always remaining foils (termed “consistent mapping”), gradually causes attention to be attracted automatically to targets and repelled by foils, thereby leading gradually to parallel search. Shiffrin and Lightfoot (1997) showed that a second type of learning also occurs if characters are initially unknown: Search starts with serial comparisons of multiple features within each target and foil, but each character gradually becomes unitized as a whole, so that a comparison comes to be made to

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an entire character, in one step. Both types of learning are therefore characterized by reductions in slope over training. Other types of learning also occur in search studies, such as a speedup of character identification and motor execution time. These types of learning do not affect slopes but instead the overall response time, characterized by the zero intercept of the search. The intercept values, which are calculated separately from the slope, also include any changes in overall performance not related to the two types of learning discussed earlier. Thus, slope is a relatively pure measure of learning of automatic attention, and intercept values are a combination of other potential learning processes that involve aspects of the response. It is this ability to differentiate learning from other processes that made visual search an appealing methodology to use to examine the effect of stereotype threat on learning. The trade-off, of course, is that this type of learning is relatively circumscribed. Attention attraction is learning, but it is not the type of learning most relevant to the domains of inquiry of most stereotype threat work (i.e., academic performance). We (Rydell, Shiffrin, et al., 2010) conducted three studies examining the effect of stereotype threat on the learning of automatic attention attraction in visual search. In this work, 5Chinese characters were always targets and 195 Chinese characters were always foils (consistent mapping), and D was randomly 2 or 4 on different trials. The basic study compared two groups of women, a control group not under stereotype threat and a stereotype threat group reminded at several points during the session of negative stereotypes about women’s math ability and visual ability and informed that these abilities were assessed by the visual search task. The results of our first study are summarized in Fig. 1, showing the estimates of slope for successive blocks, 400 Control condition

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Fig. 1 Learning as a function of practice in visual search.

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averaged across women in each of the two groups, combined across targetpresent and target-absent trials. Responses for women in these conditions are similar at the beginning of training, but become very different after more and more training. Women in the control condition showed a decreased slope over time, indicating learning. That is, the number of foils presented became less important to RT, the difference in RT to a two-item display vs a four-item display was greatly reduced, as the session went on. The stereotype threat group, on the other hand, did not develop attention attraction (i.e., they did not learn). Their slopes stayed relatively the same across time, showing no development of automatic attention attraction but instead a continued reliance over time on a serial search strategy (i.e., examining the items in the display one by one and maintaining the RT advantage for a two-item display over a four-item display). These search results do not fit very well with the process account provided earlier in which stereotype threat causes a general disruption of mental function. Instead, it is too much attention to the task at hand, as opposed to too little, that leads to poorer learning. In this way, they are more in line with the work on stereotype threat disrupting automated, proceduralized tasks. It suggests instead that women under threat are induced to exert more effort searching (e.g., Shiffrin, 1988), in particular continuing to use a more effortful serial search strategy throughout the session. Women in the control group apparently learn to switch to an easier automatic strategy as the targets come to automatically attract attention or become unitized. Why might stereotype threat reduce women’s ability to develop learned attention attraction in a visual search task? Women under threat may be worried about confirming negative stereotypes and put effort into proving them wrong. This might lead them to continue to utilize serial search in a fixed, predetermined order, in the hope of reducing errors. Whether it is the intolerance of errors, the intention to use a fixed serial search order, or another factor that is the key, understanding why learning is prevented is an important avenue for future research (see also Seibt & Forster, 2004). Visual search occurs so rapidly that its process components are probably not readily available to introspection, so the tolerance of errors might be a key to learning. Early in training, the process of attention attraction might be weak and inconsistent. If it is used to guide search order, this factor might either produce errors or lead to a slowing of responses. The fear of errors, or of slowing response times, or the occurrence of either, could cause women under stereotype threat to rely on more effortful and demanding serial

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comparison processes (e.g., Downey & Anderson, 1915). This idea is consistent with the view that the women under threat try harder as part of an unsuccessful attempt to improve their performance (Jamieson & Harkins, 2007). The idea that attention to targets can be inhibited is also consistent with work showing that attention to target items increases with learning but, at the same time, attention to foil items is inhibited (Shiffrin et al., 1981). We also tested the possibility that women under stereotype threat may have learned automatic attention to targets, but may have failed to express this learning. Rydell, Rydell, et al. (2010, Study 3) had participants in either a control condition or a stereotype threat condition first receive eight blocks of visual search training. Their slopes replicated the findings in our earlier studies (see Fig. 1). The participants then switched to a task judging the saturation of color patches. Superimposed on the patches were two taskirrelevant Chinese characters. In one set of trials, neither of these characters had been trained as targets. In the critical set of trials, one of the two had been trained previously as a target. If such a target had developed the ability to attract attention automatically, then one might expect some interference with the color saturation judgment. Because the superimposed characters are task irrelevant, any such interruption is presumably an automatic reaction to prior learning. This reaction would not likely be suppressed given that the superimposed characters are not relevant for the new task. As Fig. 2 shows, for the control women, for whom learning had occurred, the time to judge color saturation slowed when one of the colors had a superimposed target character (i.e., showed interference from the target character); in addition, the interference was less when the target was on the more saturated color (i.e., match trials) as opposed to the less saturated color (i.e., mismatch trials). Both effects are consistent with an account in which the superimposed target character automatically engages and attracts

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Fig. 2 Learned attention attraction as a function of stereotype threat and trial type.

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attention. For women under threat, such effects were absent, indicating no attention attraction. The control results, showing interference caused by irrelevant superimposed targets, provide strong evidence that at least some of the learning that had occurred was the learning of attention to targets. The results for the stereotype threat condition strongly suggest that these women had not learned, because it is hard to see why such learning would not be expressed in an irrelevant task. Taken together, the results of these studies show that stereotype threat prevents learning. Our findings that stereotype threat prevents learning in visual search are best explained by the hypothesis that stereotype threat leads women to try to prove the stereotype threat wrong and choose an attention-demanding search strategy that they believe will do so. Instead, this strategy seems to prevent learning that would in the long run improve performance. It is, of course, not entirely clear that this explanation is the only cause for reduction of learning due to stereotype threat, and in other task settings, learning might be harmed for other reasons. Keeping this in mind, what we found on visual search has a more general implication. Skilled performance in almost any domain operates in stages by which simpler processes are learned and automatized and then used as building blocks for subsequent stages of more skilled performance. If stereotype threat prevents the automatization of the initial stages, then the development of increased skill may not occur. In such cases, the long-run consequences are likely to be severe, as the stereotyped individuals who do not learn these basic skills will probably fall behind others. But, as mentioned earlier, this type of learning is quite basic. Most researchers interested in stereotype threat are interested in much more sophisticated forms of learning that would have an impact on learning outcomes given that more basic forms of learning have occurred, specifically learning outcomes in school. Thus, we turned our attention to examining an extremely important domain for learning in school: mathematical learning.

6.1 Stereotype Threat and Learning Math Our work in stereotype threat and learning has mostly attempted to broaden the domain of stereotype threat to situations where people acquire the skills necessary to understand mathematical concepts and execute mathematical operations, allowing them to solve difficult math problems. Mathematical skills are, obviously, learned, and it is proposed here that stereotype threat impacts the acquisition of mathematical concepts and knowledge. The

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question of whether or not experiencing stereotype threat impacts learning has not been widely examined in the literature; however, it should be an important part of why, for example, women can sometimes underperform on standardized tests. Mathematical skills are learned in environments that may often activate the stereotype that “women are bad at math,” and this has been the stereotype that we have used in all of our research on stereotype threat and learning of mathematical concepts. For example, in a college math class—the quintessential learning environment for advanced mathematics—the number of men is often greater than the number of women, which causes women to experience stereotype threat (Inzlicht & Ben-Zeev, 2000; Murphy et al., 2007). When outnumbered in math settings, women are highly physiologically aroused (Murphy et al., 2007), which may lead to decreased learning (e.g., Eysenck, 1976). Even in classrooms where the number of men and women is equal, to the extent that teachers believe that men are better than women at math, they could create threatening situations for women by how they teach math, leading to poor learning (Rosenthal, 1994). Teachers who believe and perpetuate the stereotype that “women are bad at math” would then assume that there is some truth to the stereotype, because their experience, shaped by their own beliefs, is consistent with the stereotype. Also, because most famous mathematical role models are men, and students do not perceive that there are many high achieving female mathematicians, they should be less likely to associate women with math (Dasgupta & Asgari, 2004), making women susceptible to stereotype threat (Nosek et al., 2002). The arousal, low expectations, lack of role models, and beliefs in negative math stereotypes should all make math classes and math settings threatening to women and reduce learning—even among women who are highly skilled, vigilant to the fact that their performance may serve to reinforce the negative stereotype, and worried that their behavior may actually perpetuate negative math stereotypes (e.g., by asking questions or by asking for additional help). We (Rydell, Rydell, et al., 2010) conducted several experiments to examine whether or not stereotype threat can inhibit women’s mathematical learning. The first experiment was very simple. It presented women with a new form of math in which they had to use combined symbols to determine into which equation to insert a provided value. All participants learned, via a detailed tutorial, half of the symbol combinations without stereotype threat. Then, half of the women were provided with control instructions, and half were provided with stereotype threat instructions. Finally, they learned the

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other half of the symbol combinations. We wanted to see if women under threat showed reduced learning of the symbol combinations presented after the manipulation but not before the manipulation (and, of course, relative to women in the control condition). We assessed both learning (correct recollection of which equation was to be used with particular symbol combinations) and performance (solving the recalled equations using the provided value) in this experiment. But it is important to remember, in terms of differentiating learning and performance, that women in the stereotype threat condition were under threat during performance (when recalling and solving the equations). Thus, if the effect of stereotype threat was purely on performance, women in the threat condition would recall fewer equations and solve fewer equations correctly relative to women in the control condition. However, if learning is impaired by stereotype threat, it is expected that women under threat would only show reduced learning of equations presented after the stereotype threat instructions. Indeed, that is what was seen (see Table 1). Women under threat only showed reduced learning and performance on symbol combinations presented after stereotype threat was evoked. Thus, it appears that stereotype threat inhibited encoding of the information presented after threat was evoked, because if retrieval was inhibited by stereotype threat, learning and performance would have suffered for all symbol combinations and problems. In work that was very similar to ours, Taylor and Walton (2011) focused on stereotype threat and learning by examining African American students’ ability to learn definitions under threat. In their first study, they taught African American and White participants very rare words and their definitions Table 1 The Effect of Stereotype Threat on Learning and Performance During the Recollection Task Control Condition Stereotype Threat Before Instructions

After Instructions

Before Instructions

After Instructions

Mathematical learning

0.90a

0.76a

1.20a

0.27b

Math performance

1.59a

1.55a

1.37a

0.27b

Note. Means in a row with different subscripts were significantly different at the P < 0.07 level. The range of scores for mathematical learning was 0–4 both before and after the instructions, whereas the range of scores for math performance was 0–8 both before and after the instructions.

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either under threat or not. They brought participants back to the same testing room 2 weeks later and asked them to define half of the words during a low stakes “warm-up” test and half of the words during a high stakes, threatevoking test. Consistent with stereotype threat performance effects, they showed that African American participants, but not White participants, in the no-threat control condition during learning showed similar recall on the warm-up test but reduced recall on the high stakes test. Consistent with stereotype threat learning effects, they showed that African American participants under threat when learning showed poor recall on both the warm-up test and the high stakes test, whereas White participants performed well on both tests. The African American participants’ performance on the warm-up test was presumably indicative of poor learning, whereas their performance on the high stakes test was due to performance and/or learning. In Study 2 of Rydell, Rydell, et al. (2010), we moved away from memory tests like our symbol combining task or Taylor and Walton’s (2011) vocabulary test to an actual math task that was previously used in stereotype threat work in this domain. This was done to examine the extent to which stereotype threat can affect women’s mathematical learning with a task that has the qualities of math (e.g., it is internally consistent). In this experiment, we used modular arithmetic (MA). More specifically, we used MA with a binary modulo operation, which means that the mod operation in these problems indicates whether the equation is valid (true) or invalid (false). MA is a relatively simple yet obscure math task, thus one that most participants must learn, which involves determining if a math equation with three whole numbers is true (i.e., the answer is a whole number) or false (i.e., the answer is not a whole number). In MA, an equation that takes the form of a ¼ b (mod c) [e.g., 9 ¼ 3 (mod 2)] is solved by subtracting b (3) from a (9) and then dividing the solution of a  b (6) by c (2). Because in our example problem 6 (the solution of a  b) divided by 2 (c) equals a whole number (3), the correct answer is true. If one solved the equation 9 ¼ 3 (mod 4), the correct answer would be false because 9  3 ¼ 6 and 6  4 ¼ 1.5, which is not a whole number. In past work with stereotype threat and MA, Beilock et al. (2007) manipulated stereotype threat after women had learned how to solve MA problems (i.e., learning could not have been affected by stereotype threat) and varied the difficulty of MA problems. Beilock and colleagues’ research showed that because stereotype threat performance effects are dependent on reduced working memory capacity, stereotype threat only reduced women’s performance on difficult problems that required more working memory

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(i.e., problems with large numbers and a borrow operation—transferring digits from one column to another in subtraction), whereas easy MA problems that required almost no working memory (i.e., problems with smaller numbers that did not need a borrow operation) were immune to performance-related stereotype threat effects. We assumed that any performance decrements on easy MA problems would be due to difficulty encoding the mathematical operations necessary to complete MA problems and not due to stereotype threat-based performance effects, because their successful completion does not tax working memory. We assumed that presenting stereotype threat before learning would reduce women’s ability to encode the mathematical rules and operations necessary to solve MA problems. However, presenting stereotype threat after learning would not affect encoding of the operations necessary to complete MA, but instead only inhibit performance on difficult MA problems (replicating Beilock et al., 2007). Given that easy MA problems are immune to stereotype threat-based performance decrements, deficits on these problems were used to demonstrate stereotype threat-based learning decrements. If people have learned how to solve MA problems (i.e., stereotype threat is presented after learning), they should be able to solve easy MA problems regardless of whether or not they are experiencing stereotype threat, because the math involved in these problems is so rudimentary that it can be solved even when women are under threat (e.g., Beilock et al., 2007; O’Brien & Crandall, 2003; Spencer et al., 1999). If people have not learned how to solve MA problems (i.e., stereotype threat is presented before learning), however, they should not be able to solve as readily easy MA problems, because they would not have properly encoded how to complete these problems. Because performance on difficult MA problems should be poor under stereotype threat, lower performance was expected on difficult MA problems in the stereotype threat condition than in the control condition, regardless of when stereotype threat was presented. These predictions were borne out by the data. Women who received stereotype threat instructions before learning how to complete MA problems performed more poorly on easy MA problems than those who were given stereotype threat instructions after learning or women in the control conditions (see Fig. 3). Consistent with Beilock et al. (2007), those under threat, regardless of when it was given, did worse on difficult problems than those in control conditions. Further, those who received stereotype threat before learning were also more likely to show poorer learning by incorrectly

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1 0.9 0.8 Control

0.7

Stereotype threat

0.6 0.5 Before After Before After learning learning learning learning Easy problems Difficult problems

Fig. 3 The effect of stereotype threat on math accuracy as a function of problem difficulty and placement of the stereotype threat manipulation.

defining “mod” and by having more difficulty recalling the proper steps to solve MA problems than those who received threat after learning. In our third study (Rydell, Rydell, et al., 2010), we examined the detrimental effect of stereotype threat on learning an abstract symbolic logic task that utilizes several mathematical principles (e.g., Kaminski, Sloutsky, & Heckler, 2008). This task is based on logic and uses complicated mathematical reasoning. We chose to use this abstract symbolic logic task, where the goal is to decipher hieroglyphics from a language that uses three symbols (diamond, circle, and flag; see Kaminski et al., 2008), because the mathematical principles that underlie this task can be applied to novel tasks. Namely, it allows people’s learning to be assessed differently, by measuring their ability to apply the abstract knowledge from the focal task (i.e., the learned, hieroglyphics task) to a transfer task (i.e., a task using the same mathematical principles as the focal task, but for which there was no task-specific learning). In this case, the transfer task was a child’s pointing game in which participants were asked to predict the outcomes of the game. In the game, one child pointed to certain objects, and given the objects that the child had already pointed to (which were provided), participants had to guess the final object that child would choose. The three objects (i.e., the three elements of the task) were directly equivalent to the elements from the focal task: a broach (diamond), a bottle (circle), or a ring (flag). Other than being told that the two games were similar, participants were not given any specific instructions about the rules of the transfer task. Research indicates that learning abstract concepts results in more elaborative representations of learned knowledge (e.g., Gick & Holyoak, 1983; Novick & Holyoak, 1991), and this more elaborate knowledge increases people’s ability to apply or transfer this knowledge to novel domains

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(e.g., Catrambone & Holyoak, 1989; Goldstone & Sakamoto, 2003). Kaminski and colleagues (2008) showed that learning mathematical principles based on abstract examples led to high levels of transfer from one task to another, with relatively small transfer deficits (i.e., almost the same level of learning was displayed on the focal and transfer tasks). We utilized this methodology to determine if stereotype threat, in addition to reducing initial mathematical learning with abstract examples (i.e., on the focal task), would also inhibit transfer of the learned mathematical rules (provided in the focal task) to a new task using a learning paradigm that also utilized abstract examples (i.e., the transfer task). In our study, both men and women’s mathematical learning and ability to transfer mathematical learning to a new domain were assessed. Because no stereotype threat was expected for men, their ability to learn or transfer the mathematical principles on the abstract logic task should not be affected by the threat manipulation. However, women in the stereotype threat condition were expected to show lower levels of focal task learning than women in the control condition, and this difference was expected to be amplified for the transfer task where initial learning had to be applied to a new task. This study also included an associative measure of learning to assess learning without relying on mathematical performance. An association in memory was expected between the symbols that were linked together by the rules of the focal task. The associative measure of learning, therefore, compared the extent to which people associated abstract symbols that were linked together by the rules of the focal task with the extent to which people associated abstract symbols that were used in the focal task but not linked together by the rules of the task (see Rydell, Rydell, et al., 2010, for more details). We expected weaker associations between symbols that were linked by the rules for women under threat than for women in a control condition or men (i.e., less elaborated schematic knowledge about the focal task). As Fig. 4 shows, stereotype threat reduced women’s, and not men’s, ability to learn an abstract task that was based on mathematical principles (i.e., the focal task). Stereotype threat also inhibited women’s ability to transfer knowledge they had gained about the focal task to the transfer task, producing even greater stereotype threat effects for women on the transfer task than on the focal task. In addition, women had weaker associations between symbols that were part of the same rule in the stereotype threat condition than in the control condition, whereas men showed no differences in associative learning as a function of the stereotype threat manipulation. Additionally, the impact of gender and stereotype threat on transfer task learning was

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Accuracy (% correct)

1 0.9 0.8 0.7 Control

0.6

Stereotype threat

0.5 0.4 0.3 Focal task Transfer task Focal task Transfer task Men Women

Fig. 4 The effect of stereotype threat on learning as a function of gender and task type.

accounted for by focal task learning and associative learning. This pattern of mediation suggests that reduced learning of the transfer task relative to the focal task for women under threat was due to reduced encoding of the mathematical principles necessary to complete the focal task. These results support the conclusion that stereotype threat reduces mathematical learning and are relatively difficult to explain with a purely performance-based account of stereotype threat effects.

6.2 A Process Model for Stereotype Threat-Based Learning Decrements Aside from showing that stereotype threat can inhibit learning in the threatened domain, there has been little attempt to understand the process through which these learning decrements occur. As noted earlier, we (Rydell, Shiffrin, et al., 2010) have argued that reduced perceptual learning via inhibiting attention attraction occurred because those under threat were more likely to continue to exert effort in an attempt to disconfirm the stereotype. This effort seemed to backfire, because it did not allow those under threat to automate their performance; instead, for whatever reason, they continued to rely on effortful visual search, which interfered with attention attraction. We also demonstrated that stereotype threat reduces the encoding of mathematical operations and principles (i.e., reduces learning; Rydell, Rydell, et al., 2010); however, we did not examine why stereotype threat reduced encoding. What are the specific processes that hurt the encoding of mathrelated information when women are under threat? We now discuss this issue and present a model of how stereotype threat can inhibit the encoding of complex information, in an attempt to spur future research in this area.

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We propose that the impact of stereotype threat on encoding during learning is due to failures of vital functions of either motivation (Major, Spencer, Schmader, Wolfe, & Crocker, 1998; Steele, 1997) or the central executive (working memory) that are necessary for learning (see Engle, 2002). As reviewed earlier, converging lines of research have shown that when women experiencing stereotype threat have reduced levels of working memory capacity (i.e., the ability to mentally comprehend and represent the current environment in order to solve problems and approach goals), their ability to perform is reduced (e.g., Beilock et al., 2007; Schmader & Johns, 2003). The proposed model of how stereotype threat impairs encoding during learning draws heavily on models of stereotype threatbased performance effects. These performance models assume that people typically view themselves positively and want to maintain this view of the self (Schmader et al., 2008). In these models, women’s reduced performance in math in response to stereotype threat effects can occur due to: (a) cognitive imbalance that occurs when women’s positive sense of self-esteem is inconsistent with the expectation that their ingroup lacks ability in a given performance domain (Nosek et al., 2002; Schmader et al., 2008) or (b) women becoming disengaged from the domain of math and withdrawing the effort needed to perform well (Major & Schmader, 1998; Steele, 1997). As reviewed earlier, cognitive imbalance activates a psychological stress response (e.g., Blascovich, Spencer, Quinn, & Steele, 2001) and a monitoring process (i.e., searching the environment for stereotype-related information; see Murphy et al., 2007) that ultimately reduce the working memory resources needed to solve difficult math problems (see Schmader et al., 2008). Taylor and Walton (2011) provided some correlational evidence that stereotype threat may inhibit learning by making stereotype suppression difficult and reducing attempts to maximize performance, which would be generally consistent with this mechanism. On the other hand, women who are disengaged from math do not experience cognitive imbalance, because their selfesteem is not contingent upon math performance (Steele, 1997). Nonetheless, women disengaged because of stereotype threat should not perform well in math, because they are disinterested or lack the motivation to perform well, not because of reduced working memory resources caused by cognitive imbalance. When these findings from the stereotype threat performance literature are applied to mathematical learning, they predict two distinct processes through which stereotype threat can lead to reductions in learning that

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are determined by stereotyped individuals’ motivation to learn math. When potentially negatively stereotyped individuals are motivated to learn math, stereotype threat should lead to increased worry about confirming the stereotype, increased arousal, and increased monitoring, thereby reducing the working memory resources devoted to learning mathematical material. Lack of working memory resources should lead to poorer encoding of mathematical rules and operations being learned (Unsworth & Engle, 2005). However, when women are not motivated to learn math, experiencing stereotype threat may lead them to disengage from information related to the domain of mathematics, reducing the extent to which they attend to and therefore encode information presented about mathematical rules and operations. When encoding is reduced via either of these two processes, math performance should suffer, because these poorly encoded rules and operations are needed to solve complex math problems.

6.3 Using Feedback When Under Stereotype Threat In the model we just presented, learning is very simple, straightforward, and circumscribed. It is a model of learning that occurs before any feedback is provided (or with no feedback). Learning is usually cyclical. People learn, people perform, and people receive feedback about their performance. This cycle is repeated over and over. Therefore, feedback is essential to the learning process. Positive feedback reinforces our learning by noting what we currently understand and can practice, whereas negative feedback signals what we have yet to master and need to work on to improve. By seeking, valuing, and acting upon feedback, we can learn more quickly, deeply, and fully. However, the experience of stereotype threat can shape when we obtain feedback, how we view it, and how we use it when learning and applying this new knowledge. At the most basic level, our working model of feedback’s impact on learning and performance proposes that students under threat approach subsequent learning tasks in the stereotyped domain differently depending on whether they receive positive or negative feedback. When students receive positive feedback under threat, they can focus their attention more on the novel tasks, persist longer during learning to make sure they understand the tasks, and thus encode the rules necessary to perform the tasks well. However, when students receive negative feedback under threat, they will likely not focus as much attention on the novel

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tasks and may not persist during learning, especially if the task is difficult. This reduced attention and persistence will likely lead to problems encoding the rules of the novel tasks, thereby making performance on that task more difficult (Rydell, Rydell, et al., 2010). In addition to performance feedback on the initial tasks, perceived learning and expected performance on the subsequent tasks should also lead to increases or decreases in domain interest as a function of feedback: positive feedback should increase interest, and negative feedback should undermine it. Fig. 5 presents our model, including feedback effects. In this section, we review research that directly or indirectly supports this model and additionally point out situations in which feedback may not be received at all or when positive or negative feedback has the opposite impact as our model’s predictions. Although the reviewed research rarely examines the full learning process (i.e., learning, getting feedback, reaction to feedback, and subsequent interest, motivation, and performance) within one study, the pattern of results across studies suggests that feedback can invoke a recursive process, where motivating feedback can result in better later learning and performance, and demotivating feedback can lead to negative, snowballing effects on these important academic outcomes. This work also highlights psychological factors that can moderate or amplify the impact of feedback. We will discuss three factors. The first is stigmatized individuals’ identification with the stereotyped domain. As Steele (1997) outlines, for students to be motivated to achieve success in negatively stereotyped domains, they must perceive that being someone who is good in this domain is an important part of who they are or how they define themselves. It follows that if a domain is important to students, they will feel good when they experience successes and bad when they experience failures in the domain. Only those for whom this domain is an important part of their

Subsequent learning

Performance feedback Negative feedback

Decreased motivation and persistence

Decreased attention

Decreased learning/ perform

Decreased STEM interest

Positive feedback

Increased motivation and persistence

Increased attention

Increased learning/ perform

Increased STEM interest

Stereotype threat

Fig. 5 Stereotype threat, feedback, and subsequent math learning and interest.

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self-concept (e.g., highly math identified women) will make a sustained effort to learn to master skills in this domain. However, people do not include just any performance domain into their self-concept. Research on self-esteem (e.g., Crocker & Major, 1989; Tesser, 1988) and Social Identity Theory (Turner & Tajfel, 1986) has shown that people want to avoid performance or skill domains where they obtain negative self-relevant outcomes (e.g., women who perform poorly might psychologically disengage with the domain of math so that outcomes in that domain no longer impact perceptions of self-worth) and approach performance domains where they obtain positive self-relevant outcomes (e.g., women who perform well might psychologically engage or increase the extent to which outcomes in math affect perceptions of self-worth). What happens when students confirm (receive negative feedback) or disconfirm (receive positive feedback) negative stereotypes about their group? It is proposed that when students perceive that they have disconfirmed negative group stereotypes, they will feel good about their achievement, come to value the domain more, and integrate this domain into their self-concept, because it serves as a source of positive feelings about the self (e.g., Crocker & Major, 1989; Steele, 1988, 1997). Further, students who perform well may also come to value the domain more, because it showcases a personal attribute that is valued by others (e.g., Tesser, 1988). When students under threat are led to believe that they have performed poorly, however, they should be more likely to devalue the domain, because performance in this domain has served to reduce both their collective and personal self-esteem by confirming negative ingroup stereotypes and by decreasing their perceived ability (e.g., Crocker, Major, & Steele, 1998; Major et al., 1998; Major & Schmader, 1998; Steele, 1997). Thus, students under stereotype threat who believe they performed well should increase their identification with the domain, and those who believe they performed poorly should disidentify from the domain. A second important factor is somewhat similar to the first: people’s perceptions of belongingness or fit in the domain (see Cohen & Garcia, 2008; Murphy et al., 2007). Negatively stereotyped individuals are often unsure about whether or not they belong in the stereotyped domain—a phenomenon known as belonging uncertainty (see Walton & Cohen, 2007). People become more interested in putting forth effort and pursuing careers in stereotyped domains when they are made to feel that they belong in this domain—that is, when belonging uncertainty is diminished (Cohen & Garcia, 2008). Within the framework of recursive beneficial and detrimental

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processes, it is expected that receiving positive feedback, especially in the face of stereotype threat, will increase perceptions of belongingness and reduce uncertainty about whether students do or do not “belong” in stereotyped settings. Students who receive positive feedback when under threat should be more motivated to learn and achieve in stereotyped domains and should attend more to learning skills in subsequently presented tasks. The situation for threatened students who receive negative performance feedback should be quite different. The perception that they might not belong in stereotyped domains will be quite salient due to stereotype threat, and this perception as well as the stereotype will be confirmed by negative feedback. This will lead them either to feel even more uncertain as to whether they belong in the domain or to conclude that they do not belong. Either way, this perception should reduce their motivation to learn new skills, reduce their attention to learning a new task, and undermine their interest in careers in these domains. Given that students provided with negative feedback will not learn subsequent skills very well, it is likely that they will perform poorly on similar tests in the future. This poor performance should reinforce their feelings that they do not belong in the domain, further reducing their motivation to achieve. Lastly, a third important factor is the endorsement of negative group stereotypes. It is expected that students’ successes will provide them with evidence that these stereotypes are incorrect. To the extent that students are less likely to believe negative group stereotypes, they should be more motivated to learn new skills and knowledge and to encode information during learning. This should lead to further successes that will degrade stereotypic beliefs and facilitate beneficial recursive processes, allowing for sustained high levels of performance and learning. What is more, to the extent that stereotypic beliefs are reduced, students may be more likely to show sustained interest in careers in the stereotyped domain. When students receive negative feedback on a task when experiencing stereotype threat, they are unlikely to interpret this feedback as implying that they alone are bad at tasks in the domain. Instead, it makes more sense that they would perceive their poor performance as indicative of their group’s level of ability. To the extent that students can buffer the personal impact of negative feedback by making their performance due to a group level issue, they may be able to avoid negative emotional and cognitive outcomes that would normally occur upon failure (see Crocker & Major, 1989). This strategy may be effective in the short term, but it may be problematic over time. Increased belief in the validity of the negative group stereotypes will likely

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reduce motivation to learn and will likely lead them to display decreased attention during subsequent learning. Thus, one reason that perceived failure in stereotyped domains when under threat may lead students to begin a detrimental recursive process is that this initial failure may set the stage for the acceptance of negative group stereotypes. Belief in the validity of these stereotypes may negatively impact future performance in the face of threat (e.g., Kiefer & Sekaquaptewa, 2007), providing more information that will drive this detrimental recursive process. Taken together, our model of feedback’s role in learning identifies the psychological processes invoked by feedback, pinpoints the mechanisms that are responsible, at least in part, for sustaining these processes, and posits who might be most vulnerable to a negative recursive cycle when receiving negative feedback while experiencing stereotype threat. With these predictions and mechanisms laid out, we now turn to a review of past research on feedback for stigmatized individuals that sheds light on various pieces of our model.

7. SEEKING FEEDBACK WHEN EXPERIENCING STEREOTYPE THREAT A basic question to answer is: Do stereotyped individuals actively attempt to receive feedback? Unfortunately, very few studies have examined the feedback-seeking behaviors of individuals in stereotype-threatening situations. One such study explored feedback seeking by African American managers in the workplace (Roberson, Deitch, Brief, & Block, 2003). Results showed that those who were the only person of their race in their work group reported greater stereotype threat concerns, and these concerns predicted greater indirect feedback seeking. Instead of directly asking one’s manager or peers about one’s performance, indirect feedback seeking involves observing others’ behaviors and paying attention to informal remarks in order to infer one’s performance. This form of feedback seeking may be less effective and more time-consuming than directly seeking feedback, so it could be potentially problematic for those experiencing stereotype threat, who may already be cognitively taxed. In addition to differences in what and how feedback is sought, people experiencing stereotype threat may try to avoid receiving any feedback. Given that people avoid feedback about their own biases (e.g., Howell et al., 2013), individuals under stereotype threat may also be avoidant of negative feedback that denotes they have confirmed the negative stereotypes of

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their group. Even if people experiencing stereotype threat do not avoid feedback completely, they may select tasks where the feedback is likely to be positive, or where negative performance can be dismissed as not convincingly confirming group stereotypes (e.g., Crocker & Major, 1989). For example, people experiencing stereotype threat may choose easy over challenging tasks or select a very difficult task where poor performance would be expected for many students irrespective of group memberships (Good, Aronson, & Inzlicht, 2003).

8. HOW FEEDBACK IS PERCEIVED WHEN STEREOTYPIC EXPECTATIONS ARE SALIENT When members of negatively stereotyped groups are uncertain about their ability and efficacy in the stereotyped domain, they can rely more on provided performance feedback and view this feedback through the lens of salient group stereotypes. Specifically, Correll (2001) found that women weighted performance feedback more heavily in their self-assessments of math ability and looked to societal expectations (e.g., stereotypes) when they were less confident in their judgments. Additional evidence from Roberts and Nolen-Hoeksema (1989) shows this pattern for women receiving both positive and negative evaluative feedback, with negative feedback in particular being seen as containing more relevant information about their abilities. Men’s ability self-assessments were generally less affected by negative evaluative feedback than women’s. To demonstrate how performance feedback is perceived in reference to negative group stereotypes in the domain, Biernat and Danaher (2012) presented women and men with the same negative subjective performance feedback and found that women, compared to men, saw their feedback as indicating that they had objectively worse performance. A similar result was found when examining the reactions of Black and White participants upon completing a writing task and receiving negative subjective feedback on it. In turn, these self-perceptions of performance were associated with lowered importance (i.e., devaluation) of the negatively stereotyped domain reported by women and Black participants. How might negative performance feedback come to be weighted more heavily and have greater influence on outcomes in the stereotyped domain? Research from a social neuroscientific perspective provides insights into this process for individuals experiencing stereotype threat. In stereotype-threatening situations, there is a neural attentional bias

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toward negative feedback (Forbes & Leitner, 2014). Women who received feedback on math problems while under stereotype threat showed biased attention toward negative feedback that they might be confirming group stereotypes with their performance (as evidenced by several indices from the continuous recording of EEG activity while they completed the math task): they showed enhanced attentional processing and increased power in and coactivation of neural networks responsible for our ability to pay attention and utilize working memory resources. This attentional bias then contributed to the underperformance of these women under stereotype threat. The greater focus on negative feedback when under stereotype threat can also result in more extensive encoding of this feedback. As an indirect consequence of this better encoding, memories of past performance may become biased toward negative feedback, such that in future stereotypethreatening situations, stereotype-confirming experiences may be more salient. In a careful test of this prediction, women and men received feedback on a math task under either stereotype threat or nonthreatening conditions (Forbes, Duran, Leitner, & Magerman, 2015). This feedback indicated either that an error was made or that the response was correct and was given in different fonts. In order to assess the extent of the encoding of the feedback, participants were given a surprise memory test for feedback fonts they had seen during the math task. From this memory test, Forbes et al. (2015) found that women experiencing stereotype threat encoded the error feedback better than correct feedback, which was a tendency not seen with women not under threat or men in either condition. This encoding difference mediated stereotype threat-based performance decrements and elevated anxiety after the performance task. Extending the impact of this attentional bias to learning, Mangels et al. (2012) examined how greater attention to negative feedback curtails the use of a helpful tutorial and, therefore, impairs learning. Specifically, women completed a math test under stereotype threat or no threat, and while completing the test, they were presented with accurate feedback and offered access to a tutorial on the steps to solving problems included in the test. On a surprise retest of the material a day later, women’s greater focus on failure feedback in the stereotype threat condition predicted less usage of the tutorial and poorer learning of what information was explored in the tutorial compared to women in the nonthreatening condition. Taken together, these studies indicate that negative feedback plays a critical role in orienting stereotype-threatened individuals’ attention and in the

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weighting of stereotypic information in judgments of ability, which can result in both poorer learning and performance outcomes.

9. DISCOUNTING PERFORMANCE FEEDBACK AND DEVALUING THE PERFORMANCE DOMAIN Although we see that negative feedback is detrimental in past work and as proposed in our model, responses to performance feedback can be varied. Individuals can view the feedback as diagnostic to their actual level of performance; however, when stereotypic expectations are salient, individuals may view the performance feedback with suspicion of bias. In a seminal paper by Crocker, Voelkl, Testa, and Major (1991), Black students differentially attributed feedback to prejudice based on its valence and if the evaluator was aware of the students’ race. Black students made greater attributions to prejudice after negative feedback than positive feedback and when the evaluator could see them than when the evaluator could not see them. Although negative feedback was more greatly discounted as due to prejudice than positive feedback, positive feedback was still viewed with some suspicion when the evaluator was aware of the students’ race, potentially because this positivity could be viewed as a response by the evaluator to appear nonprejudiced. This pattern of feedback discounting when attributional ambiguity exists has been consistently documented (e.g., Coleman, Jussim, & Isaac, 1991; Lawrence, Crocker, & Blanton, 2011), and additional research suggests that feedback discounting might be well placed at times. When evaluators are concerned about appearing racist or playing into stereotypes, they can withhold essential constructive feedback (e.g., Croft & Schmader, 2012) and may not warn students about potential academic difficulties in coursework (e.g., Crosby & Monin, 2007). As another wrinkle in the proposed differences for outcomes following positive and negative feedback, work from our lab suggests that not all positive feedback motivates learning. Particularly, we find that women under stereotype threat can discount positive performance feedback (Boucher, Rydell, & Hirt, 2017). Women were randomly assigned to a stereotype threat or control condition before taking a difficult math test. After completing this task, they were randomly assigned to receive no feedback, negative feedback, or positive feedback on this initial math test. They were then presented with a second math test (for which they had to learn how to complete the problems presented), and math accuracy was assessed for this critical performance following feedback. For women experiencing stereotype threat,

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subsequent performance was lower when positive feedback was provided than when negative feedback was provided, whereas for women not under stereotype threat, the pattern flips such that positive feedback was motivating and resulted in greater math accuracy on the second math test than negative feedback. Subsequent performance when no feedback was provided tended to fall between performance for those in the two feedback conditions, although the comparisons were not consistently significant. Follow-up studies demonstrated that the discounting of positive feedback under stereotype threat likely occurred because women in this condition assumed that the strong performance was in relation to other women (i.e., they were the best of the negatively stereotyped group). Moreover, we have evidence that this comparison was demotivating, as women under threat who received positive feedback in relation to other women spent less time on learning how to complete the second math task and reported more possible excuses for their subsequent performance than women under threat who received positive feedback in relation to men. These findings point to how effort reduction and self-handicapping can result from some forms of positive feedback instead of increased motivation and effort. Discounting feedback is linked to devaluing of the performance domain, as both motivations allow for a buffering of self-esteem by disengaging one’s self-worth from the once valued performance domain. In an illustrative example of this process, Fogliati and Bussey (2013) randomly assigned male and female participants to a stereotype threat or control condition and then presented them with a math test; participants received positive or negative performance feedback on this test and, following this feedback, rated their self-esteem and noted their likelihood of attending a free mathematics tutorial. Not only did women under stereotype threat perform worse after receiving negative feedback on the math test, they were less motivated to improve, as reflected in their reduced interest in attending the free math tutorial. As one important, positive consequence, women’s self-esteem was buffered when receiving negative feedback such that there were no significant differences with women in the other conditions. This study suggests that negative performance feedback can be demotivating, such that additional learning and practice may be less likely to occur following it. The negative consequences of stereotype threat for learning and performance can accumulate, such that frequent feedback discounting and domain devaluing can lead to disengagement (e.g., Crocker et al., 1998; Major et al., 1998). As documented in Major et al. (1998), the self-esteem of African American students was relatively unaffected by negative performance

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feedback, especially for individuals who had become chronically disengaged from tests of intelligence. In this way, individuals from negatively stereotyped groups can start to distance themselves from the stereotyped domain or uncouple performance within it from one’s self-esteem. Drops in interest and performance in school in general and in the more difficult subjects of math and science can be a consequence of this disengagement and disidentification with academics and particular disciplines. Although schooling continues through young adulthood, disengagement and disidentification due to chronic stereotype threat early on could be an obstacle for future learning and performance in negatively stereotyped domains.

10. HOW FEEDBACK CAN IMPROVE OUTCOMES UNDER STEREOTYPE THREAT As noted earlier, feedback, especially negative feedback, can invoke disengagement processes that often lead to negative consequences for learning and performance. However, negative feedback can sometimes prompt a form of situational disengagement that can maintain and even increase motivation for future tasks. In a study by Nussbaum and Steele (2007), White and Black participants were presented with an anagram task described as being either a diagnostic of one’s academic ability (i.e., the stereotype-threatening condition) or a nondiagnostic, warm-up activity (i.e., the nonthreatening condition). The task was the same for all participants, and after completing it, participants received their score on it. Since the task was difficult, participants did rather poorly, so the feedback they received was negative. Next, participants were allowed to choose the problems to complete in an ostensible second test: choosing how many of the 20 questions would be similar anagrams or analogies; how many anagram questions were chosen served as the index of persistence. Participants did not complete the second test. Compared to White participants in either task-framing condition and to Black participants completing the nonthreatening task, Black participants who received negative feedback on the ability-diagnostic task reported the greatest disengagement, which paradoxically predicted greatest task persistence. This pattern suggests that people can temporarily suspend their identification with the threatening task and leverage this to inspire greater motivation for subsequent performance. Receiving positive feedback when experiencing stereotype threat is often beneficial; although if its veracity and intent are uncertain and consequently discounted, positive feedback can be demotivating. Generally,

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positive performance outcomes can increase individuals’ engagement of their self-esteem in the negatively stereotyped domain when experiencing threat, and this greater engagement can lead to increases in self-esteem and better performance on subsequent tasks in the same domain (Leitner, Jones, & Hehman, 2013). These two papers (Nussbaum & Steele, 2007; Leitner et al., 2013) demonstrate that situational disengagement or engagement can be beneficial in translating performance feedback into motivation that can potentially mitigate threat’s impact on important outcomes like learning and performance. A second way to utilize feedback to mitigate stereotype threat is to focus upon the content of the feedback itself, particularly what it signals about the beliefs of evaluators of the performance. In “wise feedback” interventions, instructors who communicate that negative group stereotypes will not play a part in their evaluations reduce the impact of stereotype threat for students. Providing critical performance feedback that indicates that the evaluator is providing this feedback because he/she believes the student can reach his/her high standards neutralizes concerns about the evaluator viewing the student in light of negative group stereotypes. By eliminating the motivation to discount the feedback and the concerns about confirming stereotypes, “wise feedback” increases task motivation (e.g., Cohen, Steele, & Ross, 1999; Treisman, 1992). Recent interventions by Yeager, Purdie-Vaughns, et al. (2014) replicated these findings and showcased the impact of teachers’ “wise feedback” on persistence, learning, and performance. Seventh graders who received “wise feedback” from their teachers were more likely to submit a revision of a class essay and turned in better final drafts of this assignment. These effects were stronger for students from negatively stereotyped groups and for those who had the greatest mistrust for their teachers and school in general (i.e., the students most vulnerable to thinking they will be viewed in line with negative stereotypes). Training students to view all feedback from their teachers as “wise feedback” could go a long way toward mitigating the impact of stereotype threat on important psychological processes involved in successful learning.

10.1 Eliminating Learning Deficits Due to Stereotype Threat: Applying Our Knowledge As noted in the opening to this chapter, the process of how stereotype threat unfolds to impair performance has been well researched and documented (e.g., Schmader et al., 2008). Moreover, there have been analyses of archival

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data to delineate the contribution that stereotype threat plays in known achievement gaps (e.g., Danaher & Crandall, 2008; Walton & Spencer, 2009). Less is known, however, about how stereotype threat influences every day learning experiences. Here, we highlight specific efforts to eliminate learning deficits due to stereotype threat and point to indirect evidence of how applying the knowledge from work on performance outcomes could be beneficial in a learning context. These findings come from lab experiments as well as social psychological interventions conducted in the field. Each of these strategies is effective because it taps into psychological motivations and promotes a more adaptive construal of threatening situations and a more active response to them (e.g., Walton, 2014; Yeager & Walton, 2011).

11. REMOVING CUES TO STEREOTYPE THREAT IN THE LEARNING ENVIRONMENT In one of the few direct tests of how stereotype threat-based learning decrements can be mitigated, we provided men and women with stereotype-threatening or nonthreatening information before learning a novel math task (Boucher et al., 2012). For those under stereotype threat, some participants had their threat concerns alleviated by the presentation of information that the tasks that they would complete were “gender fair”; those experiencing stereotype threat either got this buffering information before learning, after learning but before assessment, or not at all. The “gender fair” information only buffered learning for female participants who received this information prior to learning. Men’s learning was unaffected by condition. For those targeted by the negative group stereotype (i.e., women in math here), the effectiveness of strategies to reduce learning decrements importantly depended on its timing. To further demonstrate the deleterious influence of stereotype threat-based learning decrements, we (Boucher et al., 2012) presented all participants with a second math task, one that assessed the transfer of learned information from the first task to a related one (the same transfer task used by Rydell, Rydell, et al., 2010, as described earlier). As depicted in Fig. 6, the pattern of results from the initial learning task was even stronger for transfer of the learned information, with women who received “gender fair” information showing greater transfer than women in the other conditions. These findings, thus, showcase how a manipulation that has been previously shown

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Accuracy (% correct)

1 0.9 0.8 0.7 0.6

Focal task

0.5

Transfer task

0.4 0.3

Men Women Men Women Men Women Men Women Control

ST

GF before learning GF after learning

Note:ST = stereotype threat; GF = gender fair manipulation

Fig. 6 Focal task learning and the ability to transfer as a function of gender and stereotype threat/gender fair condition during learning.

to reduce stereotype threat-based performance deficits can also reduce learning decrements if the timing is right within the process of learning. “Gender fair” information about an evaluative task is one cue to reduce learning disparities due to stereotype threat. In addition to focusing on the perceived bias or fairness of evaluations, learning under stereotype threat could be buffered by reframing people’s reactions to the anxiety they experience while trying to learn. Although the link to learning has yet to be tested to our knowledge, training people to reappraise stress and anxiety while experiencing stereotype threat leads to improved performance (e.g., Jamieson, Mendes, Blackstock, & Schmader, 2010). Individuals are trained to view the negative affect and thoughts as motivation to do well instead of signs of failing or personal weakness. Connecting the anxiety specifically to one’s negatively stereotyped group identity when learning about stereotype threat can also result in better performance (Johns, Schmader, & Martens, 2005). Such reappraisal of the source and function of stress and anxiety could be potentially beneficial in learning contexts, especially in ones where the material is difficult and the response to experiencing difficulty could be construed as a natural one and not one exclusively due to threat. Another situational cue that holds promise as a means to eliminate stereotype threat-based learning deficits is group representation in the academic setting. It is important to consider who else is in the room learning alongside students who face stereotype threat. Solo status, or being the only member from one’s group present, impairs learning of facts relative to nonsolo status (Sekaquaptewa & Thompson, 2002). Specifically, when

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men and women learned facts believing that they were the only person of their gender in their group, they had poorer recall of learned facts, even if they later retrieved and used this knowledge in a setting in which their group was better represented. This study highlights the need to work toward better representation of underrepresented groups not just in performance situations but in learning settings as well. Group membership is a visible cue to stereotype threat in negatively stereotyped domains; a less visible but similarly critical dimension to consider is the ability levels of classmates and peers. In a multipronged effort to increase women’s representation in computer science, a discipline where disparities and stereotypic expectations continue to exist, Harvey Mudd College revised their introductory computer science course and placed students into sections based on their previous experience with computing. In this way, students who did not have much previous exposure or opportunities to engage in computing were able to learn about the field and programming basics without salient in-class comparisons with students who had more extensive practice and expertise. Given that painful comparisons to those who appear much better at the subject than you may be more accessible for those who come from negatively stereotyped groups, this strategy from Harvey Mudd College could reduce threat’s influence in the classroom. Indeed, evaluations of their changes show that in 5 years, Harvey Mudd College was able to increase their percentage of women graduating in computer science from 12% to 40% (Alvarado, Dodds, & Libeskind-Hadas, 2012; Alvarado & Judson, 2014).

12. CHANGING THE CONTENT AND PEDAGOGICAL APPROACH TO FOSTER BETTER LEARNING OUTCOMES A different, complementary focus on reducing stereotype threat’s effects on learning is from the teacher’s perspective. Interests and goals are key motivational components to students’ academic success (e.g., Hidi & Harackiewicz, 2000), but inspiring and maintaining motivation can be difficult, especially when students are experiencing stereotype threat (e.g., Smith, 2004; Thoman, Smith, Brown, Chase, & Lee, 2013). Providing course content in a manner that allows for personal connections to the material and structuring the learning time to engage students more actively can leave less room for negative group stereotypes to play a role in academic achievement by harnessing interest and motivation in adaptive ways.

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Relevant content and activities can take multiple forms: they can involve applying knowledge to real world problems, linking learning to personal experiences, and understanding the importance of knowledge and skills for future goals. When there is a match between what students think tasks afford and their personal motivations, motivation and performance are boosted (e.g., Rodriguez, Romero-Canyas, Downey, Mangels, & Higgins, 2013); perceiving that coursework matches one’s personal goals for learning predicts greater usage of tutorials and the choice of the type of problems students wish to solve. Having students write about personal connections to what they learned in their science course increased interest in the subject and improved grades in the course, particularly for students who expected to underperform in it (Hulleman & Harackiewicz, 2009). In a related vein, prompting a prosocial purpose to learning less interesting material is related to greater persistence in the short term and the long term: students who persisted longer on a boring task were later less likely to drop out of college (Yeager, Henderson, et al., 2014). Although these efforts do not appear to directly address stereotype threat in learning, feeling more engaged in the learning process may insulate students from the impact of these concerns or provide for the leveraging of additional motivation to learn. Collaboration and active learning are other pedagogical practices that could buffer students from stereotype threat-based learning decrements. Compared to students who completed a first statistics test individually, students completing the same test collaboratively, not surprisingly, showed an immediate performance benefit on this test (Pociask & Rajaram, 2014); interestingly, women showed sustained benefits of collaboration in that learning extended beyond the first collaborative test to a second individual test. Active learning adds structure to collaboration and involves deeper consideration of course material by problem solving and asking and answering one’s own questions about it. This approach’s benefits are obvious in a metaanalysis of active learning in science, engineering, and math courses, wherein student performance was significantly improved and lower failure rates were found for students in active learning classroom environments (Freeman et al., 2014). Importantly, active learning has been shown to reduce the achievement gap for students from disadvantaged educational backgrounds in early but difficult courses in the college curriculum (e.g., introductory biology; Haak, HilleRisLambers, Pitre, & Freeman, 2011). As an added benefit to improved learning and performance in traditionally difficult courses, the promotion of collaboration and active learning

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could potentially change stereotypic perceptions of science, math, and technology fields themselves. These fields are perceived as not fulfilling communal goals of working with and helping others, and the disconnect between perceptions of these fields’ views and one’s personal valuing of communion predicts gaps in women’s and other minority groups’ participation within them (e.g., Diekman, Steinberg, Brown, Belanger, & Clark, in press; Diekman, Weisgram, & Belanger, 2015). Having greater fit between one’s goals and the perceived values of certain disciplines can increase interest, belonging, and motivation, which could curtail the influence of stereotype threat on future learning outcomes.

13. ADOPTING A GROWTH MINDSET WHEN LEARNING Multiple motivations can be involved when learning new material. One central motivation is achievement motivation, which includes the pursuit of two classes of goals: learning goals and performance goals. Pursuing learning goals means that individuals are seeking to understand or master something new to them, whereas people who are pursuing performance goals are motivated to have others judge them positively in terms of their intelligence and ability (e.g., Dweck, 1986; Dweck & Elliott, 1983). Different behavioral patterns and learning outcomes emerge for these two types of goals. People with learning goals focus on progress and respond to obstacles with greater effort and strategy use, which, in turn, often improves performance. Conversely, a focus on performance goals leads people to be overly concerned about how smart they seem to others, so they often choose easy tasks or incredibly difficult ones, are more reactive to negative feedback, and withdraw effort when challenged (e.g., Bandura & Dweck, 1985; Elliott & Dweck, 1988). As one illustrative study of the interplay of these goals for learning outcomes, Farrell and Dweck (1985) found that eighth graders who had learning goals had greater success at transferring their knowledge and provided more evidence for their answers. These two goal orientations have been related to two kinds of mindsets that people can have toward their intelligence and ability: learning goals are adopted by individuals said to have a growth mindset, whereas performance goals are adopted by individuals said to have a fixed mindset (e.g., Dweck, 2006; see chapter “Implicit theories: Assumptions that shape social and moral cognition” by Plaks). With a growth mindset of intelligence, people see intelligence as malleable and able to be developed, whereas people with a fixed mindset of intelligence view intelligence as innate and unchangeable. Compared to having a

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growth mindset, having a fixed mindset results in shying away from challenge, reducing or downplaying effort following setbacks, and not seeking out or utilizing feedback. These negative consequences of a fixed view of intelligence were documented for female students in a calculus class, such that they reported a lower sense of belonging, less interest in pursuing math in the future, and had lower math grades (Good, Rattan, & Dweck, 2012). Importantly, a growth mindset can be learned, and several interventions have been successful in training students how to take on this mindset. Good et al. (2003) paired seventh graders with college students, and the college students acted as mentors throughout the academic year. Mentors in the growth mindset condition emphasized aspects of the growth mindset by discussing how intelligence can be expanded. This message powerfully impacted students’ subsequent test performance. A gender difference in math performance for students with mentors who emphasized a control antidrug message disappeared for students who had mentors who emphasized the growth mindset. Moreover, students in the growth mindset condition had higher subsequent reading scores than students in the control antidrug group. Blackwell, Trzesniewski, and Dweck (2007) tested a complementary growth mindset intervention with Black and Latino middle schoolers from economically disadvantaged backgrounds. Encouraging the adoption of a growth mindset again led to improved student achievement, particularly for motivation and grades, compared to a control group that learned about the brain, how memory works, and study skills. In addition to encouraging students to adopt a growth mindset, researchers have begun to delineate the ways in which instructors can communicate that they value the growth mindset and structure their courses to promote and satisfy learning goals. Explaining to students the purpose of assessment and promoting a mastery purpose for evaluations can improve learning and performance for students, especially for those who are members of negatively stereotyped or disadvantaged groups (e.g., women in science, students from a lower socioeconomic status; Smeding, Darnon, Souchal, Toczek-Capelle, & Butera, 2013; Souchal et al., 2014). Instructors can structure their courses in service of learning goals by providing multiple assessments of covered material such that each evaluation is lower stakes than the traditional midterm and final format. Not only does this structure increase the adoption of learning goals, but it also results in greater learning, because repeated testing improves long-term retention of the information (e.g., Roediger, Agarwal, McDaniel, & McDermott, 2011; Roediger & Karpicke, 2006). As a specific example, providing daily quiz results and

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feedback to students in large college courses improved performance in the courses and led to a spillover effect of better performance in other courses during the current and following semester (Pennebaker, Gosling, & Ferrell, 2013); the daily quizzing also resulted in a reduction of an existing social class achievement gap in the course.

14. SELF-AFFIRMATION AND ACADEMIC ACHIEVEMENT All of the effective strategies we have discussed so far focus on the learning or performance situation and changing the construals of and experiences within the situation. An alternative way to deal with stereotype threat in a learning environment can be to bolster one’s self-esteem in another domain. Self-affirmation interventions allow people to be reminded of other aspects of their lives that they value, excel within, and for which they have positive self-views. By reaffirming one’s global self-worth, academic motivation and performance is buffered from stereotype threat’s pernicious effects (Sherman et al., 2013). Brief, written self-affirmation tasks significantly influence important psychological and behavioral outcomes: affirmed students see daily difficulties as more manageable, have more positive academic attitudes, and utilize better coping strategies and available resources (Walton, Logel, Peach, Spencer, & Zanna, 2015). Moreover, self-affirmation increases the likelihood of success in difficult “weeder” courses, improves overall GPAs, and reduces achievement gaps (Cohen, Garcia, Apfel, & Master, 2006; Harackiewicz, Canning, Tibbetts, Priniski, & Hyde, 2016; Miyake et al., 2010). These benefits are maintained over multiple years (Cohen et al., 2009) and have been seen for diverse students groups (e.g., racial minorities, male and female students in physics and engineering, first-generation college students). Self-affirmation can occur spontaneously, without prompting from others (Brady et al., 2016), and interventions to inspire self-affirmation can be scaled to benefit larger numbers of students (e.g., Borman, Grigg, & Hanselman, 2016; but see Hanselman, Bruch, Gamoran, & Borman, 2014; Hanselman, Rozek, Grigg, & Borman, in press). Despite the well-documented successes of self-affirmation interventions, very few studies have examined the mitigating influence self-affirmation can have for learning under stereotype threat. In one published study, which was reviewed more extensively earlier, Taylor and Walton (2011) had Black students complete a values affirmation activity before studying words under stereotype threat. Compared to Black students who didn’t complete this

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activity, these students fared better in a nonthreatening assessment a week later. The buffering effect of the affirmation occurred because the suppression of stereotypes was reduced and a focus toward promotion and growth was heightened.

15. CONCLUSION The research to date on how stereotype threat can affect learning is limited, perhaps because differentiating learning from performance is difficult. The early focus in stereotype threat research was on performance in “high stakes” situations, so how and why stereotype threat impairs learning was not on the research radar of investigators. Research from our lab, however, has shown that stereotype threat can interfere with both basic, perceptual types of learning (Rydell, Shiffrin, et al., 2010) and more complicated forms of learning, specifically memorization and mathematical learning (Rydell, Rydell, et al., 2010; see also Taylor & Walton, 2011). Interestingly, stereotype threat seems to impair perceptual learning by leading people to put too much effort into their performance, so they do not automatize a skill that comes naturally, whereas stereotype threat seems to impair memorization and the acquisition of mathematical information by reducing encoding. More research is certainly warranted on how stereotype threat can cause each of these types of learning deficits, but it is also likely that stereotype threat impairs other types of learning as well, and the processes underlying the effect of stereotype threat on these other types of learning may differ from the processes identified to date. In addition, another mechanism through which threat may influence learning, namely by reducing motivation to learn, has not been studied at all. We suggest that much like threat can lead people to devalue a performance domain or withdraw effort during performance, people may not be motivated to learn because they don’t care about learning, don’t think it is important, or don’t feel that they can. Research on this mechanism is obviously needed and could prove useful for combating the effect of stereotype threat on learning in the real world. Although we have documented that stereotype threat can influence learning, there is still much more to be done. The interaction of stereotype threat and feedback seems critical to understanding the role threat may play in learning at schools. Both formal and informal feedback are important parts of the school experience, which are meant to provide information about how much one has learned. Because schools operate in feedback cycles, students learn and get feedback (e.g., grades) over and over.

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Therefore, we need to understand how this feedback influences negatively stereotyped individuals. Can we craft feedback in such a way as to increase subsequent learning? It would be exciting to develop effective interventions to reduce or eliminate the effect of stereotype threat on learning. This may prove to be difficult simply because it is often unclear how to differentiate learning from performance in real world settings. Ultimately, it seems ideal to strive for interventions designed to improve both learning and performance (which may be true of some interventions that have already been developed). From a theoretical perspective, being able to understand how and why interventions that reduce stereotype threat lead to more positive outcomes for negatively stereotyped individuals would be interesting, but it is likely that at least some interventions improve performance by increasing learning. Stereotype threat has been the subject of much research in the last 20 years. We certainly know a great deal about how stereotype threat affects performance. We urge researchers to focus more attention on how stereotype threat can impact learning. This area of inquiry has the potential to be very important both theoretically and practically.

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