Using Relevant Animations to Counter Stereotype Threat When Learning Science

Using Relevant Animations to Counter Stereotype Threat When Learning Science

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ARTICLE IN PRESS Journal of Applied Research in Memory and Cognition xxx (2019) xxx–xxx Contents lists available at ScienceDirect

Journal of Applied Research in Memory and Cognition journal homepage: www.elsevier.com/locate/jarmac

Using Relevant Animations to Counter Stereotype Threat When Learning Science夽 Christopher A. Sanchez∗ , Karah Weber Oregon State University, United States Much research has supported the notion that adding relevant animations to science text can positively impact learning. Can relevant animations also provide an opportunity to address other issues that affect learning, specifically situations when learners are explicitly placed under stereotype threat? The current study extends work on both animations and stereotype threat by examining whether relevant imagery can positively address issues of stereotype threat. Participants were placed under threat or not, and then read a science text that was either illustrated or not. Results replicated the broad effects of both stereotype threat and animations, but also found that these factors interact. Specifically, the presence of animations seemed to negate the negative effects of primed maladaptive stereotypes. This suggests that relevant animations do have an insulating effect on learners relative to stereotype threat and may protect them from salient assaults on their perceived ability to learn science material.

General Audience Summary Research has suggested that telling learners that they are less likely to learn in STEM areas consistent with cultural stereotypes (e.g., females do worse at science), can actually cause learners to learn less. This phenomenon is known as stereotype threat. However, it has also been shown that adding relevant animations to learning materials can positively enhance understanding. However, can animations also eliminate the effects of negative stereotypes? The current study had participants read a science text that either did or did not have animations. Participants were also told they were less likely to achieve based on their demographics, or instead told nothing. Results replicated the positive effects of animations on learning, and also the negative effects of stereotype threat on learning. However, it was also found that animations help learners under stereotype threat, and cause them to learn at the same level as individuals who were not told they were less likely to achieve. These results are the first demonstration of this interaction, and suggest that animations can help science learning in multiple ways. Keywords: Science learning, Stereotype threat, Animations

Much prior work has supported the notion that the inclusion of relevant animations within a text can have a positive impact on learning (see Berney & Betrancourt, 2016; Höffler & Leutner, 2007 for reviews), and especially so in STEM domains that contain a large visuospatial component (Uttal, Miller, & Newcombe, 2013). This effect is integral to Mayer’s (2005) cognitive theory of multimedia learning (CTML), which suggests that relevant

Author Note Christopher A. Sanchez & Karah Weber, Oregon State University, Corvallis, OR, United States. ∗ Correspondence concerning this article should be addressed to Christopher A. Sanchez, School of Psychological Science, Oregon State University,

imagery and animations can have multiple positive effects on how learners think and reason about content. Animations seem especially helpful for low ability learners, as they provide an opportunity to offload some of the spatial processing burden inherent to these domains (Hegarty & Kriz, 2008; Höffler & Leutner, 2011; Sanchez & Wiley, 2014), while also encouraging learners to engage in more effortful and appropriate processing

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Please cite this article in press as: Sanchez, C. A., & Weber, K. Using Relevant Animations to Counter Stereotype Threat When Learning Science. Journal of Applied Research in Memory and Cognition (2019), https://doi.org/10.1016/j.jarmac.2019.08.003

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(Lin & Atkinson, 2011; Mayer, 2014; Mayer & Fiorella, 2014; Rieber, 1991). While the comprehension benefit of animations is well-established, are there other ways animations also positively impact the learning experience? For example, is it possible that they might also provide a means of addressing other issues critical for learning success, such as perceived threats to learner achievement? The current study seeks to explore this potential additional benefit of animations in situations where learners have been explicitly primed with the notion that they will fail to achieve in a STEM domain (i.e., stereotype threat). Stereotype Threat and Animations Previous research has identified a robust phenomenon known as stereotype threat (Steele, 1997), in which the activation of a negative stereotype within an individual causes them to realize lower levels of performance, consistent with said stereotype. Such primed negative stereotypes may cause learners to not only feel they can achieve less than they actually can, but may also encourage them to expend less effort while learning (see Smith, 2004). As the learner also has to devote attentional resources to processing the threat, such threats also produce a further burden on the working memory system (Beilock, Rydell, & McConnell, 2007; Schmader, Johns, & Forbes, 2008). Thus, as threats not only place an additional cognitive burden on the learner, but also cause the learner to expend less effort overall, it is perhaps easy to see how such threats can overwhelm unsuspecting learners and cause them to learn less. Note that such effects are independent of a learners’ actual ability, and instead represent an attempt to perform to an artificial standard or status that is disconnected from the reality of the situation (Josephs, Newman, Brown, & Beer, 2003; McGlone & Aronson, 2006). Thankfully, research has identified several interventions that can reduce the impact of such negative threats, such as encouraging individuals to self-affirm or challenge the threat (Alter, Aronson, Darley, Rodriguez, & Ruble, 2010; Martens, Johns, Greenberg, & Schimel, 2006), or instead change their own view on what it means to be intelligent (e.g., Good, Aronson, & Inzlicht, 2003). These interventions likely produce some benefit as they explicitly force learners to address the internal issues of dejection that arise as a result of being exposed to such noxious suggestions, and thus free learners from the downstream cognitive effects of being exposed to threat (Keller & Dauenheimer, 2003; Schmader et al., 2008). However, one issue with such interventions is that they force learners to take these threats headon and cognitively process (and likewise successfully refute) such claims before moving on. This could represent yet another processing burden placed on the learner who is likely already overwhelmed by content (Beilock et al., 2007). Thus, it seems critical to identify other external interventions or supports that can also mitigate stereotype threat, but perhaps do not place such additional demands on the learner. One possible intervention that might prove useful could be the inclusion of relevant dynamic animations. When learning a physical science topic (a context that often demonstrates stereotype threat), it has been demonstrated that the inclusion of relevant animations not only enhances comprehension, but also

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increases estimates of achievement and especially so within traditionally vulnerable populations (Barak, Ashkar, & Dori, 2011; Liu, Cho, & Schallert, 2006; Sanchez & Wiley, 2010; Wong, Castro-Alonso, Ayres, & Paas, 2015). As increases in perceived achievement are often synonymous with domain interest and motivation to learn (Hidi, Berndorff, & Ainley, 2002; Murphy & Alexander, 2000; Schiefele, 1991), increases in learner engagement could provide a direct counter to any negative effects induced by threat exposure. Thus, the positive increase in perceived achievement fostered by animations might in fact offset the observed negative motivational effects brought on by a perceived threat. This increase in motivation might also help ensure that learners are fully engaging with the material in appropriate ways, as adding multimedia has also been shown to increase relevant generative processing (Mayer, 2014). Properly constructed animations have also been shown to alleviate some of the extraneous processing burden inherent to learning science (Hasler, Kersten, & Sweller, 2007; Mayer, Moreno, Boire, & Vagge, 1999; Moreno, 2007; Schnotz & Rasch, 2008), allowing learners to focus on more relevant aspects of the material. The structure of the representations themselves seems to help guide the selection and processing of conceptual information (Lowe, 2003; Mayer, 2003; Münzer, Seufert, & Brünken, 2009), thereby freeing the working memory system to focus on more deep conceptual relationships (De Koning, Tabbers, Rikers, & Paas, 2011; Mayer, 2005). This unburdening of the working memory system might also be a boon for learners dealing with stereotype threat (e.g., Schmader et al., 2008), as it frees resources that can now be repurposed as needed by the learner. While animations and stereotype threat have not been examined concurrently before, the above results suggest a promising opportunity to offset the negative repercussions of stereotype threat by including relevant animations. As stereotype threat appears to operate via the reduction of expended effort, and likewise the over-burdening of the working memory system, animations should provide an effective counter to both these issues as they appear to not only facilitate processing, but also address issues of motivation and effort. To investigate this interaction, in the current study participants were either placed under stereotype threat or not and then asked to read a physical science text that either did or did not include relevant conceptual animations. Participants were evaluated for the activation of threat and for learning in a transfer task. The following hypotheses were generated: H1a. It was expected that conceptual animations should provide a positive overall benefit for learning, consistent with previous results demonstrating that the inclusion of such imagery assists in developing understanding in STEM areas via the more appropriate focusing of attention on deeper conceptual relationships. H1b. Similarly, animations should also positively impact levels of effort expended while learning, as they appear to provide a means of increasing learner motivation while simultaneously providing a more efficient path towards comprehension.

Please cite this article in press as: Sanchez, C. A., & Weber, K. Using Relevant Animations to Counter Stereotype Threat When Learning Science. Journal of Applied Research in Memory and Cognition (2019), https://doi.org/10.1016/j.jarmac.2019.08.003

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H2a. Placing individuals under stereotype threat should negatively affect learning performance, as it causes learners not only to expend less cognitive effort, but also to devote critical processing resources towards processing the threat (rather than the to-be-learned material). H2b. Stereotype threat should also reduce the amount of effort learners expend while learning, due to the primed negative stereotype effectively encouraging learners to perform consistent with said stereotype. H3. As animations have been shown to positively affect motivation to learn, and also alleviate the processing burden of learning science, it is expected that while animations do produce a main effect on understanding, they should be especially beneficial for learning for individuals placed under threat. H4. Related to H3, as animations have also been shown to help address issues of motivation, it is likewise expected that animations should not only increase the amount of effort learners expend overall, but should specifically eliminate or attenuate the reduced effort expended by learners under stereotype threat. Methods Participants and Design Previous meta-analytic research has estimated the effect size of including animations (d ∼ .76; Höffler & Leutner, 2007) or stereotype threat (d ∼ .53; Nguyen & Ryan, 2008) as medium to large. Results from an a priori power analysis (calculated using G*Power using a medium effect size (f = .26), β = .80, and 2 factors) suggested roughly 30 participants for each of the 4 conditions. To this end, one-hundred twenty eight (N = 128) native English speaking undergraduates from a large public university in the United States completed the study for course credit. Participants were low in knowledge of the content area as determined by a pretest (see below). The current experiment consisted of a 2 (threat) × 2 (imagery) between-groups design. Participants read a science text that either did or did not contain relevant animations, while either under threat or not. Materials Prior knowledge pretest. This measure was adapted from Sanchez and Wiley (2014) and consists of 30 inferences about the causes of volcanic eruptions, which participants are asked to verify as correct or incorrect. For every correct identification, participants are awarded 1 point. Participants were not provided with their score on the pretest. This measure has been used successfully in previous studies and produced an acceptable level of inter-item reliability within the current sample KR20 = .73. Demographic reporting. Prior to reading, participants were asked to report several demographics that have been traditionally connected to the occurrence of stereotype threat (e.g., Steele, 1997) including age, gender, parent SES, and ethnicity. These demographics are available in Table 2. Stereotype threat manipulation and check. Immediately after submitting their demographics, participants then either

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received a stereotype threat message or not. The threat message was phrased as follows: “Previous individuals who had responses that were similar to yours for these demographic questions (e.g., gender, age, etc.) tended to score VERY LOW when it comes to learning the science text you are about to read. . .Thus, it is likely you might also struggle to learn, although that is not guaranteed.” Importantly, this threat message was designed to be vague in the sense that it did not specifically target a single demographic facet (i.e., gender, race, etc.). As the occurrence of stereotype threat can be observed across multiple demographic characteristics (see Inzlicht & Schmader, 2012), it was of interest to explore the broader effect of threat across prospective learners, and not focus on a specific group characteristic. Participants who did not receive the threat message were instead thanked for submitting their demographics, and then proceeded to the next part of the experiment. All participants were then asked to rate on a scale of 1–10 (1 being lowest) How well do you think you will learn the science text? This rating was meant to verify whether the threat manipulation was effective or not by explicitly asking participants to provide an estimate of their likely learning performance for the to-be-read text. If the threat manipulation was ineffective in reducing perceived levels of achievement, one would expect no difference in these ratings across threat conditions. However, if the threat did cause learners to believe they are less likely to be able to learn the science text, participants should score lower when under threat than when not. Science text and animations. Participants read a physical science text (plate tectonics) that contained ∼3500 words. The text was based on information from the USGS This Dynamic Planet unit and the NASA Classrooms of the Future Volcanoes unit, originally developed by Wiley (2001). This text includes eight a priori concepts from a causal model of volcanic eruptions, which participants must integrate to form a complete mental model of the text (Sanchez & Wiley, 2014). This text was also illustrated with relevant animations, based on condition. An example of the illustrated text is presented in the Appendix. Animations were presented in line with the relevant text section, and were redundant with the textual information. For example, in the second graphic in the screenshot presented in the Appendix, the oceanic plate moves and subducts beneath the continental plate thereby forming magma, just as described in the text. These illustrations were presented in .gif format, which continuously looped as long as they were visible on screen. Participants were not able to pause, stop, or reverse these animations. Transfer learning essay. Participants were asked to write an argumentative essay responding to the prompt “On May 18, 1980, Mt. St. Helens, which is located in the state of Washington, erupted. Please write an argument answering the question ‘What do you think caused the eruption of Mt. St. Helens?’ Please try your hardest to develop an argument. An argument means taking a position and justifying it based on what you have just read. Please write as much as necessary, and make sure to justify what you think caused the eruption of Mt. St. Helens.” The text never explicitly mentions the eruption of Mt. St. Helen’s, and as such, this measure requires participants to apply the

Please cite this article in press as: Sanchez, C. A., & Weber, K. Using Relevant Animations to Counter Stereotype Threat When Learning Science. Journal of Applied Research in Memory and Cognition (2019), https://doi.org/10.1016/j.jarmac.2019.08.003

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Table 1 Descriptive Statistics for Performance Measures by Condition Condition

Pre-test

How well learn?

Essay task

Reported effort

No threat No imagery (n = 32) Animations (n = 33)

20.7 (2.7) 20.3 (2.5)

6.3 (1.3) 5.9 (1.4)

2.2 (1.1) 2.4 (1.1)

6.9 (1.8) 7.1 (1.8)

Threat No imagery (n = 31) Animations (n = 32)

20.4 (2.9) 20.2 (3.1)

5.3 (2.0) 4.9 (2.0)

1.4 (1.0) 2.4 (1.1)

5.6 (1.8) 7.0 (1.9)

Note. Standard deviations appear in parentheses.

accumulated knowledge from their reading to this novel situation in a case of near transfer. Participants were not allowed to access the text while writing, and were asked to write at least one page in response. Essay responses were then examined for the presence of the eight correct concepts. Two scorers blind to condition independently coded these essay responses for the presence of correct concepts, and produced a high level of inter-rater agreement (ICC = .84; p < .001; Shrout & Fleiss, 1979). Any observed scoring differences were resolved through discussion for the final analysis. Learning effort expended. As it has been suggested that primed threats promote disengagement within learners, after writing the essay response participants were simply requested to report overall how hard they tried to learn the information on the webpage. Participants rated their effort on a 1–10 scale, with 1 being lowest.

Procedure After completing informed consent, all participants completed the pretest on prior knowledge of the content area. Once they had completed this, participants were then asked to report the requested demographics. Based on condition randomization, participants then received the threat manipulation or not, and then all participants rated how well they thought they would learn the text. Participants were then given 15 min to read the science text, and advised to read the entire text as they would be tested on it later. After reading, participants then completed the transfer essay task and then the learning effort task. Participants were then debriefed and dismissed. The entire experiment took no longer than 1 h.

Results Descriptive statistics for all learning measures are available in Table 1. Demographically, participants in each group were very similar (Table 2), and all groups demonstrated low knowledge of the content area on the pretest (Wiley et al., 2009). There was no significant difference (or interaction across groups) for age, parental income, ethnicity, major, or gender distribution. Thus, it appears that the groups were well matched on relevant demographics. To examine the impact of both threat and animations on relevant variables, 2 × 2 between groups ANOVAs were conducted. All results were evaluated using a significance level of p < .05.

Threat Manipulation Check In terms of participants’ rating of how well they would learn the text, threat condition produced a significant main effect on this estimate, F(1, 124) = 11.17, MSE = 2.85, p < .01, η2p = .08. Those individuals who received the threat message rated their likelihood of learning as significantly lower than those participants who had not. There was no reliable main effect of imagery, F(1, 124) = 1.87, MSE = 2.85, p = .17, η2p = .02, nor interaction between imagery and threat condition, F(1, 124) = .04, MSE = 2.85, p = .85, η2p = .00. The lack of animation effects are entirely expected as participants had not yet seen the text, and were thus unaware of how or what they would be learning, including whether they would get imagery or not. Importantly, these findings confirm that the threat manipulation, as implemented, did have the desired effect on individuals’ estimates of learning achievement for the science text, regardless of later assignment to imagery condition.

Table 2 Participant Demographics by Condition Condition

Age

Gender (% female)

Major (% science)

Ethnicity (% white)

Reported parental income (×100, USD)

No threat No imagery (n = 32) Animations (n = 33)

19.2 (1.6) 19.7 (2.0)

78.1 63.6

56.3 57.6

87.5 78.8

115.8 (91.7) 119.0 (108.9)

Threat No imagery (n = 31) Animations (n = 32)

19.7 (1.9) 19.5 (3.4)

67.7 75.0

67.7 50.0

74.2 84.4

85.0 (72.7) 112.7 (123.1)

Note. Standard deviations appear in parentheses.

Please cite this article in press as: Sanchez, C. A., & Weber, K. Using Relevant Animations to Counter Stereotype Threat When Learning Science. Journal of Applied Research in Memory and Cognition (2019), https://doi.org/10.1016/j.jarmac.2019.08.003

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Figure 1. Correct causal concepts by condition. Error bars represent the standard error of the mean.

Causal Concepts in Essay Responses It was predicted that the introduction of stereotype threat would reduce comprehension overall, and conversely that the inclusion of animations would benefit learning overall. Consistent with the overall predictions of H1a and H2a, there was a significant main effect of threat condition on actual learning, F(1, 124) = 3.83, MSE = 1.19, p = .05, η2p = .03, in addition to a significant main effect of animations on learning, F(1, 124) = 9.54, MSE = 1.19, p < .01, η2p = .07. These results demonstrate that receiving a threat message does actually decrease learning performance, while conversely, the inclusion of animations increased learning. These main effects are directly consistent with past work in both areas, confirming that the intended threat and imagery manipulations produced results consistent with initial expectations. However, it was also predicted (H3) that these factors would interact, such that animations should offset or attenuate the negative effects of stereotype threat on learning. Consistent with this prediction, there was a significant interaction between threat manipulation and animations, F(1, 124) = 4.08, MSE = 1.19, p = .04, η2p = .03. As is visible in Figure 1, planned comparisons with a Bonferroni adjustment indicated that while there was little difference across the imagery groups that did not receive the threat message (F < 1, p > .05), for those individuals placed under threat, individuals who received animations performed significantly better than those who did not, F(1, 61) = 13.91, MSE = 1.10, p < .01, η2p = .19, and at levels consistent with their no-threat counterparts. The lack of a difference between imagery conditions while not under threat further suggests that the main effect of animations is being driven by the low performance of the non-illustrated condition under threat. This is an additional interesting finding, and suggests that perhaps the current animations are most useful in situations where the learner is under some kind of extraneous processing demand (i.e., threat), which animations have been shown to be adept at alleviating (Cohen & Hegarty, 2007; Mayer, 2005). These comprehension results thus replicate the broad pattern of effects previously observed in both the stereotype threat and animation literature. Further, they extend this work and

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Figure 2. Self-reported effort expended by condition. Error bars represent the standard error of the mean.

demonstrate that animations can produce an insulating effect on learners, such that even when placed under internal pressure to learn less well, the inclusion of relevant animations does allow learners to achieve at levels consistent with peers that did not receive the threat message. This is consistent with other work that has suggested that animations can be especially beneficial to individuals who are traditionally at risk for successful learning in science, and thus often exposed to similar threats (Sanchez & Wiley, 2010). Learning Effort Expended It was anticipated that the inclusion of animations would positively increase learning effort, however stereotype threat should likewise reduce it. To test these predictions, participants’ ratings of how much effort they had expended on learning the science topic were also analyzed. To begin, reported effort was significantly correlated with performance in the essay response (r = .45, p < .001). Further, comparing these ratings across the threat and imagery manipulations produced results that exactly mirrored that of the essay analyses. Consistent with predictions H1b and H2b, there were main effects of both threat, F(1, 124) = 4.34, MSE = 3.39, p = .04, η2p = .03, and animations, F(1, 124) = 6.57, MSE = 3.39, p = .01, η2p = .05 on amount of reported effort. Adding threat messaging reduced effort expended, but adding animations increased effort overall. More importantly, it was also predicted that these factors would interact (H4), in a similar fashion as what was observed in the comprehension results. Indeed, there was also a significant interaction between these factors, F(1, 124) = 3.97, MSE = 3.39, p = .05, η2p = .03. Just as with the learning results, while there appeared to be very little difference between imagery conditions while not under threat (F < 1, p > .05), those individuals placed under threat without animations tended to try less hard than those with who did receive animations while under threat, F(1, 61) = 10.12, MSe = 3.42, p < .01, η2p = .14; Figure 2. This suggests that the facilitative effect of animations may be two-fold: not only do they help individuals learn better conceptually, but they also cause them to try harder to learn than they would otherwise, potentially further enhancing their learning.

Please cite this article in press as: Sanchez, C. A., & Weber, K. Using Relevant Animations to Counter Stereotype Threat When Learning Science. Journal of Applied Research in Memory and Cognition (2019), https://doi.org/10.1016/j.jarmac.2019.08.003

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Discussion The current study sought to examine the potential interaction between two factors that have previously been shown to affect how well individuals learn science: stereotype threat and learning with relevant animations. Results demonstrated that threat messaging harms learning and lowers effort, while including relevant animations helps comprehension and increases effort. Further, these factors do also interact. Participants who were exposed to threat while reading without animations demonstrated a significant decline in both reported effort, and how much they learned. However, participants that read an animated version of the same text (even while under threat), performed at a level consistent with those individuals who were not exposed to threat. The inclusion of relevant animations does appear to effectively negate the presence of primed threats, allowing learners to comprehend at more typical levels. Thus, it appears that animations can insulate or eliminate the negative repercussions of stereotype threat, and might be useful for dealing with situations that might reduce perceptions of science achievement. This is the first demonstration of such an effect and provides evidence of an additional positive benefit of including animations within a science learning context. Why do animations effectively counter to stereotype threat? It is likely the confluence of several benefits that have been previously attributed to animations. For example, it is possible that animations implicitly produce a more appropriate conceptual reframing of the problem (Lowe, 2003; Schnotz & Rasch, 2008), moving the learner away from their threat-based mindset. Such strategies have been recommended previously as a means of reducing stereotype threat (Appel & Kronberger, 2012). Further, animations also seem to encourage learners to expend more effort while learning, explicitly countering the lack of effort that often accompanies threat exposure (Smith, 2004). It is our contention here that cognitive resources were likely re-allocated from threat processing, and instead focused in a more useful way towards the content material. This aligns with previous results that found that animations increase more relevant intentional processing (Rieber, 1991), while simultaneously reducing extraneous processing (Amadieu et al., 2011; Mayer, 2014). While animations did demonstrate a broad facilitative effect for learning and effort, interaction analyses seem to suggest that these simple main effects are not evidenced in no-threat situations. This is an interesting caveat, and seems to suggest that animations are most useful when the learner is experiencing some kind of extraneous processing demand, such as the primed threat. As animations have been shown to adeptly alleviate such extraneous demand via such functions as weeding (Mayer & Moreno, 2003), it is possible that this identifies how animations are affecting change in the current study: by helping users focus on more appropriate aspects of the task. While speculative, this finding warrants further exploration to better understand precisely how stereotype threat affects learners, and more importantly, how best to counter it.

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Practical Implications The current pattern of results suggests a useful and low-risk intervention that can easily be implemented to help students learn. Given the ease with which technology can be integrated into physical classrooms and the learning environment, the addition of animations to a given text is no longer difficult. At worst, animations do not harm learning, and at best, they seem to bolster learners who are struggling with the material due to perceived stereotypes. Further, as the threat used here did not focus on a specific demographic, it is possible that animations have the ability to counter threats based on differences in multiple demographics that are often encountered in academic settings (e.g., gender, SES, age). Limitations and Future Directions As the current investigation only explored this interaction within a single science text, future research should continue to explore the interaction and attempt to identify other supporting factors that could also reduce the negative impacts of stereotype threat. As stereotype threat seems to be a function of perceived lack of ability (Keller & Dauenheimer, 2003), any learning support that provides an opportunity to eliminate this erroneous perception should produce a similar effect. It would also be of interest to more deeply explore the relationship between effort and learning in this context. For example, understanding when and how this additional effort is expended might not only illuminate how animations increase effort, but also might indirectly clarify how threat produces the opposite pattern of effects. Finally, as the current pattern of results is solely learning based, more detailed trace measures such as eye-tracking would be especially useful to verify how animations change processing of relevant information for individuals under threat. Observing changes in visual search patterns could illuminate specific processes that may lead to the development of not only better animations, but better threat interventions overall. Conclusion The inclusion of relevant animations has previously demonstrated a robust positive effect on learning science. The current study extends this work and demonstrates, for the first time, that animations can also be used to counter explicit threats on perceived learner achievement (i.e., stereotype threat), and can help learners not only comprehend better, but also expend more effort while learning. Thus, animations appear to positively influence multiple facets of the learning experience, and the addition of animations stands as a worthwhile intervention to improve the overall quality of learning in STEM areas. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Please cite this article in press as: Sanchez, C. A., & Weber, K. Using Relevant Animations to Counter Stereotype Threat When Learning Science. Journal of Applied Research in Memory and Cognition (2019), https://doi.org/10.1016/j.jarmac.2019.08.003

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Author Contributions C.A. Sanchez was responsible for study conceptualization, experimental design, statistical analyses, and manuscript preparation/revision. K. Weber was involved in data collection and manuscript preparation.

Appendix. Screenshot of experimental material, as presented to participants

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Received 11 June 2019; received in revised form 21 August 2019; accepted 21 August 2019 Available online xxx

Please cite this article in press as: Sanchez, C. A., & Weber, K. Using Relevant Animations to Counter Stereotype Threat When Learning Science. Journal of Applied Research in Memory and Cognition (2019), https://doi.org/10.1016/j.jarmac.2019.08.003