The Relationship Between Intelligence And Mindset
Intelligence 64 (2017) 52–59Contents lists available at ScienceDirectIntelligencejournal homepage: www.elsevier.com/locate/intellThe relationship between intelligence and mindsetMARK⁎Brooke N. Macnamara , Natasha S. RupaniCase Western Reserve University, United StatesA R T I C L E I N F OA B S T R A C TKeywords:MindsetIntelligenceImplicit theoriesAgeGenderIntelligence mindset refers to one's belief that either intelligence is a malleable trait that can improve witheffort—a “growth” mindset—or is a relatively stable trait—a “fixed” mindset. According to proponents ofmindset theory, holding a growth mindset is beneficial (e.g., greater academic persistence) while holding a fixedmindset is detrimental. Is there a relationship between one's intelligence mindset and one's intelligence?Proponents of mindset theory suggest that the answer is yes, and that this relationship differs by gender, withmore intelligent females holding more of a fixed mindset (aka, the “bright girl effect”). However, investigationsof all three factors—measured intelligence, intelligence mindset, and gender—have only been conducted withchildren and adolescents. Therefore, we tested whether, among adults, women have more of a fixed mindset thanmen, and whether women with higher intelligence are more likely to hold fixed mindsets. We found no evidencefor women holding fixed mindsets more so than men. We found very limited evidence for a “bright womaneffect”: Three-way interactions between age, gender, and intelligence predicting mindset emerged, however, therelationships were not consistently driven by brighter women (young or old) holding more of a fixed mindsetthan their less intelligent female counterparts or men. Furthermore, we did not find evidence to support thenotion that holding more of a growth mindset results in greater academic persistence. We conclude that neithergender nor intelligence is consistently associated with mindset.1. IntroductionAccording to mindset theory (aka implicit theories or self theories;Dweck, 2000)—a theory popular both within academia and the media—individuals hold varying beliefs about whether traits, such as intelligence, are relatively stable or whether they can be changed witheffort. Those who believe that intelligence and other traits are relativelystable are said to have a “fixed mindset” (or hold an “entity theory”)while those who believe that abilities are changeable with effort aresaid to have a “growth mindset” (or hold an “incremental theory.”)According to this theory, holding a growth mindset is beneficial. Forexample, individuals with growth mindsets are more likely to exerteffort to overcome a challenge, leading to greater academic achievement (e.g., Blackwell, Trzesniewski, and Dweck, 2007; Dweck andLeggett, 1988). In contrast, individuals with fixed mindsets are morelikely to avoid challenges, assume failure is attributable to ability thatcannot be changed, be debilitated by failure, fall into a helpless pattern,and lose their desire to learn (Dweck, 2000, 2007a, 2007b). Mindsetsare assumed to develop from the type of praise a child receives fromteachers and parents. Children who receive “process praise,” that is,praise for effort and perseverance, will develop growth mindsets, whilechildren who receive praise for their intelligence and abilities, will⁎develop fixed mindsets (Dweck, 2007b, see also Mueller and Dweck,1988).2. The bright girl effectMindset theory also suggests that girls and women might be morelikely to hold fixed mindsets than boys and men because, “[s]tarting ininfancy, parents tend to give boys more process praise, an advantagethat results in a greater desire for challenge, and a growth mindset, lateron” (Dweck and Simmons, 2014, para. 13). For example, as reported inDweck (1986), Licht and Shapiro (1982) found that girls were morelikely to attribute failure to their ability. Similarly, Dweck (1986) alsoreports that, among a sample of bright junior high students, the girlswere more likely than boys to hold a fixed mindset (Leggett, 1985).Indeed, bright girls in particular are believed to be especially likelyto hold fixed mindsets, because they are the most likely to be praised fortheir intelligence. For example, Halvorson (2011) pens, “more oftenthan not, bright girls believe that their abilities are innate and unchangeable, while bright boys believe that they can develop abilitythrough effort and practice” (para 6). She goes on to explain the presumed reason for this difference: girls often develop self-control earlierand are praised in terms of their attributes (e.g., being a good student,Corresponding author at: Department of Psychological Sciences, Case Western Reserve University, Cleveland, OH 44106, United States.E-mail address: brooke.macnamara@case.edu (B.N. .07.003Received 13 September 2016; Received in revised form 19 June 2017; Accepted 7 July 20170160-2896/ 2017 Published by Elsevier Inc.
Intelligence 64 (2017) 52–59B.N. Macnamara, N.S. Rupanieither observed that women and men have similar mindsets of intelligence on average (Heyman, Martyna, and Bhatia, 2002; Kornilova,Kornilov, and Chumakova, 2009; Yan, Thai, and Bjork, 2014) or thatwomen have more of a growth mindset than men (Spinath, Spinath,Riemann, and Angleitner, 2003). Similarly, while research suggests thatholding a fixed mindset negatively predicts academic achievement inchildren (e.g., Blackwell et al., 2007), these results run counter to thefinding that adults with higher levels of education are more likely tohold a fixed mindset than their less educated counterparts (Yan et al.,2014).The present set of studies seeks to examine claims about gender,intelligence, and mindsets among adult samples. In Study 1, in a college-age sample, we test the prediction that women endorse a morefixed mindset compared to men. We also test whether intelligence interacts with this relationship, specifically, whether more intelligentwomen are more likely to hold fixed mindsets. In Study 2, in an onlinesample, we test the same assumptions as in Study 1, and also examinewhether age interacts with gender, mindset, and intelligence. In Study3, we replicate Study 2, and also ask whether mindsets influence levelof education attained. Data for all three studies are openly available athttps://osf.io/r4x53/.being smart), with the smartest girls receiving the most attribute praise.In contrast, boys of the same age are often more hyperactive and arepraised for their efforts to sit still and pay attention.Similarly, Dweck (2000) writes,Bright girls are a group that does not want challenge (Licht andShapiro, 1982). And when they are presented with a challenge orobstacles, they are a group that readily blames their ability and fallsinto a helpless pattern (Licht and Dweck, 1984a, 1984b; Licht,Linden, Brown, and Sexton, 1984; Licht and Shapiro, 1982 . (p. 53)Thus, two assumptions have become suggested in the mindset literature and in the popular media. The first is that girls and women aremore likely to have fixed mindsets than boys and men. The second isthat girls and women with high IQs are especially likely to have fixedmindsets.However, little evidence supports these assumptions. For example,in a recent behavioral genetics study, Tucker-Drob, Briley, Engelhardt,Mann, and Harden (2016) examined mindsets among 811 third-eighthgrade twins and triplets. If girls are more likely to have fixed mindsetsbecause parents praise girls and boys differently, we should observe asignificant difference between girls' and boys' mindsets in the expecteddirection, and environmental effects should be greater than geneticinfluence. This pattern of results was not observed. They found thatgirls' and boys' mindsets were not significantly different from eachother. Furthermore, they found that mindsets among monozygotictwins, who share 100% of their genes, were significantly correlated, butthat mindsets were not correlated between same-sex or opposite-sexdizygotic twins, who only share about 50% of their genes. These resultssuggest that one's mindset is largely heritable and is not substantiallyinfluenced by one's home environment (e.g., praise from parents) orone's gender. However, Tucker-Drob et al. (2016) did not examine howIQ impacts gender differences in mindsets, which is an important partof the bright girl effect.Dweck (2007b) cites studies as evidence of how IQ interacts withgender, resulting in the debilitating bright girl effect. Describing Lichtand Dweck's (1984a) research on 5th-graders who received confusingmaterials at the start of a task, Dweck (2007b) states,4. Study 14.1. Method4.1.1. ParticipantsOne hundred three (57 female) General Psychology I students atCase Western Reserve University participated in exchange for partialcourse credit as part of a larger study.4.1.2. Materials and procedureAfter completing a brief demographics questionnaire asking participants to indicate their sex and age, participants completed the following measures in the following order.4.1.2.1. Intelligence mindset questionnaire. A questionnaire (Dweck,2000) asking participants to respond to statements about intelligencewas administered. Participants responded to eight statements (e.g.,“Your intelligence is something about you that you can't change verymuch.”) “Strongly Agree,” “Agree,” “Mostly Agree,” “Mostly Disagree,”“Disagree,” or “Strongly Disagree.” Responses were coded as 1, 2, 3, 4,5, or 6 respectively and reverse scored when appropriate such thathigher scores reflect more of a growth mindset.What we found was that bright girls did not cope at all well with thisconfusion. In fact, the higher the girl's IQ, the worse she did. Manyhigh-IQ girls were unable to learn the material after experiencingconfusion. This did not happen to boys. (p. 47)Dweck and Simmons (2014) add, “Notably, the highest IQ girlsstruggled the most” (para 10). However, the results of the Licht andDweck (1984a) study do not support the conclusion that the brighterthe girl the more likely she will to give up when facing challenges, apresumed trait of holding a fixed mindset. First, Licht and Dweck(1984a) excluded the brightest students from the sample, those scoringabove the 95th percentile on a standardized test. Additionally, Lichtand Dweck (1984a) only had IQ scores for a subset of the sample. Forthis reason, they asked children to rank how smart they thought theywere relative to their classmates, and this—not children's actualIQ—was the measure Licht and Dweck (1984a) used to correlate withperformance on the task. Most importantly, the correlation betweenthis measure of intelligence and performance on the task after experiencing confusion was not significant. Thus, the conclusion that, “thehigher the girl's IQ, the worse she did,” is not supported.Three other studies are commonly cited and discussed as evidencefor “the bright girl effect”: Leggett (1985), Licht and Shapiro (1982),and Licht et al. (1984). However, none of these studies were everpublished and are not accessible. Thus, there is little, if any, availableevidence to support the bright girl effect.4.1.2.2. Talent mindset questionnaire. A questionnaire (mindsetonline.com) asking participants to respond to statements about talent wasadministered. Participants responded to eight statements (e.g., “Yourtalent in an area is something about you that you can't change verymuch.”) “Strongly Agree,” “Agree,” “Mostly Agree,” “Mostly Disagree,”“Disagree,” or “Strongly Disagree.” Responses were coded as 1, 2, 3, 4,5, or 6 respectively and reverse scored when appropriate such thathigher scores reflect more of a growth mindset.4.1.2.3. Raven's Advanced Progressive Matrices. In this measure of fluidintelligence (Raven, Raven, and Court, 1962), participants are asked torecognize patterns, reason, and problem solve to the best of theirability. Participants were given 2 practice problems, feedback aboutwhy the correct answers were correct, and the chance to ask questions.Odd numbered items from the full scale were presented. Participantshad 10 min to complete as many as possible.4.2. Results3. Is there a bright woman effect?The mean age of the participants was 18.95 (SD 1.82). Contraryto assumption, women did not hold more fixed mindsets than men. InAmong adult samples, investigations of gender and mindset have53
Intelligence 64 (2017) 52–59B.N. Macnamara, N.S. RupaniTable 1Study 1 descriptive statistics.Intelligence mindsetTalent mindsetRaven's Adv. MatricesTable 2Study 1 regression analyses.FemalesMalestp4.20 (1.05)3.95 (1.16)0.65 (0.13)3.71 (1.06)3.69 (1.22)0.67 (0.11)2.301.09 0.770.0230.2780.445Note. Standard deviations in parentheses. Higher mindset scores correspond to more of agrowth mindset. Raven's Adv. Matrices Raven's Advanced Progressive Matrices.EstimateSEBetat-Valuep-ValueIntelligence mindsetInterceptGenderRaven'sGender Raven's3.720.48 0.36 0.430.160.211.411.810.22 0.04 0.0423.462.25 0.25 0.24 0.0010.0260.8010.815Talent mindsetInterceptGenderRaven'sGender Raven's3.680.270.58 0.240.180.241.582.030.110.06 0.0220.751.110.37 0.12 0.0010.2690.7120.905Note. Raven's Raven's Advanced ProgressiveBeta standardized regression coefficient.Matrices.SE standarderror.4.3. DiscussionContrary to claims that women have more fixed mindsets than men,we found that women were significantly more likely to endorse agrowth intelligence mindset relative to their male counterparts. Thecorrelation between intelligence and mindset was significant for thewomen (but not the men), indicating that more intelligent women weremore likely to hold fixed mindsets. However, when submitting the datato regression, the interaction between gender and intelligence was notsignificant. A limitation of this study is that the sample consisted ofcollege students and a restricted range of intelligence. We thus soughtto test these relationships with an online sample to examine a wider ageand intelligence range.5. Study 25.1. Method5.1.1. ParticipantsOne hundred forty-seven (72 female) MTurk workers completed thestudy in exchange for payment. MTurk workers are generally morerepresentative of U.S. demographics than convenience face-to-facesamples (Berinsky, Huber, and Lenz, 2012; Ross, Irani, Silberman,Zaldivar, and Tomlinson, 2010). While MTurk workers have likelyparticipated in other online studies, the majority is not habitual studyrespondents and their presence in a sample has not been found tosubstantially or significantly affect the outcome (Berinsky et al., 2012).In sum, certain safeguards must be put in place when conducting onlinesamples (e.g., instructional manipulation checks; Oppenheimer,Meyvis, and Davidenko, 2009). However, data generally support thenotion that studies conducted on MTurk are no more susceptible tobiases and demand characteristics than standard methods of data collection (Casler, Bickel, and Hackett, 2013).Fig. 1. Study 1 results. Relationships between intelligence and mindsets for women andmen.fact, women had greater growth intelligence mindsets than men. Scoreson talent mindset and Raven's Advanced Progressive Matrices were similar for the females and males (Table 1).To test whether a “bright woman effect” existed, we conductedcorrelational analyses between intelligence and mindset for women andmen. For women, we observed negative correlations between intelligence and intelligence mindset (r 0.35, p 0.007) and between intelligence and talent mindset (r 0.28, p 0.033) indicating that the more intelligent the woman, the more likely she was toendorse a fixed mindset. For men, these relationships were not significant (r 0.03, p 0.865 and r 0.10, p 0.528). See Fig. 1.However, correlation analyses divided by gender do not test whether the correlations between women and men are significantly different. To test whether there was a significant interaction betweengender and intelligence predicting mindset, we conducted regressionanalyses. Raven's Advanced Progressive Matrices scores were centered.Men were coded as 0, women as 1. Neither intelligence nor theGender Intelligence interaction significantly predicted mindset. Theonly significant finding was a main effect of gender when intelligencemindset was the outcome variable, such that on average, women heldmore of a growth mindset than men. See Table 2.5.1.2. Materials and procedureFollowing a brief demographics questionnaire, participants completed the online version of the intelligence mindset questionnaire usedin Study 1, followed by the talent mindset questionnaire used in Study1, and then the same odd numbered Raven's Advanced ProgressiveMatrices problems used in Study 1. Participants had 10 min to completeas many as Raven's problems as possible. Prior to beginning the Raven'sproblems participants received 3 easy practice problems and feedbackabout why the correct answers were correct.5.2. ResultsBased on piloting, we found that participants needed approximately20 min to read all instructions and complete the demographics questionnaire, the intelligence mindset questionnaire, the talent mindset54
Intelligence 64 (2017) 52–59B.N. Macnamara, N.S. Rupaniwomen. Specifically, as with intelligence mindset, the more intelligentthe relatively younger female, the more likely she is to hold a fixedmindset, but as age increases, the relationship between talent mindsetand intelligence reverses for women such that the more intelligent therelatively older female the more likely she is to hold a growth mindset.The relationship between talent mindset and intelligence is considerably weaker for males and remains so regardless of age.Table 3Study 2 descriptive statistics.AgeIntelligence mindsetTalent mindsetRaven's Adv. MatricesFemalesMalestp42.60 (14.09)3.37 (1.24)3.55 (1.19)0.46 (0.21)38.02 (12.53)3.63 (1.20)3.68 (1.18)0.47 (0.19)1.93 1.23 0.62 0.430.0560.2230.5350.6685.3. DiscussionNote. Standard deviations in parentheses. Higher mindset scores correspond to more of agrowth mindset. Raven's Adv. Matrices Raven's Advanced Progressive Matrices.Similar to Study 1, we found that the higher young womens' scoreson the Raven's Advanced Progressive Matrices were, the more of a fixedintelligence mindset they endorsed having. Unlike Study 1, we observedthe opposite pattern for younger males, such that the higher their scoreon the Raven's Advanced Progressive Matrices, the more of an intelligence growth mindset they endorsed having. Also, while in Study 1we found that women had more of a growth mindset on average thanmales (contrary to the mindset literature assumption), we found nodifference between the genders in Study 2. Given the inconsistentpatterns across age for the two mindset measures in Study 2 and thedifferent patterns between the young men across the two studies, weconducted a third study.questionnaire, the practice Raven's Advanced Progressive Matricesproblems, and the Raven's Advanced Progressive Matrices problems. Inline with recommendations to use safeguards when using MTurk, weremoved participants (n 9) who completed the study in 5 mingiven that this rate made it unlikely that they could carefully read theinstructions and respond to the survey and test items. Eleven moreparticipants were removed for failing to correctly respond to the majority of the 3 practice problems; these practice problems were designedto be easy to answer correctly and thus, failing to correctly answer 2/3or 3/3 indicated that either the test was too difficult to measure theirintelligence or that they were not attempting to answer correctly. Theaverage age for the remaining 127 participants (67 females) was 40.43(SD 13.52).As can be seen in Table 3, age and scores on the mindset measuresand intelligence measure were similar between females and males.There were no significant correlations between mindset and intelligence for either females or males. To examine the effects of eachpredictor variable and their interactions we conducted regression analyses. Continuous variables were centered. Male was coded as 0, femaleas 1. As can be seen in Table 4, there were no main effects of gender,intelligence, or age for either type of mindset. However, there weresignificant 3-way Age Raven's Gender interactions for bothmindset types. As illustrated in Fig. 2, for intelligence mindset and intelligence, the 3-way interaction appears to be driven by differences inthe relationship between mindset and intelligence between genders atyounger ages. Specifically, the more intelligent the relatively youngerfemale, the more likely she is to hold a fixed mindset, whereas the moreintelligent the relatively younger male, the more likely he is to hold agrowth mindset. As age increases, the relationships between intelligence mindset and intelligence are buffered. For talent mindset andintelligence, the 3-way interaction appears to be driven by a reversal inthe relationship between mindset and intelligence as age increases for6. Study 36.1. Method6.1.1. ParticipantsTwo hundred (99 female) MTurk workers completed the study inexchange for payment.6.1.2. Materials and procedureThe materials and procedure were identical to Study 2 with thefollowing exceptions. We moved the demographics questionnaire to theend of the study and additionally asked participants about the highestlevel of education they had achieved. We also did not allow participantsto move past the Raven's Advanced Progressive Matrices until the 10min time limit had expired.6.2. ResultsGiven that we did not allow participants to advance until the 10 minexpired on the Raven's Advanced Progressive Matrices and based on ourpilot results indicating that the study takes approximately 20 min, weremoved participants (n 28) who completed the task in fewer than13 min. That is, we assumed that it was unlikely participants werecarefully reading and responding if spending fewer than 3 min total onthe instructions, Raven's practice problems, intelligence mindset questionnaire, talent mindset questionnaire, and demographics questionnaire. As with Study 2, we additionally removed participants whoincorrectly responded to the majority of the practice problems (n 9).One hundred sixty-three participants (87 females) were included in theanalyses.The mean age was 37.26 years old (SD 12.82). Education levelwas coded as the following: 0 some high school, 1 high schooldiploma, 2 some college/associates degree, 3 bachelor's degree,4 graduate degree. As can be seen in Table 5, measured variableswere similar between females and males.Correlation analyses revealed a significant negative relationship(r 0.33) between talent mindset and education level for males suchthat the more of a fixed talent mindset a male had, the greater hishighest education level attained. To examine the effects of each predictor variable and their interactions we conducted regression analyses.Continuous variables were centered. Male was coded as 0, female as 1.As can be seen in Table 6, for intelligence mindset there were no maineffects of gender, intelligence, age, or education. However, there was aTable 4Study 2 regression analyses.EstimateSEBetat-Valuep-ValueIntelligence mindsetInterceptGenderAgeRaven'sGender Raven'sGender AgeRaven's AgeGender Ravens Age3.57 0.17 0.000.28 0.950.01 0.110.250.160.220.010.841.090.020.060.08 0.07 0.030.05 0.120.07 0.230.3822.14 0.75 0.190.34 0.870.49 1.762.94 0.0010.4520.8500.7370.3880.6260.0810.004Talent mindsetInterceptGenderAgeRaven'sGender Raven'sGender AgeRaven's AgeGender Ravens Age3.64 0.05 0.00 0.280.820.01 0.070.170.160.220.010.831.080.020.060.083 0.02 0.03 0.050.110.04 0.150.2822.78 0.25 0.18 0.340.760.30 1.162.09 0.0010.8070.8570.7340.4520.7680.2500.038Note. Raven's Raven's Advanced ProgressiveBeta standardized regression coefficient.Matrices.SE standarderror.55
Intelligence 64 (2017) 52–59B.N. Macnamara, N.S. RupaniFig. 2. Study 2 results. Relationships between intelligenceand mindsets for women and men. Age is dichotomized forillustration purposes. Younger younger than the medianage. Older equal to or older than the median age.Table 5Study 3 descriptive statistics.Table 6Study 3 regression analyses.FemalesAgeIntelligence mindsetTalent mindsetRaven's Adv. MatricesEducation Level36.80 (12.60)3.80 (1.19)3.89 (1.16)0.44 (0.21)2.51 (0.83)Males37.78 (13.13)4.02 (1.12)4.04 (1.09)0.46 (0.21)2.51 (0.93)t 0.48 1.17 0.88 0.59 0.05p0.6310.2460.3790.5600.957Note. Standard deviations in parentheses. Higher mindset scores correspond to more of agrowth mindset. Raven's Adv. Matrices Raven's Advanced Progressive Matrices.significant Age Raven's interaction and a significant 3-way (Gender Age Raven's) interaction. The interactions appear to be drivenby a slight positive relationship between intelligence and growthmindset among younger participants and a strong relationship betweenfixed mindset and intelligence among relatively older male participants(see Fig. 3). None of the predictors or their interactions significantlypredicted talent mindset.According to the mindset literature, those with growth mindsetsembrace challenge and thus have higher academic achievement thantheir fixed mindset counterparts who are debilitated by failure (e.g.,Blackwell et al., 2007; Dweck, 2006) especially if female and especiallyif a bright female (Dweck, 2000; Dweck and Leggett, 1988). Wetherefore tested whether gender, age, intelligence, mindset, or any oftheir interactions (with the exception of crossing the two mindsetmeasures) predicted highest level of education attained. As can be seenin Table 7, there were no significant effects. The largest effects (thoughnot significant) were intelligence mindset, talent mindset, Gender Intelligence mindset, Gender Talent mindset, and Raven's Intelligence mindset. As can be seen in Fig. 4, if anything, more of a fixedmindset was beneficial for achieving higher levels of education, andEstimateSEBetat-Valuep-ValueIntelligence mindsetInterceptGenderAgeRaven'sGender AgeGender Raven'sAge Raven'sGender Age Raven's4.07 0.25 0.01 0.340.020.86 0.120.160.130.180.010.660.010.890.050.07 0.11 0.05 0.060.140.11 0.250.2530.32 1.35 0.45 0.521.240.96 2.192.16 0.0010.1800.6560.6040.2160.3380.0300.032Talent mindsetInterceptGenderAgeRaven'sGender AgeGender Raven'sAge Raven'sGender Age Raven's4.08 0.190.01 0.670.000.88 0.080.060.130.180.010.650.010.880.050.07 0.090.07 0.130.030.12 0.190.1030.86 1.070.57 1.040.271.01 1.580.88 0.0010.2860.5710.2980.7840.3160.1160.383Note. Raven's Raven's Advanced ProgressiveBeta standardized regression coefficient.Matrices.SE standarderror.slightly more so for males. Additionally, if anything, more of a fixedintelligence mindset was beneficial for achieving higher levels of education for individuals below the median score for intelligence.6.3. DiscussionContrary to the assumptions of the mindset literature, we did notobserve that women held fixed mindsets more so than men.Additionally, we did not observe a gender intelligence interaction,which could have suggested that the brighter the female, the more56
Intelligence 64 (2017) 52–59B.N. Macnamara, N.S. RupaniFig. 3. Study 3 results. Relationships between intelligenceand mindsets for women and men. Age is dichotomized forillustration purposes. Younger younger than the medianage. Older equal to or older than the median age.likely she was to hold a fixed mindset. We did observe aGender Age Raven's three-way interaction for intelligencemindset, but not for talent mindset. We did not observe that the more ofa growth mindset the higher the level of education attained. However,this measure was limited as a short ordinal scale rather than a trulycontinuous measure.7. Synthesis of studies and general discussionWe sought to examine two key claims from the mindset literature:(1) women have more of a fixed mindset than men and (2) the moreintelligent the female, the more likely she is to hold a fixed mindset.Across three studies, we found no evidence that adult females haveTable 7Study 3 regression analyses predicting highest educational attainment.InterceptGenderAgeRaven'sMindset: IMindset: TGender AgeGender Raven'sGender Mindset IGender Mindset TAge Raven'sAge Mindset: IAge Mindset: TRaven's Mindset: IRaven's Mindset: TGender Age Raven'sGender Age Mindset: IGender Age Mindset: TAge Raven's Mindset: IAge Raven's Mindset: TGender Age Raven's Mindset: IGender Age Raven's Mindset: TEstimateSEBetat-Valuep-Value2.53 0.010.000.170.17 0.38 0.000.78 0.350.280.04 0.00 0.000.81 0.420.010.000.010.000.04 0.06 020.020.430.410.160.010.010.090.070.090.08 0.010.070.040.23 0.23 0.010.14 0.340.280.12 0.03 0.020.20 0.110.030.060.060.000.12 0.15 0.1223.19 0.090.530.311.09 1.62 0.081.09 1.961.620.95 0.11 0.081.87 1.040.230.260.300.010.540.60 0.68 0.5470.495Note. Raven's Raven's Advanced Progressive Matrices. Mindset: I Intelligence mindset. Mindset: T Talent mindset. SE standard error. Beta standardized regression coefficient.57
Intelligence 64 (2017) 52–59B.N. Macnamara, N.S. RupaniFig. 4. Study 3 results. Relationships between mindsetsand academic achievement for women and men.Intelligence is dichotomized for illustration purposes. Lessintelligent Raven's Advanced Progressive Matrices scorebelow the median. More intelligent Raven's AdvancedProgressive Matrices score equal to or above the median.fixed-effect meta-analysis results for the Gender Raven's interactions were B 0.06, 95% CI [ 1.20, 1.33], p 0.921 for intelligence mindset, and B 0.74, 95% CI [ 0.52, 2.01], p 0.249 for talentmindset.We did observe significant Gender Age Raven's interactions inboth studies that included a wide age range (Studies 2 and 3). However,the patterns of results driving these interactions were
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