E. Jenkins' Thesis

Running head: CONFIDENCE AND PERFORMANCE

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Howard University

The Effect of Confidence in Past Performance on Future Performance

A Senior Thesis

Submitted to the Faculty

of the College of Arts and Sciences

of

HOWARD UNIVERSITY

in partial fulfilment of the requirements for graduation from the

Honors Program

Department of Psychology

by

Elizabeth D. Jenkins

Washington, D.C.

April 8, 2016


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Acknowledgements

I would like to express thanks to my supervisor, Dr. Jamie Barden, who

patiently guided me with expertise and knowledge. I appreciate and admire his

knowledge of psychology and his assistance in writing this thesis. Even more, I am

grateful for his faith in me as a student, his timeliness, and his constant push for

excellence.

A very special thank you goes to Dr. Afiya Fredericks, whose motivation and

encouragement pushed me to continue with my thesis. Dr. Fredericks is a professor

and mentor who continues to positively influence my life.

Appreciation also goes to Dr. Angela Cole, Amanda Terry, and other faculty

or teachers within the Department of Psychology’s Honors Program. Thank you all

for support and guidance in completing this thesis.

I would also like to thank my friends and family for the support they provided

through my journey. Their love, encouragement, and editing assistance helped me to

finish my thesis.

Finally, I appreciate the financial support of the National Science Foundation

granted to Dr. Barden, which funded the research discussed in this thesis.


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Table of Contents

Acknowledgements………………………………………………………………….ii

Abstract ……………………………………………………………………………….1

The Effect of Confidence in Past Performance on Future Performance………………3

Introduction……………………………………………………………………………3

Method………………………………………………………………………………...8

Participants and design……………………………………………………………......8

Procedure……………………………………………………………………………...8

Predictor Variables……………………………………………………………………8

Self-reported strong/poor quiz 1 performance………………………………...9

Evaluative certainty…………………………………………………………...9

Dependent Measures …………………………………………………………………9

Math performance……………………………………………………………..9

Results ……………………………………………………………………………….10

Self-reported strong/poor quiz 1 performance……………………………….10

Second math quiz performane ………………………………………………10

Discussion……………………………………………………………………………12

References……………………………………………………………………………16

Table 1.Means and Standard Deviations for Continuous Variables…………………..18

Table 2. Predictors of Actual Performance on Math Test 2…………………………19

Figure 1. Actual performance on the second math test for those perceiving poor and

strong performers with either high or low confidence on the first math test………...20


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Abstract

Recent literature has found that the convergent experiences of the activation

of negative, self-relevant stereotypes and the perception of having performed poorly

on the task can lead to greater certainty in that poor performance, a process called

stereotype validation (Clark, Thiem, Barden, Stuart & Evans, 2015). The separate

self-validation hypothesis states that meta-cognitive certainty in our own thoughts and

judgments increases the consequences of those thoughts and judgments for attitudes

and behaviors (Petty, Briñol, & Tormala, 2002). The current research hypothesized

that confidence in one’s perceived performance has an effect on future performance.

To test this hypothesis, each participant completed two sets of difficult questions.

After the first math test, participants indicated whether their performance was strong

or poor and how confident they were in that assessment. Then they completed a

second math test. Participants who reported high confidence in their strong

performance on the first test performed better on the second test, even controlling for

actual performance on the first test. Conversely, students who reported high

confidence in their poor performance on the first test performed worse on the second

test. However, participants that reported low confidence in their strong or poor

performance on the first test did not perform significantly better or worse on the

second test. Overall, the data suggests that there is an effect of high confidence in past

performance on future performance. This finding expands our understanding of how


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self-validation and the meta-cognition of confidence can have critical performance

outcomes for African American students’ standardized tests in STEM disciplines.

Keywords: certainty, meta-cognition, Black, academic performance


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The Effect of Confidence in Past Performance on Future Performance

Introduction

An abundance of research has been conducted to investigate the lack of

minorities, such as Blacks, Latinos, or Native Americans, within science, technology,

engineering, and math (STEM) fields (Tsui, 2007). STEM fields have traditionally

been and remain dominated by White males (Riegle-Crumb & King, 2010). This

remains the case despite the many Blacks, Latinos, and Native Americans interested

in these fields. In fact, Tsui’s (2007) research suggests minority freshmen are just as

likely, if not more, to enroll in science and engineering studies, compared to their

White peers. However, these students are also more likely to change to a non-science

major (Tsui, 2007). Thus, minorities, such as Blacks, are less likely to graduate with a

STEM major. One-third of college students are Black, Latino, or Native-American,

yet only 11% of STEM jobs are filled by members of these minority groups (Tsui,

2007). In a separate line of work, Kao (2000) measures high school students’

perceptions of students of their own and other races in terms of performance

stereotypes. Research shows that Blacks have relatively high educational aspirations,

but low academic performance when compared to Asian and White students that have

low educational aspirations with high academic performance (Kao, 2000). These

findings suggest that student’s cultural stereotypes about themselves regarding

intellectual inferiority could lead to low participation in STEM fields among

racial/ethnic minority groups.


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Stereotype threat has been defined as a psychological predicament in which

individuals fear that their performance may be evaluated in light of a negative

stereotype of their group (Steele & Aronson, 1995). The research on stereotype threat

suggests that self-relevant stigmas can negatively affect the standardized test

performance and school outcomes of Blacks (Aronson et al., 1999). Aronson and

colleagues’ (1999) have found that African-American students perform significantly

worse than Whites on standardized test, but only when conditions are set to activate

stereotype threat condition. Thus, stereotype threat can lead to lower performance and

disengagement from the domain (Aronson et al., 1999). Past research has shown that

merely presenting African-American students with a diagnostic test can induce

stereotype threat.

Recent research shows that after completing a performance task a different

process can occur called stereotype validation. In this case, activating negative, self-

relevant stereotypes after completion of a task can lead people to feel more certain

that they performed poorly. Clark and colleagues’ (2015) research shows that self-

relevant stereotypes can validate evaluations of previous performance and influence

later achievement within the same domain. Clark and Thiem (under review) showed

they researched the effect of stereotype validation as it relates to gender by testing

both male and females on tests related to childcare and science. Results of the studies

indicated that negative and positive stereotype validation can affect future

achievement if the stereotype coincides with a person’s thoughts about their


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performance. Even more, higher certainty in perceived poor performance resulted in

lower performance on the second test. Contrastingly, high certainty in perceived

strong performance on the first test predicted higher achievement on the next test. A

positive validation of stereotypes helped improve later performance as well.

Stereotype validation could result in members of stigmatized groups’ having

decreased esteem in their abilities and changing academic or career goals (Clark &

Thiem, under review). The current research will explore the effects of racial

stereotype validation.

In another study, Clark and colleagues (2008) investigated the effects of the

meta-cognition of confidence in stereotypes regarding socioeconomic status on

judgment. They argued that activating a stereotype validates, or increases confidence

in, stereotype consistent thoughts. In two experiments, participants were given

information about a child and their test performance to evaluate the child’s

performance (strong or poor). Then, they were given a description to activate

stereotypes regarding SES (high or low). The results of the study supported past

research that stereotypes can validate thoughts about other people. Thus, stereotypes

can create the metacognition of confidence in one’s stereotype consistent thoughts

(Clark, Wegener, Briñol, & Petty, 2008).

Metacognition has been defined as people’s thoughts about their thoughts or

thought processes. Some researchers have expanded the definition of metacognition

to include people’s knowledge about their own and others’ mental states, processes,


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and beliefs (Petty, Briñol, Tormala, & Wegener, 2007). Meta-cognitive confidence is

important because thoughts held with more confidence have a greater impact on

judgments or behavior (Petty, Briñol, Tormala, & Wegener, 2007). In particular,

certainty is important to the self-validation hypothesis, which states that the degree of

certainty one has in his or her thoughts should have a significant impact on the

attitudes or evaluations that result (Petty, Briñol, & Tormala, 2002). Having thoughts

is not enough to have an impact on judgment, but having confidence in those thoughts

will have an impact (Briñol, & Petty, 2009). Thus, the correlation between thoughts

and attitudes is stronger when thought confidence is high (Briñol & Petty, 2009). The

self-validating role of confidence in thoughts is consistent with the overall role of

certainty as an amplifying agent for attitudes as well. No research has tested whether

stereotype validation can have an impact on Blacks’ academic performance.

Petty, Briñol, and Tormala (2002) tested the self-validation hypothesis, the

notion that confidence in a person’s own thoughts has an effect on persuasion. The

study investigated how low or high confidence increases or decreases persuasion.

Participants were college students who were asked to write down their thoughts

regarding a certain issue. Before sharing their thoughts on the issue, the participants

received two strong and two weak arguments supporting the issue. Participants were

then asked to rate how confident they were in the validity of their own thoughts.

Higher confidence in one’s thoughts resulted in the thoughts having more of an


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impact on attitudes. So, the amount of confidence a person has in their thoughts

determines the ability for those thoughts to predict attitudes.

Previous research has found that certainty in one’s thoughts has an impact on

attitudes and attitudes can serve as predictors of behavior (Fazio & Zanna, 1978). In

efforts to further this research, the current study hypothesized that certainty might

have an impact on performance behavior. Additionally, the current study examined

the impact certainty and the self-validation hypothesis has on Black students’

academic performance. Specifically, researchers examined how an individual's

certainty about their past academic performance affected their future academic

performance. It was hypothesized that high certainty in strong performance would

lead to better future performance. Conversely, high certainty in poor performance was

predicted to lead to a worse future performance. Thus, the predictions were derived

from the thought validation hypothesis, with thoughts being replaced with judgments

of past academic performance.

Research Overview

The current research examined certainty in past academic performance and its effect

on future performance. Past research led researchers to hypothesize that performance

judgments held with high confidence would have a greater impact on future

performance than judgments held with low confidence. Within the current research,

each participant completed two sets of GRE math questions. After the first math test,


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participants evaluated their performance as either strong or poor. Then, they indicated

how confident they were in their assessment of their performance on an 11-point

scale. Afterwards, participants completed a second math test that was easier than the

first.

Method

Participants and design.

A total of 173 participants completed the study. However, only participants

who self-identified as Black were included in the analysis. Thus, the sample consisted

of 147 undergraduates at Howard University, an historically Black university, located

in the eastern region of the United States. The participants of the study received

partial course credit for participating. One hundred seventeen participants were

female and the remaining 32 were male. Participants’ ages ranged from 18 to 27 (Mage

= 18.61, SD = 1.24). The majority of the participants self-identified their ethnicity as

African-American (83.7%), 10.2% identified as Caribbean, 5.4% as African, and the

remaining 7% identified as Hispanic or Hispanic-American.

Procedure.

A maximum of six participants were included in a single session. Once the

participants arrived to the lab, they were greeted by a Black experimenter. Each

participant was then seated at a private computer station that was visually isolated

from the other participants. Next, participants were told that the experiment was being


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conducted in order to understand the differences in people’s abilities to solve a

number of different types of problems. Then, the participants completed a set of 12

difficult GRE math questions, each with 5 multiple choice options.

After these measures, participants were asked to answer additional questions

about their math abilities and perception of their performance on the previous math

test. They rated their certainty regarding their performance and the likelihood that

they would pursue math-related careers.

After this, the participants completed a second set of 6 math questions

intended to be somewhat easier than the first 12 math questions. Lastly, the

participants were asked questions regarding their demographics and were debriefed.

Predictor Variables.

Self-reported strong/poor quiz 1 performance. After the first math test,

participants evaluated their performance on a dichotomous scale, as either “strong” or

“poor”. The evaluations were dummy coded so that “poor” was 0 and “strong” was 1.

Evaluative certainty. Afterwards, participants reported their certainty

regarding their performance assessment of the first math quiz on 11-point scales. The

first four items matched each participant’s response on the dichotomous performance

evaluation. For example, participants who rated their performance as “strong”

received the following four questions: “How certain are you that your performance on

the test was strong” (1= not at all certain to 11= very certain); “How sure are you that

your performance on the test was strong?” (1= not all sure to 11=very sure); “I am


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certain that I performed strongly on the test” (1= not all certain to 11=very certain);

and “I am sure that I performed strongly on the test” (1= strongly disagree to

11=strongly agree). Participants who rated their performance as “poor” received

similar questions, but the words strong/strongly were replaced by poor/poorly.

Cronbach’s alpha was ∝ = .94 for poor performers (n = 115) and ∝ = .95 (n = 32) for

strong performers.

Dependent Measures.

Math performance. The first math test consisted of 12 questions and the total

number of correct answers from the first math test served as a covariate. The second

math test consisted of 6 questions intended to be easier than the first set.

Results

Self-reported strong/poor quiz 1 performance. On the dichotomous

performance evaluation, the majority (n = 115; 78.2 %) of participants reported their

performance as “poor.” The remaining (n = 32; 21.8%) participants reported having

“strong” performance. These findings were expected given the difficulty of the math

questions. Also, to reduce stereotype threat, participants were greeted with a Black

experimenter and were not told the test was diagnostic of math ability or intelligence.

These procedures have been shown to reduce stereotype threat and its effects (Steele,

1997).


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Second Math Quiz Performance. A hierarchical multivariate regression

analysis was performed where math performance on the second quiz was regressed on

strong/poor performance, certainty in that performance, and their interaction, with

actual performance on the first quiz as a covariate (M = 4.33, SD = 2.57). Since

certainty was continuous, the impact was evaluated at one standard deviation above

and below the mean. The results are displayed in Table 1 and 2.

The results indicated that the main effect of self-reported strong versus poor

first test performance on second math test performance was not significant, b = -1.77,

t(142) = -1.43, p = .15. Additionally, the main effect of confidence on second math

test performance was not significant, b = -.10, t(142), p = .10. The effect of

performance on the first math test was used as a covariate, b = .13, t(142) = 2.07, p =

.04. This statistically significant result indicated that there is a significant main effect

of first math test performance on second math test performance.

Most important, this analysis revealed a statistical significant interaction

between first test performance evaluation and evaluative certainty as they predict

actual performance on the second test, b = .42, t (142) = 2.70, p = .01 (see Figure 1).

This interaction can be explored by looking at poor and strong performers separately.

Poor performers with low confidence in their performance correctly answered three

questions (Mlow = 3.06) on the second test, whereas those with high confidence in

their poor performance correctly answered slightly fewer questions (Mhigh = 2.62),

although this difference was not statistically significant, b = -.10, t(142) = -1.66, p =


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.10. Students with low confidence in their strong performance on the first test

correctly answered approximately three questions (Mlow = 3.52), whereas students

with high confidence in their strong performance correctly answered more questions

(Mhigh = 5.03) on the second math test. This difference was statistically significant, b

= .32, t(142) = 2.27, p = .02. This statistically significant result provides evidence that

high certainty guides behavior.

As an alternative approach, the performance estimate by confidence

interaction can be explored by looking at participants’ low and high in confidence

separately. On the one hand, students with low confidence did not perform

significantly better or worse on the second test if they perceived they performed

strongly or poorly on the first test, b = .46, t(142) = .92, p = .36. On the other hand,

those with high confidence in their performance did significantly better (Mstrong =

4.27) on the second test if they perceived their performance on the first test as strong.

Thus, high confidence guided future outcomes, b = 2.41, t(142) = 4.81, p < .001.

Even more, high confidence had a greater impact when the participant had a positive

perception of their first math test performance.

Discussion

The study provided evidence that the level of confidence in a past

performance judgment determines that judgment has an effect on future performance.

As shown in Figure 1, students with high confidence in their strong performance on

the first math test performed significantly better on the second math test than students


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with high confidence in their poor performance. Even when controlling for the actual

performance on the first math test, this significant effect of the meta-cognition was

found. Thus, these results align with past findings that judgments and evaluations

held with higher certainty guide behavior to a greater extent (Petty, Briñol, Tormala,

& Wegner, 2007). Conversely, for participants who had low confidence in their past

performance, perceiving strong or poor performance on the first test had no impact on

the second math test. Therefore, performance evaluations held with low certainty do

not guide behavior.

Thus, the current research provides support that the meta-cognition of

certainty has an effect on future performance outcomes and that the extent of

certainty appears to be a factor in the relationship between perception and

performance. To ensure that metacognition had an impact on future performance on

its own, actual performance on the first math test served as a covariate. The

performance difference occurred after participants confirmed their own belief in their

performance and was not a result of any feedback they received on how well they

actually did. In other words, it was the mere act of the student confirming their

thoughts that impacted performance on the second math test.

The implications of these findings are very pertinent to the future performance

outcomes of students, especially Blacks and other minorities. Unlike stereotype

threat, which occurs only during a test, self-validation can occur any time during the

rest of life, and still have an impact on future performance. Even outside the scope of


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academia, high confidence in one’s ability will guide behavior and thus influence life

outcomes.

These findings are also an important step in beginning to understand how to

improve Blacks’ academic performance and involvement within STEM fields.

Literature indicates that Black students have high educational aspirations, but lower

academic achievements compared to their Asian or white counterparts (Kao, 2000).

These low achievements are possibly a result of stereotype threat. The negative

stigmas attached to Blacks’ academic performance and intellect undermine their

actual performance and provoke disengagement in academic domains (Aronson, et al,

1999). However, the current findings suggest that if Blacks were to become highly

confident following strong performances, then academic performance and interest,

even in STEM fields such as mathematics, might increase.

Even so, to better understand meta-cognition and how it can positively

influence Blacks’ academic performance, future research would need to investigate

the causes of low certainty and its marginal impact on future performance. Future

research could also create solutions on how to improve an individual’s perception

regarding their performance and then improve their confidence in that performance.

Furthermore, it would be beneficial for future research to study the length of time

certainty lasts. In time, is certainty in a past performance forgotten? In general, more

research is needed to gain a better understanding of certainty and how it relates to

Blacks’ academic performance and interest in STEM.


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Conclusion

Today, there is a lack of racial minorities, including Blacks, within STEM

fields, leading to questions about why that is the case. The current research

contributes to existing research to develop a better understanding of what predicts

Black academic performance on standardized tests in STEM fields. The results

indicate that many Blacks believe that they perform poorly on math tests.

Furthermore, students who were extremely confident in their poor performance

performed marginally worse on the next exam even when controlling for how well

they actually did on the first exam. On the other hand, students who were confident in

their strong performance on the first test performed even better on the second test.

Thus, the findings suggest that if Black students become confident that they perform

well then their academic performance would improve overall over repeated tests.

More research is needed to confirm that certainty, stereotype validation, and self-

validation directly affect performance. Even more, future research needs to focus on

the creation of interventions aimed at resolving the negative, academic self-

evaluations of Black students.


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References Aronson, J., Lustina, M. J., Good, C., Keough , K., Steele, C. M., & Brown, J.

(1999). When white men can't do math: necessary and sufficient factors in stereotype threat. Journal of Experimental Social Psychology, 35, 29-46.

Clark, J.K., Thiem, K.C., Barden, J., Stuart, J.O., & Evans, A.T. (2015).

Stereotype Validation: The Effects of Activating Negative Stereotypes After Intellectual Performance. Journal of Personality and Social Psychology, 108, 531-552.

Clark, J.K., & Thiem, K. C. (under review). Stereotype validation and

intellectual performance: negative and positive implications for future achievement.

Clark, J. K., Wegener, D. T., Briñol, P., & Petty, R. E. (2008). Discovering

that the shoe fits: Discovering the self-validating role of stereotypes. Psychological Science , 20, 846-852.

Fazio, R. H., & Zanna, M. P. (1978). Attitudinal qualities relating to the

strength of the attitude-behavior relationship. Journal of Experimental Social Psychology, 14, 398-408.

Kao, G. (2000). Group images and possible selves among adolescents: linking

stereotypes to expetations by race and ethnicity . Sociological Forum , 14, 407-330.

Petty, R. E., Briñol, P., & Tormala, Z. L. (2002). Thought confidence as a

determinant of persuasion: the self-validation hypothesis. Journal of Personality and Social Psychology, 82, 722-741.

Petty, R. E., Briñol, P., Tormala, Z. L., & Wegener, D. T. (2007). The role of

meta-cognition in social justice. In E. T. Higgins, & A. Kruglanski, Social Psychology: Handbook of Basic Principles (pp. 1-36). Guilford Press: New York.

Riegle-Crumb, C., & King, B. (2010). Questioning a white male advantage in

STEM: examining disparities in college major by gender and race/ethnicity. Educational Researcher, 39, 656-664.


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Steele, C. M. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American psychologist, 52, 613-629.

Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test

performance of African Americans. Journal of personality and social psychology, 69, 797-811.

Tsui, L. (2007). Effective strategies to increase diversity in STEM fields: a review of

the research literature. The Journal of Negro Education, 76, 555-581.


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Table 1 Means and Standard Deviations for Continuous Variables

Variable M SD

Age 18.61 1.24 Confidence 7.61 2.32

First Test Performance

4.33 2.57

Second Test Performance

3.20 1.75

Note. First and second math test performance are based on the number of correct answers out of 12 and 6 questions respectively.


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Table 2 Predictors of Actual Performance on Math Test 2 Variables b SE t(142) p

Constant 3.02 .51 5.92 .00 Strong/Poor Performance

-1.77 1.23 -1.43 .15

Confidence -.10 .06 -1.66 .10 Interaction .42 .16 2.70 .01 Covariate .13 .06 2.07 .00

Note. Covariate is actual performance on the first math test (M =4.33, SD =2.57).


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Figure 1. Actual performance on the second math test for those perceiving poor or strong performance on the first test who had either high or low confidence in their perception of their first test performance. Points are plotted at +1 SD and -1 SD in confidence.

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1.5

2

2.5

3

3.5

4

4.5

5

5.5

LowConfidence HighConfidence

ActualPerform

ance

Poor

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