Encouraging Girls in 

Math and Science

IES Practice Guide

NCER 2007-2003

U.S. DEPARTMENT OF EDUCATION
Encouraging Girls in 

Math and Science

IES Practice Guide

SEPTEMBER 2007

Diane F. Halpern (Chair) 

Claremont McKenna College

Joshua Aronson 

New York University

Nona Reimer 

John Malcom Elementary School, California 

California State University, Fullerton

Sandra Simpkins 

Arizona State University

Jon R. Star 

Harvard University

Kathryn Wentzel 

University of Maryland, College Park

NCER 2007-2003

U.S. DEPARTMENT OF EDUCATION
This report was prepared for the National Center for Education Research, Institute of Education 

Sciences, under contract no. ED-05-CO-0026 to Optimal Solutions Group, LLC. 

Disclaimer

The opinions and positions expressed in this practice guide are the authors’ and do not necessarily 

represent the opinions and positions of the Institute of Education Sciences or the U.S. Department 

of Education. This practice guide should be reviewed and applied according to the specific needs of 

the educators and education agencies using it and with full realization that it represents only one 

approach that might be taken, based on the research that was available at the time of publication. 

This practice guide should be used as a tool to assist in decision-making rather than as a “cookbook.” 

Any references within the document to specific education products are illustrative and do not imply 

endorsement of these products to the exclusion of other products that are not referenced.

U.S. Department of Education 

Margaret Spellings 

Secretary

Institute of Education Sciences 

Grover J. Whitehurst 

Director

National Center for Education Research 

Lynn Okagaki 

Commissioner

September 2007

This report is in the public domain. While permission to reprint this publication is not necessary, 

the citation should be:

Halpern, D., Aronson, J., Reimer, N., Simpkins, S., Star, J., and Wentzel, K. (2007). Encouraging Girls 

in Math and Science (NCER 2007-2003). Washington, DC: National Center for Education Research, 

Institute of Education Sciences, U.S. Department of Education. Retrieved from http://ncer.ed.gov.

This report is available for download on the IES website at http://ncer.ed.gov.

Alternative Formats 

On request, this publication can be made available in alternative formats, such as Braille, large print, 

audiotape, or computer diskette. For more information, call the Alternative Format Center at 

(202) 205-8113. 
( iii )

Encouraging Girls in 

Math and Science

Contents

Preamble from the Institute of Education Sciences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

About the authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Disclosures of potential conflicts of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Encouraging girls in math and science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Scope of the practice guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Checklist for carrying out the recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Recommendation 1: Teach students that academic abilities are expandable and improvable. . . . . . . . 11

Recommendation 2: Provide prescriptive, informational feedback. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Recommendation 3: Expose girls to female role models who have succeeded in math and science. . . . 19

Recommendation 4: Create a classroom environment that sparks initial curiosity 

and fosters long-term interest in math and science. . . . . . . . . . . . . . . . . . . . . . . . 23

Recommendation 5: Provide spatial skills training. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Appendix: Technical information on the studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
( iv )

List of Tables and Figures

Tables

Table 1. Institute of Education Sciences Levels of Evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Table 2. Recommendations and corresponding Levels of Evidence to support each . . . . . . . . . . . . . . . . 7

Table 3. Percent of degrees awarded to women in engineering subfields in 1966, 1985, and 2004 . . . 20

Figures

Figure 1. Percent of degrees awarded to women by major field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Figure 2. Percent of public high school graduates who completed various mathematics 

and science courses in high school, by gender: 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Figure 3. NAEP mathematics scores by highest course completed and gender: 2005 . . . . . . . . . . . . . . 5

Figure 4. NAEP science scores by highest course completed and gender: 2005 . . . . . . . . . . . . . . . . . . . 5
Encouraging Girls in Math and Science

( v )

1

 Field and Lohr (1990).

Preamble from the 

Institute of Education 

Sciences

What is a practice guide?

The health care professions have embraced a mechanism for assembling and communicating evidencebased advice to practitioners about care for specific 

clinical conditions. Variously called practice guidelines, 

treatment protocols, critical pathways, best-practice 

guides, or simply practice guides, these documents are 

systematically developed recommendations about the 

course of care for frequently encountered problems, 

ranging from physical conditions such as foot ulcers to 

socioemotional issues such as navigating the demands 

of adolescence.1

Practice guides are similar to the products of typical 

expert consensus panels in that they reflect the views 

of those serving on the panel, as well as the social 

decision processes that come into play as the positions 

of individual panel members are forged into statements 

that all are willing to endorse. However, practice guides 

are generated under three constraints that do not 

typically apply to consensus panels. The first is that a 

practice guide consists of a list of discrete recommendations that are intended to be actionable. The second is 

that those recommendations taken together are intended to comprise a coherent approach to a multifaceted 

problem. The third, which is most important, is that 

each recommendation is explicitly connected to the 

level of evidence supporting it (e.g., strong, moderate, 

and low). The levels of evidence are usually constructed 

around the value of particular types of studies for 

drawing causal conclusions about what works. Thus 

one typically finds that the top level of evidence is 

drawn from a body of randomized controlled trials, 

the middle level from well-designed studies that do not 

involve randomization, and the bottom level from the 

opinions of respected authorities. Levels of evidence 

can also be constructed around the value of particular 

types of studies for other goals, such as the reliability 

and validity of assessments.

Practice guides can also be distinguished from 

systematic reviews or meta-analyses, which employ 

statistical methods to summarize the results of studies 

obtained from a rule-based search of the literature. 

Authors of practice guides seldom conduct the types of 

systematic literature searches that are the backbone of a 

meta-analysis, though they take advantage of such work 

when it is already published. Instead they use their 

expertise to identify the most important research with 

respect to their recommendations, augmented by a 

search of recent publications to assure that the research 

citations are up-to-date. Further, the characterization 

of the quality and direction of evidence underlying 

a recommendation in a practice guide relies less on a 

tight set of rules and statistical algorithms and more on 

the judgment of the authors than would be the case in 

a high-quality meta-analysis. Another distinction is that 

a practice guide, because it aims for a comprehensive 

and coherent approach, operates with more numerous 

and more contextualized statements of what works than 

does a typical meta-analysis.

Thus practice guides sit somewhere between consensus 

reports and meta-analyses in the degree to which 

systematic processes are used for locating relevant 

research and characterizing its meaning. Practice guides 

are more like consensus panel reports than metaanalyses in the breadth and complexity of the topic 

that is addressed. Practice guides are different from 

both consensus reports and meta-analyses in providing 

advice at the level of specific action steps along a 

pathway that represents a more-or-less coherent and 

comprehensive approach to a multifaceted problem. 

Practice guides in education at the Institute 

of Education Sciences

The Institute of Education Sciences (IES) publishes 

practice guides in education to bring the best available evidence and expertise to bear on the types of 

systemic challenges that cannot be addressed by single 

interventions or approaches. Although IES has taken 

advantage of the history of practice guides in health 

care to provide models of how to proceed in education, 

education is different from health care in ways that 

may require that practice guides in education have 

somewhat different designs. Even within health care, 

where practice guides now number in the thousands, 
Practice Guide

( vi )

there is no single template in use. Rather, one finds 

descriptions of general design features that permit 

substantial variation in the realization of practice 

guides across subspecialties and panels of experts.2

Accordingly, the templates for IES practice guides 

may vary across practice guides and change over 

time and with experience. 

The steps involved in producing an IES-sponsored 

practice guide are first to select a topic, which is 

informed by formal surveys of practitioners and 

spontaneous requests from the field. Next, a panel chair 

is recruited who has a national reputation and up-todate expertise in the topic. Third, the chair, working in 

collaboration with IES, selects a small number of panelists to co-author the practice guide. These are people 

the chair believes can work well together and have the 

requisite expertise to be a convincing source of recommendations. IES recommends that at least one of the 

panelists be a practitioner with considerable experience 

relevant to the topic being addressed. The chair and the 

panelists are provided a general template for a practice 

guide along the lines of the information provided in 

this preamble. They are also provided with examples of 

practice guides. The practice guide panel works under 

a short deadline of 6 to 9 months to produce a draft 

document. The expert panel interacts with and receives 

feedback from staff at IES during the development of 

the practice guide, but the panel members understand 

that they are the authors and thus responsible for the 

final product.

One unique feature of IES-sponsored practice guides is 

that they are subjected to rigorous external peer review 

through the same office that is responsible for independent review of other IES publications. A critical task of 

the peer reviewers of a practice guide is to determine 

whether the evidence cited in support of particular 

recommendations is up-to-date, and that studies 

of similar or better quality that point in a different 

direction have not been ignored. Peer reviewers also are 

asked to evaluate whether the evidence grades assigned 

to particular recommendations by the practice guide 

authors are appropriate. A practice guide is revised as 

necessary to meet the concerns of external peer reviews 

and to gain the approval of the standards and review 

staff at IES. The process of external peer review is 

carried out independently of the office and staff within 

IES that initiated the practice guide.

Because practice guides depend on the expertise of their 

authors and their group decision-making, the content 

of a practice guide is not and should not be viewed as 

a set of recommendations that in every case depends 

on and flows inevitably from scientific research. It 

is not only possible but also likely that two teams of 

recognized experts working independently to produce a 

practice guide on the same topic would generate 

products that differ in important respects. Thus consumers of practice guides need to understand that they 

are, in effect, getting the advice of consultants. These 

consultants should, on average, provide substantially 

better advice than educators might obtain on their 

own because the authors are national authorities who 

have to achieve consensus among themselves, justify 

their recommendations in terms of supporting 

evidence, and undergo rigorous independent peer 

review of their product. 

2

 American Psychological Association (2002). 
Encouraging Girls in Math and Science

( vii )

About the authors

Diane F. Halpern is the Director of the Berger 

Institute for Work, Family, and Children, and Professor 

of Psychology at Claremont McKenna College. She 

earned her Ph.D. in Psychology from the University 

of Cincinnati. Her research focuses on the development 

of critical thinking skills and on gender differences.

Joshua Aronson is an associate professor of Developmental, Social, and Educational Psychology at New 

York University. He earned his Ph.D. in Psychology 

from Stanford University. His research focuses on 

“stereotype threat” and minority student achievement. 

Nona Reimer has been an elementary school teacher 

in Capistrano Unified School District, California, for 

20 years. She is also a part-time faculty member in biology at the California State University at Fullerton. She 

earned her B.A. in History and Environmental Studies 

from the University of California, Santa Barbara and 

her Multiple Subjects Credential from California State 

University, Hayward. She currently teaches fifth grade 

at John S. Malcom Elementary School, a National Blue 

Ribbon School.

Sandra Simpkins is an assistant professor in the 

School of Social and Family Dynamics at Arizona State 

University. She earned her Ph.D. in Psychology from 

the University of California, Riverside. Her research 

focuses on children’s pursuits, such as their participation in after-school activities or enrollment in an 

elective science course.

Jon R. Star is an assistant professor in the Graduate 

School of Education at Harvard University. He 

earned a Ph.D. in Education and Psychology from the 

University of Michigan. Star is a former middle and 

high school mathematics teacher. His research focuses 

on students’ learning of middle and secondary school 

mathematics.

Kathryn Wentzel is a professor of Human Development at the University of Maryland, College Park. She 

earned a Ph.D. in Psychological Studies in Education 

from Stanford University. Her research focuses on 

teachers, peers, and parents as social motivators of 

young adolescents’ classroom behavior and academic 

accomplishments.

Disclosures of potential 

conflicts of interest

Practice guide panels are composed of individuals 

who are nationally recognized experts on the topics 

about which they are rendering recommendations. 

IES expects that such experts will be involved professionally in a variety of matters that relate to their work 

as a panel. Panel members are asked to disclose their 

professional involvements and to institute deliberative 

processes that encourage critical examination of the 

views of panel members as they relate to the content 

of the practice guide. The potential influence of panel 

members’ professional engagements reported by each 

panel member is further muted by the requirement that 

they ground their recommendations in evidence that 

is documented in the practice guide. In addition, the 

practice guide is subjected to independent external peer 

review prior to publication, with particular focus on 

whether the evidence related to the recommendations 

in the practice guide has been appropriately presented. 

The professional engagements reported by each panel 

member that appear most closely associated with the 

panel recommendations are noted below.

Dr. Aronson has developed interventions aimed at 

changing students’ conceptions of intelligence in 

order to improve their academic achievement. He 

has also developed interventions to reduce stereotype 

threat. These interventions are not referenced in the 

practice guide. 
Encouraging Girls in Math and Science

( 1 )

Introduction

The goal of this practice guide is to formulate specific 

and coherent evidence-based recommendations that 

educators can use to encourage girls in the fields of 

math and science. The target audience is teachers 

and other school personnel with direct contact with 

students, such as coaches, counselors, and principals. 

The practice guide includes specific recommendations 

for educators and the quality of evidence that supports 

these recommendations.

We, the authors, are a small group with expertise 

on this topic. The range of evidence we considered 

in developing this document is vast, ranging from 

experiments, to trends in the National Assessment of 

Educational Progress (NAEP) data, to correlational and 

longitudinal studies. For questions about what works 

best, high-quality experimental and quasi-experimental 

studies, such as those meeting the criteria of the What 

Works Clearinghouse, have a privileged position. In all 

cases, we pay particular attention to findings that are 

replicated across studies. 

Although we draw on evidence about the effectiveness 

of specific practices, we use this information to make 

broader points about improving practice. In this 

document, we have tried to take findings from research 

or practices recommended by experts and describe 

how the use of this recommendation might actually 

unfold in school settings. In other words, we aim to 

provide sufficient detail so that educators will have 

a clear sense of the steps necessary to make use of the 

recommendation. 

A unique feature of practice guides is the explicit and 

clear delineation of the quality and quantity of evidence 

that supports each claim. To this end, we adapted a 

semi-structured hierarchy suggested by the Institute 

of Education Sciences. This classification system helps 

determine whether the quality and quantity of available 

evidence in support of a practice is of strong, moderate, 

or low quality. This system appears in table 1 below. 

Strong refers to consistent and generalizable evidence 

that an approach or practice causes improved 

performance in math or science among girls or that an 

assessment is reliable and valid. Moderate refers either 

to evidence from (a) studies that allow strong causal 

conclusions but which cannot be generalized with 

assurance to the target population because, for example, 

the findings have not been sufficiently replicated, or 

(b) studies that are generalizable but have more causal 

ambiguity than offered by experimental designs, for 

example, statistical models of correlational data or 

group comparison designs where equivalence of the 

groups at pretest is uncertain. For assessments, moderate refers to high quality studies from a small number 

of samples that are not representative of the whole 

population. Low refers to expert opinion based on 

reasonable extrapolations from research and theory on 

other topics and/or evidence from studies that do not 

meet the standards for moderate or strong evidence. 

For each recommendation, we include an appendix 

that provides more technical information about the 

studies and our decisions regarding level of evidence for 

the recommendation. To illustrate the types of studies 

reviewed, we describe one study in considerable detail 

for each recommendation. Our goal in doing this is to 

provide interested readers with more detail about the 

research designs, the intervention components, and 

how impact was measured. By including a particular 

study, we do not mean to suggest that it is the best 

study reviewed for the recommendation or necessarily 

an exemplary study in any way. 
Practice Guide

( 2 )

Table 1. Institute of Education Sciences Levels of Evidence

Strong

In general, characterization of the evidence for a recommendation as strong requires both studies 

with high internal validity (i.e., studies whose designs can support causal conclusions), as well as 

studies with high external validity (i.e., studies that in total include enough of the range of participants 

and settings on which the recommendation is focused to support the conclusion that the results 

can be generalized to those participants and settings). Strong evidence for this practice guide is 

operationalized as: 

• A systematic review of research that generally meets the standards of the What Works 

Clearinghouse (see http://ies.ed.gov/ncee/wwc/) and supports the effectiveness of a program, 

practice, or approach with no contradictory evidence of similar quality; OR

• Several well-designed, randomized, controlled trials or well-designed quasi-experiments that 

generally meet the standards of the What Works Clearinghouse and support the effectiveness of a 

program, practice, or approach, with no contradictory evidence of similar quality; OR

• One large, well-designed, randomized, controlled, multisite trial that meets the standards of the 

What Works Clearinghouse and supports the effectiveness of a program, practice, or approach, 

with no contradictory evidence of similar quality; OR

• For assessments, evidence of reliability and validity that meets the Standards for Educational and 

Psychological Testing.3

Moderate

In general, characterization of the evidence for a recommendation as moderate requires studies 

with high internal validity but moderate external validity, or studies with high external validity but 

moderate internal validity. In other words, moderate evidence is derived from studies that support 

strong causal conclusions but where generalization is uncertain, or studies that support the generality 

of a relationship but where the causality is uncertain. Moderate evidence for this practice guide is 

operationalized as:

• Experiments or quasi-experiments generally meeting the standards of the What Works 

Clearinghouse and supporting the effectiveness of a program, practice, or approach with small 

sample sizes and/or other conditions of implementation or analysis that limit generalizability, and no 

contrary evidence; OR

• Comparison group studies that do not demonstrate equivalence of groups at pretest and therefore 

do not meet the standards of the What Works Clearinghouse but that (a) consistently show 

enhanced outcomes for participants experiencing a particular program, practice, or approach and 

(b) have no major flaws related to internal validity other than lack of demonstrated equivalence at 

pretest (e.g., only one teacher or one class per condition, unequal amounts of instructional time, 

highly biased outcome measures); OR

• Correlational research with strong statistical controls for selection bias and for discerning influence 

of endogenous factors and no contrary evidence; OR

• For assessments, evidence of reliability that meets the Standards for Educational and 

Psychological Testing4

 but with evidence of validity from samples not adequately representative of 

the population on which the recommendation is focused. 

Low

In general, characterization of the evidence for a recommendation as low means that the 

recommendation is based on expert opinion derived from strong findings or theories in related 

areas and/or expert opinion buttressed by direct evidence that does not rise to the moderate or 

strong levels. Low evidence is operationalized as evidence not meeting the standards for the 

moderate or high levels.

3 American Educational Research Association, American Psychological Association, and National Council on Measurement in Education 

(1999). 

4

 Ibid. 
Encouraging Girls in Math and Science

( 3 )

Encouraging girls in 

math and science

Overview

Although there is a general perception that men do 

better than women in math and science, researchers 

have found that the differences between women’s and 

men’s math- and science-related abilities and choices 

are much more subtle and complex than a simple 

“men are better than women in math and science.” 5

 

In fact, experts disagree among themselves on the 

degree to which women and men differ in their 

math- and science-related abilities.6

 A quick review of 

the postsecondary paths pursued by women and men 

highlight the areas in math and science where women 

are not attaining degrees at the same rate as men. 

In 2004, women earned 58 percent of all bachelor’s 

degrees, 78 percent of bachelor’s degrees in psychology, 62 percent in biological sciences, 51 percent in 

chemistry, 46 percent in mathematics, 25 percent 

in computer sciences, 22 percent in physics, and 

21 percent in engineering.7

 In general, women earn 

substantial proportions of the bachelor’s degrees in 

math and the sciences, except in computer sciences, 

physics, and engineering. At the master’s level, women 

earned 59 percent of all master’s degrees. The pattern 

at the master’s degree level is similar (see figure 1). At 

the doctoral level, however, gender imbalances become 

more prevalent, including in math and chemistry (see 

figure 1). Women earned 45 percent of all doctoral 

degrees, but they earn less than one-third of all doctoral 

degrees in chemistry, computer sciences, math, physics, 

and engineering.8 In contrast, women earn 67 percent 

of the doctoral degrees in psychology and 44 percent 

in other social sciences.9 This disproportionate representation in math and science graduate degrees is also 

reflected in math and science career pathways. While 

women make up nearly half of the U.S. workforce, 

they make up only 26 percent of the science and 

engineering workforce.10 The question many are asking 

is why women are choosing not to pursue degrees 

5

 See Hyde (2005), Spelke (2005), and Halpern (2000) for recent discussions of the literature.

6

 See Gallagher and Kaufman (2005) for a collection of chapters representing different researchers’ views.

7

 National Science Foundation (2006d).

8

 Ibid.

9

 Ibid.

10 National Science Foundation (2006c).

Figure 1. Percent of degrees awarded to women by major field

Bachelor’s

Master’s

Doctorate

All Fields Biological

Sciences

Chemistry Computer

Science

Mathematics Physics Engineering Psychology Social Sciences

SOURCE: National Science Foundation, Science and Engineering Degrees: 1966-2004. 

90

80

70

60

50

40

30

20

10

0

57.6 59.1

45.4

62.5

58.6

51.1

46.3 46.2

31.7 31.2

45.9 45.4

28.4

21.8

25.2

15.5

20.5 21.1

17.6

77.8 78.1

67.3

54.5 55.9

44

25.1

20.5
Practice Guide

( 4 )

and careers in the physical sciences, engineering, or 

computer science. Several potential reasons for the 

gender disparity include previous coursework, ability, 

interests, and beliefs.

An examination of course-taking patterns shows that 

girls are taking math and science courses in high 

school. On the 2005 National Assessment of Educational Progress (NAEP) High School Transcript Study, 

girls who graduated from high school, on average, 

earned slightly more credits in mathematics and science 

(7.3) than boys earned (7.1). Boys, however, earned 

slightly more credits in computer-related courses (1.1) 

than girls earned (0.8).11 Figure 2 shows the percentages of female and male high school graduates in 2000 

that completed math and science courses. Although 

a greater percentage of boys completed physics (34 

percent) and calculus (12 percent) than girls (physics, 

29 percent; calculus, 11 percent), girls were more 

likely to complete biology (girls, 93 percent; boys, 89 

percent), advanced placement (AP) or honors biology 

(girls, 19 percent; boys, 14 percent), and chemistry 

(girls, 66 percent; boys, 58 percent) than boys were. 

Although some gender differences are present in high 

school math and science course enrollments, similarities between the genders is also common. This gender 

parity in course-taking patterns may be less surprising 

than it appears, given that high school graduation 

requirements typically include multiple science courses, 

as well as mathematics.

A second reason for the observed differences in college 

and occupational choices may be that males and 

females have variant math and science abilities, as 

measured by standardized tests. Although girls generally do as well as, or better than, boys on homework 

assignments and course grades in math and science 

classes,12 boys tend to outscore girls when tested on 

11 Shettle, Roey, Mordica, et al. (2007).

12 College Board (2006, August 29); Shettle, Roey, Mordica, et al. (2007). 

Figure 2. Percent of public high school graduates who completed various mathematics and science courses in 

high school, by gender: 2000

0

10

20

30

40

50

60

70

80

90

100
Encouraging Girls in Math and Science

( 5 )

0

50

100

150

200

250

300

Figure 3. NAEP mathematics scores by highest course completed and gender: 2005 

0

50

100

150

200

250

300

Figure 4. NAEP science scores by highest course completed and gender: 2005 
Practice Guide

( 6 )

13 See Halpern, Benbow, Geary, et al. (2007) for a more thorough discussion of this point.

14 Shettle, Roey, Mordica, et al. (2007).

15 Wainer and Steinberg (1992).

16 Andre, Whigham, Hendrickson, et al. (1999); Herbert and Stipek, (2005); Jacobs, Lanza, Osgood, et al. (2002); Simpkins and Davis-Kean 

(2005); Wigfield, Eccles, Mac Iver, et al. (1991).

17 Simpkins and Davis-Kean (2005); Updegraff and Eccles (1996).

18 Pajares (2006).

the same content in high-pressure situations, such as 

standardized tests with time limits. These tests are typically not linked to instructed curriculum, and so can be 

understood to be measures of more general abilities in 

math and science.13 For example, on the 2005 NAEP 

math and science assessments, girls scored lower than 

boys when controlling for highest course completed at 

all levels, except the lowest level (see figures 3 and 4).14

Performance differences on timed standardized tests 

do not necessarily mean that girls are not as capable as 

boys in math or science. Researchers have found, for 

instance, that SAT math scores underpredict young 

women’s performance in college math courses.15 This 

suggests that it is not ability, per se, that hinders girls 

and women from pursuing careers in math and science. 

If not ability, then what?

Areas where consistent gender differences have emerged 

are children’s and adolescents’ beliefs about their 

abilities in math and science, their interest in math 

and science, and their perceptions of the importance 

of math and science for their futures. In general, 

researchers have found that girls and women have less 

confidence in their math abilities than males do and 

that from early adolescence, girls show less interest 

in math or science careers.16 This gender difference is 

interesting, and somewhat puzzling, given that males 

and females generally enroll in similar courses and 

display similar abilities (at least as measured by course 

grades). In other words, girls, particularly as they move 

out of elementary school and into middle and high 

school and beyond, often underestimate their abilities 

in mathematics and science. However, it is important 

to note that not all girls have less confidence and interest in mathematics and science, and that girls, as well 

as boys, who have a strong self-concept regarding their 

abilities in math or science are more likely to choose 

and perform well in elective math and science courses 

and to select math- and science-related college majors 

and careers.17 This is noteworthy because it suggests 

that improving girls’ beliefs about their abilities could 

alter their choices and performance. Theory and 

empirical research suggest that children’s beliefs about 

their abilities are central to determining their interest 

and performance in different subjects, the classes they 

choose to take, the after-school activities they pursue, 

and, ultimately, the career choices they make.18

What can teachers do to encourage girls to choose 

career paths in math- and science-related fields? One 

major way to encourage girls to choose careers in 

math and science is to foster the development of 

strong beliefs about their abilities in these subjects– 

beliefs that more accurately reflect their abilities – 

and more accurate beliefs about the participation of 

women in math- and science-related careers (see table 

2). Our first two recommendations, therefore, focus 

on strategies that teachers can use to strengthen girls’ 

beliefs regarding their abilities in math and science: (1) 

Teach students that academic abilities are expandable 

and improvable (Level of Evidence: Moderate); and 

(2) Provide prescriptive, informational feedback (Level 

of Evidence: Moderate). Our third recommendation 

addresses girls’ beliefs about both their own abilities 

and the participation of women in math- and sciencerelated careers: (3) Expose girls to female role models 

who have succeeded in math and science (Level of 

Evidence: Low).
Encouraging Girls in Math and Science

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Table 2. Recommendations and corresponding Levels of Evidence to support each 

Recommendation Level of Evidence

1. Teachers should explicitly teach students that academic abilities are expandable 

and improvable in order to enhance girls’ beliefs about their abilities. Students 

who view their cognitive abilities as fixed from birth or unchangeable are more 

likely to experience decreased confidence and performance when faced with 

difficulties or setbacks. Students who are more confident about their abilities in 

math and science are more likely to choose elective math and science courses 

in high school and more likely to select math and science-related college 

majors and careers.

Moderate

2. Teachers should provide students with prescriptive, informational feedback 

regarding their performance. Prescriptive, informational feedback focuses 

on strategies, effort, and the process of learning (e.g., identifying gains in 

children’s use of particular strategies or specific errors in problem solving). 

Such feedback enhances students’ beliefs about their abilities, typically 

improves persistence, and improves performance on tasks. 

Moderate

3. Teachers should expose girls to female role models who have achieved in math 

or science in order to promote positive beliefs regarding women’s abilities in 

math and science. Even in elementary school, girls are aware of the stereotype 

that men are better in math and science than women are. Exposing girls to 

female role models (e.g., through biographies, guest speakers, or tutoring by 

older female students) can invalidate these stereotypes. 

Low

4. Teachers can foster girls’ long-term interest in math and science by choosing 

activities connecting math and science activities to careers in ways that do 

not reinforce existing gender stereotypes and choosing activities that spark 

initial curiosity about math and science content. Teachers can provide ongoing 

access to resources for students who continue to express interest in a topic 

after the class has moved on to other areas.

Moderate

5. Teachers should provide opportunities for students to engage in spatial skills 

training. Spatial skills training is associated with performance in mathematics 

and science.

Low
Practice Guide

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Girls are more likely to choose courses and careers 

in math and science if their interest in these fields 

is sparked and cultivated throughout the school 

years.19 Our fourth recommendation focuses on the 

importance of fostering long-term interest (Level of 

Evidence: Moderate) and provides concrete strategies 

that teachers might use to promote greater interest in 

math and science.

A final way to encourage girls in math and science 

is to help them build the spatial skills that are crucial 

to success in many math- and science-related fields, 

such as physics, engineering, architecture, geometry, 

topology, chemistry, and biology. Research suggests 

that spatial skills, on which boys have typically outperformed girls, can be improved through specific types 

of training. Thus, our final recommendation is that 

teachers provide students, especially girls, with specific 

training in spatial skills (Level of Evidence: Low).

Scope of the 

practice guide

This practice guide provides five recommendations for 

encouraging girls in math and science. These recommendations together form a coherent statement: To 

encourage girls in math and science, we need to begin 

first with their beliefs about their abilities in these areas, 

second with sparking and maintaining greater interest 

in these topics, and finally with building associated 

skills. Our specific recommendations cover these three 

domains in a representative but not exhaustive way. In 

particular, we have chosen to focus on specific recommendations that have the strongest research backing 

available. In addition, we limit our focus to recommendations that teachers can carry out in the classroom 

and that do not require systemic change within a 

school district. We remind the reader that students’ 

choices to pursue careers in math and science reflect 

multiple influences that accumulate over time. We 

have identified practices that elementary, middle, and 

high school teachers can implement during instruction 

that we believe would increase the likelihood that girls 

and women will not prematurely decide that careers in 

math and science are not for them.

19 Wigfield, Eccles, Schiefele, et al. (2006). 
Encouraging Girls in Math and Science

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Checklist for carrying out 

the recommendations

Recommendation 1: Teach students that 

academic abilities are expandable and 

improvable.

 Teach students that working hard to learn new 

knowledge leads to improved performance.

 Remind students that the mind grows stronger 

with use and that over time and with continued 

effort, understanding the material will get easier.

Recommendation 2: Provide prescriptive, 

informational feedback.

 Provide students with feedback that focuses on 

strategies used during learning, as opposed to 

simply telling them whether they got an answer 

correct. This strategy encourages students to correct 

misunderstandings and learn from their mistakes.

 Provide students with positive feedback about 

the effort they expended on solving a difficult 

problem or completing other work related to their 

performance.

 Avoid using general praise, such as “good job,” 

when providing feedback to individual students or 

an entire class.

 Make sure that there are multiple opportunities for 

students to receive feedback on their performance.

Recommendation 3: Expose girls and young 

women to female role models who have 

succeeded in math and science.

 Invite older girls and women who have succeeded 

in math- or science-related courses and professions 

to be guest speakers or tutors in your class.

 Assign biographical readings about women 

scientists, mathematicians, and engineers, as part of 

students’ assignments.

 Call attention to current events highlighting the 

achievements of women in math or science.

 When talking about potential careers, make 

students aware of the numbers of women who 

receive advanced degrees in math- and sciencerelated disciplines.

 Provide girls and young women with information 

about mentoring programs designed to support 

students who are interested in mathematics and 

science.

 Encourage parents to take an active role in providing opportunities for girls to be exposed to women 

working in the fields of math and science.

Recommendation 4: Create a classroom 

environment that sparks initial curiosity 

and fosters long-term interest in math and 

science.

 Embed mathematics word problems and science 

activities in contexts that are interesting to both 

boys and girls. 

 Provide students with access to rich, engaging 

relevant informational and narrative texts as they 

participate in classroom science investigations. 

 Capitalize on novelty to spark initial interest. That 

is, use project-based learning, group work, innovative tasks, and technology to stir interest in a topic.

 Encourage middle and high school students to 

examine their beliefs about which careers are 

typically female-oriented and which are typically 

male-oriented. Encourage these students to learn 

more about careers that are interesting to them 

but that they believe employ more members of the 

opposite gender.

 Connect mathematics and science activities to 

careers in ways that do not reinforce existing 

gender stereotypes of these careers.

Recommendation 5: Provide spatial skills 

training.

 Recognize that children may not automatically 

recognize when spatial strategies can be used to 

solve problems and that girls are less likely to 

use spatial strategies than boys. Teach students 

to mentally image and draw spatial displays in 

response to mathematics and science problems. 

 Require students to answer mathematics and 

science problems using both verbal responses and 

spatial displays.

 Provide opportunities for specific training in spatial 

skills such as mental rotation of images, spatial 

perspective, and embedded figures.
( 10 )
Encouraging Girls in Math and Science

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Recommendation 1: Teach students that academic abilities 

are expandable and improvable.

To enhance girls’ beliefs about their abilities, we recommend that 

teachers understand and communicate this understanding to students: 

Math and science abilities—like all abilities—can be improved through 

consistent effort and learning. Research shows that even students 

with considerable ability who view their cognitive abilities as fixed or 

unchangeable are more likely to experience greater discouragement, 

lower performance, and, ultimately, reduce their effort when they 

encounter difficulties or setbacks. Such responses may be more likely in 

the context of math, given stereotypes about girls’ innate mathematics 

abilities.20 In contrast, students who tend to view their abilities as 

expandable tend to keep trying in the face of frustration in order to 

increase their performance. To help girls and young women resist negative reactions to the difficulty of 

math and science work, it can be very helpful for them to learn that their math and science abilities can 

improve over time with continuous effort and engagement.

Level of evidence: Moderate

The panel judges the level of evidence supporting this 

recommendation to be moderate, based on the two 

small experimental studies that examined the effect of 

this practice for improving K–12 students’ performance 

on math,21 one experimental study that examined the 

effect of this strategy for improving college students’ 

general academic performance,22 and supporting correlational research demonstrating the relation between 

students’ beliefs about the stability and malleability of 

intellectual abilities and their performance.23

Brief summary of evidence to support 

the recommendation

What students believe about the nature of intelligence 

and ability affects their achievement.24 Some students 

believe that people, in general, are born with a fixed 

amount of intelligence, such that some people are born 

smart and others less smart and that little can be done 

to change this. Similarly, some students believe that 

their abilities were determined at birth and cannot be 

changed. An alternative way to think about intelligence 

or ability is that it is not fixed but can be improved 

through hard work and effort. Research shows that 

children who view intelligence as a fixed trait or believe 

that their own abilities cannot be changed tend to 

pursue “performance goals.” That is, they tend to be 

more concerned with demonstrating their intelligence 

and prefer to complete tasks that will show that they 

are “smart.” In contrast, students who believe that intelligence or ability can be improved with effort are more 

likely to pursue learning goals.25 That is, they tend to 

be more concerned with learning new material and are 

more likely to seek to master difficult material, even if 

doing so does not make them look “smart” (e.g., they 

might not be able to solve problems initially). When 

tasks become more challenging, students who believe 

that abilities or intelligence cannot be changed are more 

likely to become anxious, downgrade their assessment 

of their ability, and give up. However, students who 

believe that abilities can be improved through effort 

and hard work are more likely to respond to challenge 

with increased effort. In the long run, the students who 

are able to persist in their attempts to master difficult 

material perform better than the students who doubt 

their ability and give up.26

20 See Dweck (2006) for a recent discussion focused on girls’ beliefs about intelligence.

21 Good, Aronson, and Inzlicht (2003); Blackwell, Trzesniewski, and Dweck (2007). 

22 Aronson, Fried, and Good (2002).

23 Weiner (1986); Graham (1991); see Dweck (1999) for an overview of research in this area.

24 Grant and Dweck (2003).

25 Dweck (1999); Dweck and Leggett (1988). 

26 Utman (1997). 
Practice Guide

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These different orientations toward learning may 

have long-term implications. For example, if a child’s 

goal is to look smart, she may shy away from challenging tasks with potential for failure in favor of easier 

tasks with higher potential for success. In addition, 

if a child believes that intelligence or abilities are fixed, 

then she is likely to attribute failure to lack of ability, 

and her belief in her own abilities may eventually 

decline. Thus, failures or challenges can have a negative 

impact on children who view intelligence or abilities 

as a fixed trait. In contrast, research shows that when 

students are taught that intelligence and abilities can 

be increased with hard work, their test scores and their 

grades improve.27

Finally, why is it important to foster girls’ belief in 

the malleability of intellectual abilities? As discussed 

in the overview, girls tend to lack confidence in their 

math and science abilities even when they do well in 

their math and science courses. Teaching girls that 

knowledge and intellectual skills increase, for example, 

when students learn how to solve problems that they 

previously could not do explicitly provides girls with a 

way to interpret failure that does not discourage them 

from persevering to master new material in class.

How to carry out the recommendation

To help modify students’ beliefs about their intelligence 

or abilities, teachers can: 

•	Expose students to and discuss the neuroscience

research that shows that brains grow new synaptic 

connections when new material is learned and 

practiced, thus making the brain more complex 

and “smarter”—that working hard to learn new 

knowledge leads to improved intelligence. Sports 

analogies can buttress this learning: practicing 

academic skills, like solving math problems, 

improves performance much like practicing 

free throws improves basketball performance 

or practicing serves helps one’s tennis game.28

•	When students are struggling, teachers can

explicitly remind their students that the 

mind grows stronger as a result of doing 

hard work, and that over time and with 

continued effort, understanding the material 

and solving the problems will get easier.29

•	Teachers can also remind students about the

malleability of intelligence when they make 

progress, pointing out that their brains are 

actively building new connections as they study.

Potential roadblocks and solutions

Roadblock 1.1. Some adults may believe that intelligence and abilities are innate or fixed and that people 

who are “naturally” good at something will excel in 

that domain. It can be difficult to convince students 

that effort will make a significant difference when 

some adults seem to favor “natural ability” explanations 

for success over “effort and hard work” explanations. 

Solution. Some teachers may view abilities and 

intelligence as static characteristics that are fixed at 

birth. Neurologists used to believe this as well, but 

they no longer do. Thus, teachers as well as students 

need to take the neuroscience seriously and examine 

and modify their preconceptions about the nature of 

human intelligence. Only then can they genuinely help 

both students and parents understand that our brains 

are constantly creating and refining new synaptic 

connections, based on our experiences and the activities we regularly practice. Teachers should consider 

the following two studies. In one, researchers found 

that cab drivers had enlarged portions of the part of 

the brain that is important in performing spatial tasks 

(right posterior hippocampus) relative to a control 

group of adults whose employment required less use of 

spatial navigational skills.30 Among the cab drivers in 

this study, the number of years spent driving taxis was 

positively correlated with the size of the right posterior 

hippocampus. In a related study, researchers found 

that in a sample of adults who were not taxi drivers, 

there was no correlation between size of the posterior 

hippocampus and navigational expertise.31 These two 

sets of findings suggest that experience with complex 

route finding caused the increased size of the relevant 

27 Aronson, Fried, and Good (2002); Good, Aronson, and Inzlicht (2003); Blackwell, Trzesniewski, and Dweck (2007). 

28 Good, Aronson, and Inzlicht (2003). 

29 Ibid.

30 Maguire, Gadian, Johnsrude, et al. (2000). 

31 Maguire, Spiers, Good, et al. (2003).
Encouraging Girls in Math and Science

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brain structure. This is just one example of research 

that underlines the fundamental flexibility of the 

human brain in creating new synaptic connections for 

tasks that are repeated and practiced over time.

Roadblock 1.2. By the time students enter high school, 

some girls perceive themselves to be less capable than 

boys in math and science. They may believe that their 

abilities in this domain are not significantly expandable or that they are innately less likely than boys to do 

well in these domains. 

Solution. Teachers will need to keep in mind that girls 

perform as well as or even better than boys in school, 

including on exams and course grades in math and 

science classes; boys outperform girls only when we 

look at scores on advanced standardized tests. Experts 

disagree as to why girls’ equal or superior classroom 

performance in math and science does not carry over 

to their performance on high-stakes standardized 

tests.32 Thus, teachers can emphasize to students that 

high scores on advanced standardized tests do not 

in the long run determine success in science- and 

math-related fields. Many different skills are needed 

for success in these domains, including the content 

knowledge gained in coursework and through experience, as well as excellent writing and communication 

skills. There is no reason to believe that girls are 

biologically programmed to perform less well than 

boys in math- and science-related careers, and there are 

many reasons to believe that women, once rare in math 

and science careers, will continue to close the gap, as 

they have for the past several decades. Again, the best 

way for teachers to respond with genuine encouragement to girls’ doubts about their innate aptitudes in 

math and science is to be clear that the male advantage 

in math has little grounding in science and is limited 

to standardized tests. Appreciating the fact that girls 

perform better on standardized math tests when they 

believe that their math abilities are not fixed is one 

powerful way to start.

32 Gallagher and Kaufman (2005).
( 14 )
Encouraging Girls in Math and Science

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Recommendation 2: Provide prescriptive, informational feedback.

We recommend that teachers provide students with prescriptive, 

informational feedback regarding their performance in math and 

science courses. Prescriptive, informational feedback focuses on 

strategies, effort, and the process of learning. Examples include 

identifying gains in children’s strategy use, praising effort, or identifying gaps or errors in problem-solving. Although this type of feedback 

overlaps with the type of feedback that teachers provide during formative assessment, this recommendation specifically targets feedback 

that focuses students’ attention on their beliefs about why they did or 

did not perform well on a particular task. Prescriptive, informational 

feedback enhances students’ beliefs about their abilities, typically 

improves persistence, and improves performance on tasks. In addition, students’ beliefs about their 

abilities are related to their math- and science-related choices.33

15

Level of evidence: Moderate

The panel judges the quality of the evidence on the 

relation between prescriptive, informational feedback 

and students’ beliefs about their math and science 

abilities and their performance on math- and sciencerelated tasks to be moderate, based on a set of small 

experimental studies using random assignment that 

focus specifically on children performing math or 

math-related tasks 34 and supporting research on the 

effects of different types of feedback on a variety of 

tasks.35 The supporting research on feedback includes 

many studies that vary in terms of design, including 

small experimental studies, longitudinal and crosssectional correlational studies, and qualitative studies. 

Many of the experimental studies on the effects of 

different types of feedback have been conducted 

with children. 

Brief summary of evidence to support 

the recommendation

Students often receive feedback regarding their 

performance in the form of grades, test scores, or 

statements from teachers regarding the accuracy of 

a response. However, all forms of feedback are not 

equal in their impact on students’ beliefs about their 

abilities in a given domain, such as math or science, nor 

in their impact on performance. In particular, when 

teachers provide specific, informational feedback in 

terms of strategies, effort, and the process of learning 

(e.g., “you worked really hard at that subtraction 

problem”), rather than general praise (e.g., “good job”) 

or feedback regarding global intelligence (e.g., “you’re 

smart”), students’ beliefs about their abilities and their 

performance are positively influenced.36 

Many teachers know that providing informational 

feedback helps create a positive learning environment. 

Indeed, the use of classroom formative assessment is 

linked to substantial learning gains.37 When teachers 

give informational feedback (e.g., pointing out to a 

student a specific problem in her logic rather than 

simply noting that the answer is incorrect) students’ 

achievement and attitudes improve.38 During wholeclass instruction, when teachers combine positive 

comments with specific information about how to 

solve a problem, students are less likely to report that 

they engage in self-defeating behaviors (e.g., putting 

off doing their homework until the last minute) or 

33 See Hackett (1985) for a classic study supporting this conclusion in the context of mathematics; Fouad and Smith (1996) discuss this 

relationship in middle school students.

34 Mueller and Dweck (1998); Elawar and Corno (1985); Miller, Brickman, and Bolen (1975).

35 See Bangert-Drowns, Kulik, Kulik, et al. (1991) for a synthesis of studies on feedback and Henderlong and Lepper (2002) for a recent 

review on the effects of praise on children’s intrinsic motivation.

36 Mueller and Dweck (1998); Elawar and Corno (1985); Miller, Brickman, and Bolen (1975).

37 See Black and Wiliam (1998) for a recent discussion of the literature on feedback and formative assessment.

38 Elawar and Corno (1985).
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avoid asking for help when they don’t understand 

assignments.39 In addition, research suggests that 

positive substantive feedback that provides information 

about students’ progress toward goals and progress in 

learning is related to children’s motivational beliefs, 

such as their self-concept of ability and self-efficacy. An 

observational study of math classrooms illustrates how 

including such feedback during instruction can support 

students’ self-efficacy in mathematics.40 Even though 

the research demonstrates the critical and potentially 

powerful role that appropriate feedback can play, it 

does not appear that teachers typically use prescriptive, 

informational feedback. In fact, a recent descriptive 

study of teacher feedback used in 58 third-grade 

mathematics classrooms suggests that the primary form 

of feedback teachers use during instruction is general 

praise, such as “that’s very good,” which does not 

provide any useful information to students.41

Experimental work suggests that feedback given in 

the form of praise focused on global intelligence (e.g., 

“you’re smart”) may have a negative impact on future 

learning behavior in comparison to praise about effort 

(e.g., “you must have worked hard”).42 Elementary 

school students who were given praise about their 

intelligence after correctly solving a problem were likely 

to attribute future failures to lack of ability, have lower 

interest, show less persistence on future tasks, and have 

a goal for future tasks of looking smart. In contrast, 

children who were given praise about their effort were 

more likely to believe that subsequent failure was due 

to lack of effort, show higher persistence on difficult 

tasks, and have a goal of mastering challenging tasks 

or concepts rather than just “looking smart.” Thus, 

teacher feedback that attributes student success to effort 

(e.g., “you’ve been working hard”) and task-specific 

ability (e.g., “you did very well at solving this division 

problem”) strengthens self-efficacy beliefs about 

mathematics. These beliefs, in turn, influence a child’s 

future persistence on difficult tasks and, ultimately, 

overall performance.

Finally, why is prescriptive, informational feedback 

important to enhancing girls’ beliefs about their 

abilities? As discussed in the overview, girls tend to 

lack confidence in their math and science abilities even 

when they do well in math and science courses. Providing informative feedback focuses students’ attention on 

what to do when they do not solve a problem correctly 

rather than letting girls attribute wrong answers to 

a lack of ability. When students experience success, 

providing informative feedback directs their attention 

to what they did to achieve that success (e.g., worked 

hard, tried multiple strategies, used the procedures in 

the correct order) rather than allowing girls to attribute 

that success to having a certain amount of ability.

How to carry out the recommendation

What can teachers do to make sure that the feedback 

they give students will help improve both their motivation to learn new material and their performance, even 

in the face of failure? 

•	Provide positive, substantive feedback to students

as they solve problems to encourage students to 

correct misunderstandings and learn from their 

mistakes.43 Teachers should create a classroom 

environment in which learning, improving, 

and understanding are emphasized. In such an 

environment, when children give an incorrect 

answer, it becomes an opportunity for learning. 

•	Highlight the importance of effort for succeeding

at difficult tasks. By attributing success to effort 

rather than to global intelligence, expectations 

for future success are supported. Praising general 

intelligence implies that natural intellectual gifts 

determine success (and failure) rather than effort; 

this can be a debilitating mindset for students 

when confronted with failure on a difficult task.44

•	Keep a balance between learning on the one hand

and performance on the other. Grades matter, 

but students who focus single-mindedly on their 

grades may come to care so much about performance that they sacrifice learning opportunities.45

39 Turner, Midgley, Meyer, et al. (2002). 

40 Schweinle, Turner, and Meyer (2006). 

41 Foote (1999).

42 Mueller and Dweck (1998).

43 Schweinle, Turner, and Meyer (2006); Turner, Midgley, Meyer, et al. (2002).

44 Mueller and Dweck (1998); see Foersterling (1985) for a review of research on attributional feedback. 

45 Dweck (2002); Mueller and Dweck (1998).
Encouraging Girls in Math and Science

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Potential roadblocks and solutions

Roadblock 2.1. Some teachers may find it difficult to 

focus on effort and strategy use rather than on performance. Too often, the attention of many students (and 

sometimes their parents) is on report card grades and 

exam scores. In addition, many teachers are required 

to assess and report performance in terms of grades or 

exam scores. 

Solution. Teachers can draw attention to students’ 

efforts when possible. When explaining exam scores or 

grades on an assignment, teachers can provide comments on effort and strategy. Teachers can routinely 

comment on the combined efforts of a class as students 

are working on assignments or projects.46 Feedback 

specific to individual students is best delivered in a 

one-on-one context.47 Teachers can also design assignments that reward effort. For example, students can be 

encouraged to submit drafts on which feedback can be 

given and then revised versions submitted for a grade.

Roadblock 2.2. Teachers whose schedules are already 

stretched may find it difficult in the course of the average school day to give each student detailed feedback 

on problem-solving and strategy use.

Solution. Feedback or praise does not need to be 

given all the time.48 In fact, informative feedback, 

and particularly praise focused on effort, should be 

given only when it is genuine. Giving students praise 

on simple tasks may undermine motivation. When 

praise is warranted, teachers can focus on effort, 

using phrases such as, “you worked really hard.” 

Teachers can be strategic in when and how they 

provide detailed informative feedback. For example, 

it often is appropriate to give such feedback to an entire 

class after a test or exam, especially when most students 

make a specific error. A class review after an assignment 

or test also is a good way to provide all students with 

informative feedback.

Roadblock 2.3. Many teachers rely heavily on standardized assessment techniques, which provide little 

feedback and can foster a performance rather than a 

learning orientation regarding scores. 

Solution. Effective math and science programs provide 

continual, multiple assessments of student knowledge 

so that appropriate adjustments can be made throughout the year. Lessons should include formative and 

summative assessments of student progress, providing 

feedback to students long before the annual standardized assessments are taken. Teachers can also use 

peer feedback and critique as a classroom activity—

providing clear criteria for feedback and critique to 

students at the outset.

46 Turner, Midgley, Meyer, et al. (2002).

47 Ward (1976).

48 Henderlong and Lepper (2002) provide a recent discussion of the research on praise.
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Encouraging Girls in Math and Science

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Recommendation 3: Expose girls to female role models who have 

succeeded in math and science.

We recommend that teachers expose girls to female role models 

who have succeeded in math and science. Research demonstrates 

that triggering negative gender stereotypes can create problems for 

girls and women on tests of mathematics and spatial reasoning.49

Exposure to female role models who have succeeded in math has 

been shown to improve performance on math tests and to invalidate 

these stereotypes.50

Level of evidence: Low

We rated the level of evidence that supports this 

recommendation as low. This recommendation is 

based on our extrapolation of relevant research, 

including four small experimental studies with college 

students.51 Although the experiments that support the 

recommendation have strong research designs (internal 

validity) for supporting causal claims, these studies 

were conducted with college students rather than girls 

from kindergarten through high school and were short 

laboratory experiments, rather than real-world classroom studies conducted with students over extended 

periods of time. Thus, the applicability of these studies 

to the effects of exposing girls to female role models in 

natural contexts (e.g., classrooms) is limited.

In addition to these studies that explicitly address 

the effect of exposure to female role models on 

young women’s math performance and beliefs about 

their math abilities, there is related research that 

supports this recommendation. This research includes 

experimental evidence that negative stereotypes can 

impede performance 52 and one small, cross-sectional 

observational study showing that children are aware of 

math-related gender stereotypes.53 

Brief summary of evidence to support 

the recommendation

Researchers have found that negative stereotypes 

can affect performance in test-taking situations 54 

and have labeled this phenomenon “stereotype threat.” 

Stereotype threat arises from a psychologically threatening concern about confirming a negative stereotype, 

both in one’s own eyes and in the eyes of others. For 

both self and others, the existence of the stereotype 

fosters negative beliefs about the meaning of difficulty 

or low performance—namely, that one lacks ability. 

Thus, when a woman is told that her math abilities 

are being evaluated, she is likely to perform worse 

on a standardized math test than a man with similar 

course grades and performance on assignments, because 

of the anxiety, deficits in short-term memory, and 

negative thoughts that have been shown to accompany 

stereotype threat. Studies also show that stereotype 

threat can lead young adolescent girls and women to 

choose unchallenging problems to solve,55 lower their 

performance expectations,56 and devalue mathematics 

as a career choice.57 Thus, negative stereotypes can 

impair engagement and confident performance of 

girls and women in science, technology, engineering, 

and mathematics. 

49 Aronson (2002); Aronson and Steele (2005); Steele, Spencer, and Aronson (2002). 

50 Marx and Roman (2002); McIntyre, Paulson, and Lord (2003).

51 Ibid. 

52 For reviews of the research, see Aronson and Steele (2005); Steele, Spencer, and Aronson (2002). 

53 Steele (2003).

54 Several experimental studies have been conducted with college students that demonstrate the stereotype threat phenomenon. For example, 

see Gonzales, Blanton, and Williams (2002); Spencer, Steele, and Quinn (1999); Steele and Aronson (1995).

55 Aronson and Good (2002).

56 Stangor, Carr, and Kiang (1998).

57 Davies, Spencer, Quinn, et al. (2002).
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Research also indicates that when some women take 

tests, a certain amount of stereotype threat is generally 

operative—that is, stereotype threat is the default 

unless measures are taken to counter it in the testing 

situation.58 It is also the case that circumstances can be 

more or less threatening depending on the number of 

stereotype cues in the environment. For example, when 

men outnumber women in the room when taking a 

test, women perform worse than when they outnumber 

men, and women seem to perform better still when no 

men are present.59

Evidence from four random-assignment experiments 

indicate that exposing women to female role models 

who are high-achieving or who are perceived as math 

experts can mitigate the effects of stereotype threat 

on math test performance. 60 These studies show that 

even brief exposure to women who are perceived to be 

experts in math can improve female students’ performance on math tests. 

Although we did not identify experimental studies testing the effect of exposure to successful role models on 

the math or science performance of girls, experimental 

studies demonstrate that calling attention to gender 

decreased performance on math tests in 12-year-old 

girls but not in younger girls (10- and 11-year-olds).61

In addition, researchers have found that by age 10 or 

so, simply being evaluated is enough to evoke stereotype threat with respect to academically stigmatized 

ethnic minority students.62 These studies demonstrate 

that stereotype threat can be a problem by the time 

girls reach middle school.

Because the research on the effects of stereotype 

threat and exposure to positive female role models 

has primarily been documented with adult women, 

we considered related research on awareness of gender 

stereotypes by girls in general. Evidence from one 

small, cross-sectional observational study suggests that 

elementary-school-aged girls are aware of the stereotype 

that men are considered to be better at math than 

women, but that they view girls and boys to be equally 

good at math. 63 

58 E.g., Inzlicht and Ben-Zeev (2000); Inzlicht, Aronson, Good, et al. (2006).

59 Ibid.

60 Marx and Roman (2002); McIntyre, Paulson, and Lord (2003).

61 Good and Aronson (2007).

62 McKown and Weinstein (2003). 

63 Steele (2003).

Table 3. Percent of degrees awarded to women in engineering subfields in 1966, 1985, and 2004

Bachelor’s Master’s Doctorate

1966 1985 2004 1966 1985 2004 1966 1985 2004

Aeronautical Engineering .3 8.4 17.8 .8 5.1 17.1 0 4.0 11.9

Chemical Engineering .8 23.4 35.4 .7 15.7 27.7 .5 8.1 23.9

Civil Engineering .4 13.8 24.2 .4 11.7 27.2 0 5.1 19.6

Electrical Engineering .3 11.5 14.2 .6 8.8 19.6 .4 4.9 13.5

Industrial Engineering .4 29.1 33.2 .5 15.5 21.3 0 6.5 19.4

Mechanical Engineering .2 10.5 13.6 .3 7.0 12.4 .2 5.1 11.1

Materials & Metallurgical 

Engineering .9 22.4 31.2 .8 15.8 24.9 .9 10.6 17.7

Other Engineering Subfields .8 16.0 29.9 .8 11.5 24.7 .4 6.3 24.9

SOURCE: National Science Foundation. Division of Science Resources Statistics. 2006. Science and Engineering 

Degrees: 1966-2004. 
Encouraging Girls in Math and Science

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Although the negative stereotype that women cannot 

perform as well as men in math and science exists and 

can affect students’ performance, the stereotype is not 

necessarily accurate. As we indicated in the overview, 

women earn a substantial proportion of the bachelor’s 

and master’s degrees in math and in many science 

disciplines (see figure 2). Even in engineering, the proportions of degrees that women now earn have substantially changed over the last 40 years.64 Table 3 shows the 

percent of degrees awarded to women by engineering 

subfields in 1966, 1985, and 2004. In 1966, women 

earned less than 1 percent of the bachelor’s degrees 

in any engineering subfield. By 2004, women earned 

about one-third of the bachelor’s degrees in chemical 

engineering (35 percent), industrial engineering (33 

percent), and materials and metallurgical engineering 

(31 percent). Exposing girls to female role models may 

help negate the stereotype and encourage more girls to 

pursue math- and science-related careers. 

How to carry out the recommendation

To counteract the negative stereotypes regarding 

women’s math and science abilities, teachers should 

provide exposure to female role models who are experts 

in math and science fields. Experimental studies with 

college women indicate that learning about women 

who have achieved success in math or science can help 

attenuate the effects of negative stereotypes.65 Teachers 

can expose students to female role models in a number 

of ways:

•	Assign biographical readings about women

scientists, mathematicians, and engineers.

•	Call attention to current events highlighting the

achievements of women in math or science.

•	When talking about potential careers, make

students aware of the numbers of women who 

receive advanced degrees in math- and sciencerelated disciplines. The National Science Foundation publishes statistics on women in the sciences, 

math, and engineering each year. This information 

is available on its website (www.nsf.gov/statistics). 

In addition, we suggest that teachers invite women or 

older students who can serve as role models in math or 

science to be guest speakers or tutors. Learning about 

role models who have achieved in math or science, 

whether through biographies or personal conversations:

•	Teaches students that struggle and eventual

success are normal. This knowledge seems to 

reduce anxiety and boost motivation when 

the student encounters challenges in work 

related to science, technology, engineering, or 

mathematics. A role model who communicates 

this may serve as a greater inspiration to 

persist through difficulty than someone for 

whom achievement appears effortless.66

•	Conveys to students that becoming good at

math or science takes hard work and that 

self-doubts are a normal part of the process of 

becoming expert at anything worthwhile.67

At least some female role models should be “attainable.” 

Research supports the idea that older students who 

overcame initial difficulty with hard work eventually to 

become high performers can be effective role models.68

A famously gifted female engineer for whom math and 

science always came easily and naturally is not always 

the best role model because she can be written off as 

an the exception—a rare case who triumphed through 

talent rather than hard work. 

In addition, many mentoring programs have been 

created for young women in an attempt to provide 

them with role models and foster their interest in 

mathematics and science.69 Mentoring is a broad 

term used to describe formal and informal programs 

in which mentors, who are people with expertise in a 

field, help people develop and accomplish their educational and career goals. Little rigorous research exists 

assessing mentors’ effectiveness in math and science 

per se, but mentoring programs may provide many 

high-school-age girls with exposure to and connections 

with a woman who has succeeded in math and science. 

However, some promising research illustrates the effects 

of mentoring programs in increasing the numbers 

64 National Science Foundation (2006b). 

65 Marx and Roman (2002); McIntyre, Paulson, and Lord (2003).

66 Ibid.

67 Ibid.; Wilson and Linville (1985). 

68 Good, Aronson, and Inzlicht (2003).

69 Building Engineering and Science Talent (2004). 
Practice Guide

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of minority students pursuing advanced degrees in 

science, technology, mathematics, and engineering.70

In addition, rigorous experimental research has shown 

that mentors can positively affect young adolescents’ 

behaviors (e.g., school attendance, drug and alcohol 

use).71 Teachers may choose to support a young girl’s 

interest in math or science by helping her to find a 

suitable mentoring program. 

Potential roadblocks and solutions

Roadblock 3.1. School hours alone may not provide 

enough opportunities for girls to be exposed to female 

role models, particularly if many of the science and 

math teachers in a given school are male.

Solution. Teachers need to encourage parents to take 

an active role in providing opportunities for girls to be 

exposed to women working in the fields of math and 

science. Teachers might encourage parents to sign up 

girls for activities where women work in math- and 

science-related careers, such as at an aquarium, a 

hospital, or a scientific laboratory. In addition, several 

national organizations provide conferences designed 

to encourage girls’ participation in math and science 

careers. 

Roadblock 3.2. Many girls see math- and sciencerelated careers as male oriented. If girls believe that 

careers in mathematics and science are nontraditional 

choices for women, they may be less likely to take 

advanced courses in math and science in high school 

or to choose a college path that leads to careers in math 

and science. 

Solution. It is certainly true that the stereotype of the 

high achieving woman in math is a nontraditional one, 

and media images do not help this.72 To counteract this 

stereotype, teachers can call attention to the fact that 

many women today are becoming mathematicians and 

scientists. The National Science Foundation publishes 

current statistics on the numbers of women and men 

receiving bachelor’s, master’s, and doctoral degrees in 

math and science.73

70 Maton and Hrabowski (2004); Summers and Hrabowski (2006).

71 Tierney and Grossman (2000).

72 E.g., Davies, Spencer, Quinn, et al. (2002).

73 See National Science Foundation at http://www.nsf.gov/statistics/wmpd/ for current statistics on the numbers of women and men receiving 

degrees in math and science.
Encouraging Girls in Math and Science

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Recommendation 4: Create a classroom environment that sparks 

initial curiosity and fosters long-term interest in math and science.

To encourage more girls to choose careers in the fields of science, 

technology, engineering, and math, we recommend that teachers use 

strategies designed to generate initial interest in specific math and 

science activities and build on this initial interest to foster sustained 

interest in math and science content. Few teachers would be surprised 

by research indicating that students’ interest is linked to academic 

performance and choices for both girls and boys. When students are 

interested in mathematics and science, they tend to get better grades 

in mathematics and science, take more advanced mathematics and 

science courses, and are more likely to pursue mathematics- and 

science-related college majors.74

Level of evidence: Moderate

A number of studies have shown that students’ interest 

predicts both concurrent and long-term performance 

in and choice of math and science courses, majors, and 

careers.75 In addition, several small-scale experimental 

studies have examined the effect of specific strategies 

(e.g., using practical problems as a context for learning math or science skills) on students’ interest and 

learning. The panel judges the quality of the evidence 

supporting this recommendation to be moderate, based 

on five small-scale experiments that focus specifically 

on children learning in math and science contexts 76 

as well as supporting experimental studies on interest 

in other domains or with adult populations and 

correlational studies of students’ interest and coursetaking or career choices.77

Brief summary of evidence to support 

the recommendation

Researchers have found gender differences in students’ 

interests, with boys typically more interested in 

activities and careers involving scientific, technical, 

and mechanical pursuits and girls more interested in 

activities and careers that involve social and artistic 

pursuits.78 These differences in interests are apparent 

by middle school and are reflected in undergraduate 

degree and career choices. Even highly mathematically 

able youth who were identified in adolescence and 

followed longitudinally showed gender effects in their 

choice of degrees. The ratio of male to female undergraduate degrees in math and science is 2.4:1.79

To make math and science content more interesting 

to students, it is helpful to think about what “interest” 

means. In research on learning, the word interest is used 

in two different ways. The first, which might be called 

long-term or individual interest, is a relatively stable and 

personal preference toward certain types of activities. A 

second kind of interest, which might be called curiosity

or situational interest, is a more immediate response 

to particular aspects of situations or problems.80 It is 

true, as noted above, that gender differences have been 

found in students’ long-term interests. But many expert 

teachers realize that an important way to cultivate 

students’ long-term interests in math and science is to 

build upon their initial curiosity. Research (as well as 

intuition) suggests that curiosity can serve as a hook to 

engage students in math and science content.81 Once 

74 Simpkins, Davis-Kean, and Eccles (2006); Updegraff and Eccles (1996). 

75 Ibid.

76 Cordova and Lepper (1996); Parker and Lepper (1992); Ginsburg-Block and Fantuzzo (1998); Turner and Lapan (2005); Phelps and 

Damon (1989).

77 For a recent review of this literature, see Hidi and Renninger (2006).

78 Lapan, Adams, Turner, et al. (2000).

79 Webb, Lubinski, and Benbow (2002). 

80 Mitchell (1993); Hidi and Renninger (2006).

81 Hidi and Renninger (2006). 
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students’ interest in a topic or content area is sparked, 

teachers can then build on that curiosity, providing 

students with opportunities to engage with interesting 

material and potentially transforming that initial 

curiosity into long-term interest. 

How to carry out the recommendation

Teachers can take several actions to create a classroom 

environment that sparks initial interest and may foster 

long-term interest.82 To spark initial interest, teachers 

can provide students the opportunity to see how the 

skills and knowledge they are learning in mathematics 

and science classes can be used to solve interesting and 

meaningful problems. For example, teachers can:

• Embed mathematics word problems and science

activities in interesting contexts.83 For elementary 

school children, embedding mathematical practice 

in fantasy contexts (e.g., saving a planet from an 

alien invasion, searching for buried treasure or 

criminals) has been found to be highly motivating 

and interesting and has led to improved performance.84 For middle school children, embedding 

mathematical practice in the contexts of realworld problems (e.g., figuring out how to build an 

effective skateboard ramp given a limited budget 

or a hovercraft that “flies” multiple students) 

can be both motivating and support learning.85

• Provide students with access to rich, engaging,

relevant informational and narrative texts as they 

participate in classroom science investigations. 

For example, during weeklong series of science 

investigation activities where elementary school 

children learn about owls and birds and have the 

opportunity to dissect owl pellets and discuss 

what they find, the children are also asked to read 

from both informational and narrative texts that 

focus on owls. Embedding the reading activities 

into the context of science investigation serves to 

generate situational interest and further curiosity.86 

• Use project-based learning, group work, innovative tasks, and technology to stir interest 

in a topic. Using web-based presentations of 

content and animated presentations of changes 

that occur during chemical bonding supports 

student exploration of key chemical concepts 

and is associated with improved learning. Other 

research shows that when students are asked 

to solve the series of problems presented in a 

video-based adventure as members of teams, 

they outperform their counterparts who are 

asked to solve the problems individually. 87 

• Examine the large variety of tools designed for

teachers to use with girls and young women to 

spark initial curiosity about science and mathematics content. Many of these tools incorporate the 

principles that have been discussed in this practice 

guide. A listing of these tools is published in a 

volume entitled New tools for America’s workforce: 

girls in science and engineering and can be downloaded at http://www.nsf.gov/publications/. 88 

Teachers can capitalize on that initial situational 

curiosity by providing students with opportunities to 

deepen their knowledge and understanding of particular math and science content and to broaden their 

understanding of how what they are learning today 

connects to their future goals. Teachers should also 

consider providing students with access to female role 

models who have been successful in mathematics and 

science careers to nurture long-term individual interest 

(see Recommendation 3).

• Encourage middle and high school students to

examine their beliefs about which careers are 

typically female-oriented and which are typically 

male-oriented. Encourage these students to learn 

more about careers that are interesting to them 

but that they believe employ more members of the 

opposite gender. Connect mathematics and science activities to careers in ways that do not reinforce existing gender stereotypes of these careers.89 

82 Mitchell (1993); Hidi and Renninger (2006). 

83 Renninger, Ewen, and Lasher (2002).

84 Cordova and Lepper (1996); Parker and Lepper (1992). 

85 Bottge, Rueda, Serlin, et al. (2007).

86 Guthrie, Wigfield, Humenick, et al. (2006).

87 Barron (2000); Linn, Lee, Tinker, et al. (2006); Phelps and Damon (1989); Kaelin, Huebner, Nicolich, et al. (2007).

88 National Science Foundation (2006a).

89 Turner and Lapan (2005); Ji, Lapan, and Tate (2004); Lapan, Adams, Turner, et al. (2000).
Encouraging Girls in Math and Science

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Potential roadblocks and solutions

Roadblock 4.1. Teachers may be reluctant to incorporate aspects of youth culture into a lesson because they 

lack familiarity with students’ interests. Teachers may 

be concerned that they might look silly by connecting 

to something long out-of-date in students’ minds.

Solution. Certainly it is a challenge to follow cultural 

trends and fads in students’ interests; it is likely that 

students do not expect their teachers to be able to 

keep up and may even be surprised when one is able 

to do so. However, connecting to trends in popular 

culture is only one potential strategy for arousing 

students’ curiosity. Teachers can also seek to connect 

math and science content with other contexts that 

are of interest to students of all ages and generations, 

including history and current events. In addition, 

incorporating hands-on activities, group work, and 

technology into lessons can make the content more 

interesting for students.

Roadblock 4.2. Teachers may be reluctant to incorporate interesting activities, because of the belief that 

some activities might distract students and not serve 

the goals of the lesson. 

Solution. Teachers should not interpret this recommendation as suggesting that all activities in math and 

science classes should take the form of games or fun 

activities. While games can be fun and exciting for 

students, it is also true that some games and activities 

that are not tightly linked to learning objectives may 

indeed distract students and be counterproductive to 

learning. Teachers should strive to achieve a balance 

between enhancing activities so that they incorporate 

some material that sparks interest while ensuring that 

content learning remains the primary goal of the lesson. 

Roadblock 4.3. Teachers may be hesitant to use 

time-intensive methods such as hands-on activities and 

group work, given the pressure that many feel to keep 

up with curriculum pacing guides.

Solution. It is true that creating interesting and 

innovative tasks is time-consuming on many levels— 

increased preparation time for teachers, more time 

needed to cover the material in class, and frequently 

more time for teachers to grade or evaluate students’ 

work. Teachers need to achieve a balance between 

incorporating interesting tasks and lesson formats 

and covering the required curriculum. But, despite 

increased time demands, using interesting tasks and 

instructional formats may be worth the extra effort: 

Research indicates a strong link between interest and 

academic performance, for both girls and boys. In 

addition, as a teacher and her students become more 

accustomed to doing things a bit differently (e.g., using 

group work or using project-based learning), the extra 

effort required to implement these kinds of activities 

can decrease.
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Encouraging Girls in Math and Science

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Recommendation 5: Provide spatial skills training.

We recommend that teachers provide spatial skills training for girls. 

Researchers have found that spatial skills are associated with 

performance on math tests and that spatial skills can be improved 

with practice on certain types of tasks.90

Level of evidence: Low 

We consider the level of evidence to support this 

recommendation to be low because of the lack of experimental or rigorous quasi-experimental studies that 

directly examine the effects of spatial skills training on 

girls’ math or science performance. Our recommendation to improve math and science performance through 

spatial skills training represents an extrapolation based 

on the broader relevant research literature.91

Brief summary of evidence to support 

the recommendation

When we look at girls’ math and science performance 

in school, we see that they are doing well on tests 

that are closely related to the curriculum they are 

taught in school. As noted earlier, girls, on average, 

graduate from high school with slightly more math 

and science classes than boys and with higher grades. 

Girls now obtain almost half of all undergraduate 

degrees in mathematics and the majority of degrees in 

health-related fields. But, as noted at the beginning of 

this guide, girls and women are underrepresented in 

physics, computer science, engineering, and chemistry 

at the undergraduate level, and their numbers fall off as 

they move beyond the undergraduate degree.92

We find the largest between-gender differences with 

standardized examinations that do not match any 

particular curriculum. We are referring to the standardized tests that are used for admission to undergraduate 

and graduate programs and for state and international 

comparisons. As already discussed, one possible reason 

that girls and women perform less well on these tests 

in mathematics and science is stereotype threat, but 

the differences are found on specific items on these 

tests, which suggests that there are gender differences 

in how certain types of questions are solved or not 

solved. For example, numerous researchers have found 

that when math items are highly spatial in nature, boys 

solve more of these questions correctly.93 Consider 

the conclusion from a study of 24,000 ninth-graders, 

which showed that males perform better on items 

that require significant spatial processing and females 

outperform males on items requiring memorization.94

Additional support comes from an analysis of the 

mathematical test questions that showed the largest 

gender differences favoring males on an international 

math assessment.95 The items included calculating the 

height of a mountain, calculating the distance between 

two intercepts on a plane, calculating the length of 

a string, calculating the perimeter of a polygon, and 

other similar problems that are spatial in nature. There 

is evidence that gender differences in math problemsolving strategies begin as early as first grade, with girls 

90 Doolittle (1989); Newcombe (2002); McGraw, Lubienski, and Struchens (2006).

91 Ben-Chaim, Lappan, and Houang (1988); Piburn, Reynolds, McAuliffe, et al. (2005).

92 A summary of research can be found in Halpern, Benbow, Geary, et al. (2007).

93 E.g., Bielinksi and Davison (2001); Doolittle (1989); Gallagaher, De Lisi, Holst, et al. (2000); Geary, Saults, Liu, et al. (2000); Gierl, 

Bisanz, Bisanz, et al. (2003).

94 Gierl, Bisanz, Bisanz, et al. (2003).

95 Casey, Nuttall, and Pezaris (2001).
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using more overt strategies, such as counting, and boys 

using more conceptual spatial strategies.96

A large research literature shows that boys outperform 

girls on many tests of spatial skills, especially ones that 

require visualizing what an object will look like when it 

is rotated in space.97 Researchers have established that 

spatial skill performance is correlated with performance 

in mathematics and science.98 For example, researchers 

have found that kindergarteners’ ability to perceive 

and discriminate among various shapes and geometric 

forms predicts their later performance in fourth-grade 

math.99 Scores on a spatial visualization test, for 

example, have correlated with subsequent test scores 

in geology.100 Other evidence supporting the idea that 

spatial abilities are important in math and science was 

provided by researchers who found that scores on a test 

of mental rotation, which measures how well students 

can visualize an irregular shape when it is rotated in 

space, accounted for a large proportion of the malefemale difference on standardized examinations.101

Additionally, geometry items comprise close to onethird of the questions on the math portion of the SAT, 

and the largest differences between males and females 

are found on geometry items.102 Spatial skills, therefore, 

figure importantly in the male-female test score gap.103 

In mathematics, researchers have studied the way 

that representations affect the learning of complex 

mathematical ideas. For example, in a study of the 

strategies used to solve mathematical problems, 

researchers found that overall, the male students were 

more likely than female students to use a flexible set 

of general strategies and more likely to solve problems 

correctly when the solution required a spatial representation, a short cut, or the maintenance of information 

in spatial working memory.104

Several studies have documented that women who 

undergo specific spatial skills training programs show 

improved performance in the specific domain of their 

training.105 In one study, for example, researchers 

designed and implemented a course to improve the 

spatial visualization skills of first-year engineering 

students.106 In this course, students learned effective 

strategies for mentally representing objects, and for 

using graphs, diagrams, charts, and maps as tools for 

thinking about topics in science and mathematics. 

Notably, retention in the engineering program for 

female engineering students who took the spatial 

visualization course was 77 percent, whereas retention 

was only 47 percent among those who did not take the 

course. Although both females and males participated 

in the spatial training course, more females scored 

low on tests of spatial visualization at the start of the 

program, and females showed greater gains in retention 

in the engineering program as well as in grades. Other 

researchers examined the effects of spatial training 

when using information about maps and found that 

when students were taught how to project lines of 

longitude and latitude and to visualize the curve of the 

Earth’s surface, their map skills improved.107

Several studies, including a few experiments using 

random assignment, have directly examined spatial 

skills training in school-age children. In these studies, 

children who received training in a specific spatial skill 

(e.g., mental rotation, spatial perspective, embedded 

figures) improved their performance on related visual 

and spatial measures more than children who did not 

receive this training.108 In a recent synthesis of the 

spatial skills training literature, such training was found 

to improve the visual and spatial skills of both children 

and adults.109 Thus, targeted training can serve to 

improve spatial skills performance beginning in early 

childhood and continuing into adulthood. 

96 Carr, Jessup, and Fuller (1999).

97 E.g., Battista (1990); Bielinksi and Davison (2001); Doolittle (1989); Harris and Carlton (1993); McGraw, Lubienski, and Struchens 

(2006).

98 Casey, Nuttall, and Pezaris (2001); Kurdek and Sinclair (2001); Piburn, Reynolds, McAuliffe, et al. (2005).

99 Kurdek and Sinclair (2001). 

100 Piburn, Reynolds, McAuliffe, et al. (2005). 101 Casey, Nuttall, and Pezaris (2001). 102 Harris and Carlton (1993). 103 E.g., Bielinksi and Davison (2001); McGraw, Lubienski, and Struchens (2006). 104 Gallagher, De Lisi, Holst, et al. (2000). 105 Halpern (2000). 106 Sorby (2001). 107 Muehrcke and Muehrcke (1992). 108 Connor, Schackman, and Serbin (1978); DeLisi and Wolford (2002). 109 Marulis, Liu, Warren, et al. (2007). 
Encouraging Girls in Math and Science

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To reiterate, the mathematical test items that show the 

greatest difference favoring boys are spatial in nature. 

Spatial skills can be improved with training. When 

spatial skills training was given to college students in 

engineering, grades in courses that use spatial skills 

improved and retention in engineering programs, 

especially for women students, improved. In addition, 

spatial ability predicted which courses high school 

students liked best (with math and science courses 

positively related to spatial ability) and the careers in 

which students were employed when they were in their 

30s (with spatial ability positively related to careers in 

math, science, and engineering).110

How to carry out the recommendation

Teachers can provide spatial skills training with a 

variety of age-appropriate activities. In particular, 

teachers can: 

•	Encourage young girls to play with toys that

require the application of spatial knowledge, such as building toys.111

•	Teach older girls to mentally image and draw

mathematics or other assignments so that they 

become as comfortable with spatially displayed 

information as they are with verbal information.112

•	Require answers that use both words and a

spatial display.113

•	Provide opportunities for specific training in

spatial skills, such as mental rotation of images, 

spatial perspective, and embedded figures.114

Potential roadblocks and solutions

Roadblock 5.1. Some teachers may not feel prepared 

to provide spatial skills training. 

Solution. Many materials are available to help teachers 

include spatial skills in their everyday curriculum. Free 

software and lesson plans for grades K to 12 are available on websites dedicated to the topic of spatial skills 

training. In addition, published materials are available 

offering ideas to teachers for incorporating spatial skills 

training in their everyday curriculum.115

Roadblock 5.2. Learners in any classroom will vary in 

their spatial abilities, making it difficult for teachers to 

know how to target their teaching in this domain. 

Solution. Tools and lesson plans available on the Web 

can be used by learners at different levels of ability. 

In addition to published materials, special workshops 

for teachers that vary by grade level could also help 

teachers begin to plan lessons, as well as ready-to-use 

sample exercises and online training programs. 

110 Shea, Lubinski, and Benbow (2001). 111 Deno (1995). 112 Gerson, Sorby, Wysocki, et al. (2001). 113 Casey, Nutall, and Pezaris (2001). 114 Sorby and Baartmans (2000). 115 Casey (2003). 
( 30 )
Encouraging Girls in Math and Science

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Conclusion

To conclude, let us revisit our recommendations. 

What do we recommend that teachers do to encourage girls and young women to choose career paths 

in math- and science-related fields? One major way 

is to foster girls’ development of strong beliefs about 

their abilities in these subjects—beliefs that more 

accurately reflect their abilities and more accurate 

beliefs about the participation of women in math- and 

science-related careers. Our first two recommendations, 

therefore, focus on strategies that teachers can use to 

strengthen girls’ beliefs regarding their abilities in math 

and science: (1) Teach students that academic abilities are expandable and improvable; and (2) Provide 

prescriptive, informational feedback. Our third recommendation addresses girls’ beliefs about both their 

abilities and the participation of women in math- and 

science-related careers: (3) Expose girls to female role 

models who have succeeded in math and science.

In addition to beliefs about abilities, girls are more 

likely to choose courses and careers in math and science 

if their interest in these fields is sparked and cultivated 

throughout the school years.116 Our fourth recommendation focuses on the importance of fostering both 

situational and long-term interest in math and science, 

and provides concrete strategies that teachers can use 

to do so.

In addition to beliefs and interests, a final way to 

encourage girls in math and science is to help them 

build the spatial skills that are crucial to success in 

many math- and science-related fields, such as physics, 

engineering, architecture, geometry, topology, chemistry, and biology. Research suggests that spatial skills, on 

which boys have typically outperformed girls, can be 

improved through specific types of training. Thus, our 

final recommendation is that teachers provide students, 

especially girls, with specific training in spatial skills.

116 Wigfield, Eccles, Schiefele, et al. (2006). 
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Encouraging Girls in Math and Science

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117 Blackwell, Trzesniewski, and Dweck (2007); Good, Aronson, and Inzlicht (2003). 118 Good, Aronson, and Inzlicht (2003). 119 Blackwell, Trzesniewski, and Dweck (2007). 120 Aronson, Fried, and Good (2002). 121 Good, Aronson, and Inzlicht (2003).

Appendix: 

Technical information 

on the studies

Recommendation 1:

Teach students that academic abilities are 

expandable and improvable.

Level of evidence: Moderate

The panel rated the level of evidence as Moderate. 

We were able to locate two small experiments demonstrating support for the practice of improving students’ 

performance by teaching them that academic abilities 

are expandable and improvable.117 In the first study, 

138 girls and boys in seventh grade participated in the 

study that examined the effect of teaching students 

about the expandability of their abilities on end-of-year 

math and reading achievement test scores.118 The 

second study was conducted with 95 girls and boys 

in seventh grade and examined the effect of such instruction on students’ end-of-semester math grades.119

In addition, we identified a small experiment with 

79 female and male college students that demonstrated 

support for this practice improving students’ end-ofterm grade point averages.120 All three studies included 

students from ethnically and socioeconomically diverse 

backgrounds.

These studies share the following features: Students or 

groups of students were randomly assigned to treatment and control conditions, where some were taught 

that intelligence is malleable and abilities are expandable, while others were not taught this but spent an 

equal amount of time engaged in learning something 

new. In all three studies, students in the group that was 

taught that abilities are expandable performed better 

than students in the control condition.

Example of an intervention that teaches students 

that academic abilities are expandable and 

improvable.

In our example study,121 shortly after the school year 

began, 138 seventh-graders (both boys and girls) were 

randomly assigned a mentor, with whom they communicated throughout the school year. The mentors were 

25 college students who were completing a required 

mentor-training course designed by the school district. 

The mentors’ role was to offer advice to their assigned 

students regarding study skills and the transition to 

junior high, explicitly teach one of four messages, and 

help the students design and create a web page for their 

computer skills class in which the students advocated 

the experimental message conveyed to them by the 

mentor throughout the year. 

The participating seventh-graders were randomly 

assigned to one of four conditions, representing a 

message taught by a mentor: (a) the incremental 

condition, in which students learned that intelligence 

is an expandable capacity that increases with mental 

effort; (b) the attribution condition, in which participants learned that many students experience difficulty 

when they move to a new educational level (such as 

junior high), but then improve their performance 

once they are familiar with their new environment; 

(c) a combined condition, in which students learned 

both the incremental and attribution messages; and 

(d) an antidrug control condition, in which students 

learned about the dangers of drug use. Each mentor 

had about six randomly assigned students across three 

of the four messages. 

Students’ math achievement was measured at the 

end of the school year using the Texas Assessment of 

Academic Skills, a statewide standardized achievement 

test administered to all students in the district. 

Study results indicate that the boys in the antidrug 

condition performed significantly better on the math 

test than the girls; that is, the math score mean for the 

boys was 81.55, but the mean math score for girls was 

74.00. However, in the three other conditions, the 

gender gap in math performance disappeared. The 
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math test scores of the girls in the experimental 

conditions were statistically equivalent to the scores of 

the boys across all conditions (i.e., in the incremental 

condition, the average math score for males was 85.25 

and for females was 82.11; in the attribution condition, 

the average math scores of both boys and girls was 

84.53; in the combined condition, the average math 

scores for females was 84.06 and for males was 82.30). 

Importantly, the large difference in test scores between 

boys and girls that was found in the control condition 

(i.e., antidrug message) was eliminated in the three 

experimental conditions. The experimental manipulations were particularly beneficial for the female students 

and demonstrated significant effects closing the gender 

gap in performance, indicating that the intervention 

procedures meaningfully increased girls’ math scores 

compared to the control condition. 

Recommendation 2:

Provide prescriptive, informational feedback.

Level of evidence: Moderate

The panel rated the level of evidence as Moderate. 

We were able to locate one high-quality study, 

which presented a series of six random assignment 

experiments demonstrating support for the practice 

of providing K–12 students with prescriptive, informational feedback as a way to improve student motivation 

and performance.122 Two additional classroom-based 

experimental studies provide support for providing 

prescriptive, informational feedback during mathematics instruction.123 We also drew on a recent substantive 

review of the literature that discusses the effects of 

praise on children’s intrinsic motivation.124 In addition, 

two high-quality longitudinal studies demonstrated 

the link between students’ self-efficacy beliefs and their 

math- and science-related choices.125

In one of the longitudinal studies, researchers used 

a large random sample of students in 10 different 

school districts in southeastern Michigan to test the 

utility of students’ math-related self-beliefs to explain 

variation in math course-taking.126 Students examined 

in this study (n = 1,039) were followed from 9th to 

12th grade, and were primarily from middle and 

lower middle class European American backgrounds. 

Self-concept of ability in math, utility of math, and 

interest in math were measured in the ninth grade 

using questionnaires. Grades in math, standardized 

test scores in math, specific course enrollment choices, 

and the number of math classes taken throughout high 

school were gathered from school record data. Findings 

indicated a strong and significant association between 

self-concept of math ability and performance in 

mathematics. In addition, the perceived utility of math 

had the strongest and most consistent association with 

the number of high school math courses taken, with 

boys perceiving math as having significantly greater 

utility than girls.

In the second longitudinal study, researchers analyzed 

data from a sample of 227 youths from 5th through 

12th grade to address longitudinal associations among 

students’ math- and science-related activities, their 

math and science related beliefs, and math and science 

courses taken throughout high school.127 The researchers focused on the physical sciences. Results indicated 

that youths’ participation in out-of-school math 

and science activities during fifth grade significantly 

predicted their math and science beliefs at sixth grade 

(e.g., math and science self-concepts, perceptions of 

math and science importance, and interest in math 

and science). These beliefs measured at 6th grade 

predicted beliefs at 10th grade, and the 10th-grade 

beliefs predicted the number of high school courses 

students took, even after taking into account the 

predictive power of their math and science grades in 

10th grade.

Together, these two studies suggest a strong relation 

between the math and science courses that students 

choose to take in high school and their beliefs regarding 

their abilities and interest in these subjects, as well as 

their perception of the importance of these subjects. 

Although these studies have high external validity, they 

do not answer questions regarding the direction of 

causality between students’ self-concepts in math and 

122 Mueller and Dweck (1998). 123 Elawar and Corno (1985); Miller, Brickman, and Bolen (1975). 124 Henderlong and Lepper (2002). 125 Simpkins, Davis-Keans, and Eccles (2006); Updegraff and Eccles (1996). 126 Updegraff and Eccles (1996). 127 Simpkins, Davis-Kean, and Eccles (2006).
Encouraging Girls in Math and Science

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science and their performance in these areas. The third 

study 128 presents a series of six randomized controlled 

experiments that demonstrate that performance on a 

math-related skill can be improved by manipulating 

fifth-graders’ attributions regarding success and failure, 

thus increasing their beliefs regarding the likelihood 

that they will succeed on future related tasks. 

Example of an intervention that uses prescriptive, 

informational feedback.

In a series of six experiments, the impact of ability 

versus effort feedback on fifth-graders’ subsequent 

performance on the Standard Progressive Matrices,129

designed to measure ability to form perceptual relations and to reason by analogy, was examined. The 

Standard Progressive Matrices is a nonverbal measure 

that correlates strongly with the Stanford Binet and 

Wechsler Scales of intelligence. In addition, studies of 

the Wechsler Preschool and Primary Test of Intelligence 

(Revised) show that math performance is moderately 

related to perceptual organization for every age group 

sampled. Thus, the Standard Progressive Matrices 

measures perceptual relations skills that are related to 

mathematics performance. 

The number of participating fifth-graders for each of 

the six studies was: 128, 51, 88, 51, 46, and 48. The 

ethnically and socioeconomically diverse students (both 

boys and girls) were drawn from public schools in the 

midwest and the northeast. Students were randomly 

assigned to one of three conditions: (a) ability or 

intelligence praise; (b) effort praise; and (c) a control 

condition in which students received a general statement of praise with no attributions regarding either 

ability or effort.

In this series of studies, students were asked to do 

three sets of Standard Progressive Matrices. Following 

the first set, students received either positive praise 

regarding their intelligence or ability; positive praise 

regarding their effort; or nonspecific praise that did 

not offer an attribution for success. Students then 

completed a second set of matrices, following which 

they were told that they had performed “a lot worse” 

on this set than they had on the first set. After completing items measuring dimensions such as desire to 

persist on the problems, enjoyment of the problems, 

and attributions for their failure, students were then 

given a third and easier set of matrices to complete, 

thus yielding a measure of post-failure performance. 

Findings from this series of studies indicate that 

fifth-graders who were praised for ability performed 

less well following subsequent failure, whereas students 

who were praised for effort did not. Following failure, 

students praised for effort rather than ability also 

showed greater task persistence and enjoyment and 

greater orientation toward mastery learning. Students 

in the control condition typically had scores between 

those of students in the ability-praise and effort-praise 

conditions.

In this series of studies, several alternative explanations 

were ruled out, including the possibility that: (a) praise 

for ability might have led children to have higher 

expectations for future performance, which might then 

have led to greater disappointment following failure; 

(b) having the same teacher administer both positive 

and negative feedback following task completion might 

have increased the desire of ability-praised children 

to perform well on the second set of matrices; and (c) 

ability-praised children might have interpreted the task 

as an intelligence test, thus leading to greater disappointment following failure. With these competing 

explanations ruled out through experimental manipulation, the authors conclude that ability-focused praise 

led the fifth-graders to view performance as an index of 

ability, resulting in decreased motivation and performance following failure. Students who were praised for 

effort rather than ability did not show these post-failure 

deficits in motivation and performance.

Recommendation 3:

Promote positive beliefs regarding women’s 

abilities by exposing girls to female role 

models who have succeeded in math 

and science.

Level of evidence: Low

The panel rated the level of evidence that supports 

this recommendation as Low, based on four small 

experimental studies with college students. Although 

the experiments that support the recommendation have 

strong internal validity for supporting causal claims, 

128 Mueller and Dweck (1998). 129 Ibid.
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these studies were conducted with college students 

rather than girls in kindergarten through high school 

and were short laboratory experiments, rather than 

real-world classroom studies conducted with students 

over extended periods of time. Thus, the generalizability of these studies to the effects of exposing girls 

to female role models over, for example, the course 

of a school year is limited.

In addition to these studies that explicitly address 

the effect of female role models on young women’s 

math performance and beliefs about their math 

abilities, there is evidence that exposure to positive 

role models or mentors can have a positive effect 

on students’ behaviors.130

In a set of three small experimental studies with 

college students, researchers demonstrated that the 

presence of female role models who are competent 

in math mitigated the negative impact of gender 

stereotypes on the math performance of female 

college students.131 These studies provide evidence 

that exposure to competent female role models can 

close the female-male math gap in testing and improve 

young women’s beliefs about their math abilities. 

However, these studies do not examine the efficacy 

of female role models with girls from kindergarten 

through high school. 

In another small, random-assignment experiment 

with college women, a team of researchers found 

significantly improved performance on a test of items 

similar to those used for the GRE math test when the 

students first read about women’s accomplishments in 

architecture, law, medicine, and invention.132

These four studies provide evidence of the positive 

effect of female role models on the test performance 

of young college women and on their beliefs about 

their math abilities. Some evidence suggests that 

exposure to positive role models or mentors can have 

a positive effect on students’ behaviors. For example, a 

large-scale evaluation of Big Brothers/Big Sisters found 

positive effects of mentoring on young adolescents’ 

school attendance and drug and alcohol use.133 

We cite these studies as providing evidence that the 

strategy (i.e., exposing girls to positive role models) in 

general has been shown to be effective for elementary to 

secondary school students in some outcome domains, 

although not specifically for improving outcomes in 

math or science.

Example of intervention using competent female 

role models with college students.

In our example study, a research team conducted 

a series of three random-assignment experiments 

examining the impact of competent female role models 

on the performance of college women in a setting that 

was represented to participants as a diagnostic testing 

situation for math.134 The participants in each of these 

experiments were students who considered themselves 

to be good in math and to be motivated to do well 

on math exams. In experiment 1, 43 undergraduate 

women and men were randomly assigned to undergo 

the math testing situation with either a female or a 

male experimenter, both of whom were presented to 

the participants as being competent in math. Women 

performed as well as their male counterparts when the 

experimenter was a woman; women did not do as well 

on the math test when the experimenter was a man. 

In experiments 2 and 3, participants were provided 

with the biographical sketch of a fictitious female 

experimenter who was not actually present; in the 

biographical sketches, the female experimenter’s level of 

math competence was manipulated to be either high or 

low. The results of both experiments demonstrated that 

the improved performance on the math exam obtained 

in experiment 1 was dependent on the undergraduate 

women perceiving the female role model to be very 

compentent in math, as opposed to simply taking the 

test with a female experimenter with average math 

skills. In addition, in experiment 3, the researchers 

found that young women’s perceptions of their math 

ability were higher when they were exposed to a female 

role model who was competent in math. 

These studies provide evidence that a brief exposure 

to a compentent female role model can affect college 

women’s performance on tests and their perceptions of 

their math abilities. An important limitation of these 

130 E.g., Tierney and Grossman (2000). 131 Marx and Roman (2002). 132 McIntyre, Paulson, and Lord (2003). 133 Tierney and Grossman (2000). 134 Marx and Roman (2002).
Encouraging Girls in Math and Science

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studies for our purposes is that the participants were 

students who self-identified as being good in math and 

being motivated to do well on math tests.

Recommendation 4: 

Create a classroom environment that sparks 

initial curiosity and fosters long-term interest 

in math and science.

Level of evidence: Moderate

The panel rated the level of evidence as Moderate. There 

is a long and rich tradition of exploring ways 

to increase student interest in mathematics and science 

content in education research. In determining the level 

of evidence supporting this recommendation, we drew 

on several experimental and quasi-experimental studies. 

For example, we found two small-scale, randomized 

controlled trials that demonstrate support for the 

practice of providing elementary school students with 

an environment that improves learning in the areas 

of mathematics and computer science by fostering 

greater interest.135 Others have experimentally evaluated 

the facilitative effect of peer collaboration on solving 

mathematics problems;136 while yet another study 137

examined how participating in a career exploration 

module fostered middle school girls’ interest in 

nontraditional careers (e.g., those in the areas of 

mathematics and science). Two additional quasi-experimental studies provide support for the benefits of this 

practice on students’ motivation and comprehension 

of science texts.138 

One study examined the impact of three interestenhancing strategies on the motivation and performance of 70 fourth- and fifth-grade students in a 

related math task.139 Another examined the influence 

of embedding a computer programming task in a 

fantasy context with 27 children.140 In another program 

of research, two studies involving a total of 885 thirdgrade students investigated reading comprehension 

of science texts.141 Finally, another set of studies 

examined 133 third-grade and 106 fifth-grade students 

from two low-income schools with predominantly 

African-American populations.142

Across these studies, students in the high-interest 

conditions outperformed students in control conditions on study-specific indices of interest, motivation, 

and learning. The learning activities in each of these 

interventions share some or all of the following 

features: They were designed around contexts that 

students found engaging, made available a range of 

texts, used real-life settings, used technology, provided 

students’ with choice, and used group work.

Example of intervention that improves math 

performance through increasing interest.

In this study, mathematics instruction was embedded 

in fantasy or nonfantasy computer games in order to 

study the impact of intrinsic interest on math performance.143 Seventy students (both boys and girls) were 

randomly assigned to play computer games designed 

to teach specific math skills (the hierarchy of the order 

of operations and the proper use of parentheses in 

arithmetic expressions) in one of five conditions: (a) in 

a basic, unembellished version that served as a control 

condition, students played a math game on the computer in which they were required to learn and correctly 

use the target skills in order to win the game; (b) in two 

generic fantasy conditions, the activity was presented 

within fantasy contexts (spacetrip and treasure island) 

designed to increase children’s intrinsic interest in 

the game; in the first generic fantasy condition, the 

students had some choice regarding at least six details 

that were incidental to the game itself (e.g., type and 

color of spaceship to use), whereas (c) in the second 

generic fantasy condition, these details were provided 

randomly by the computer; (d) in two personalized 

fantasy conditions, several generic referents in the 

program were replaced with details that were personally 

relevant to the child (e.g., child’s name, favorite foods 

to bring along on the spacetrip), obtained from a 

135 Cordova and Lepper (1996); Parker and Lepper (1992). 136 Ginsburg-Block and Fantuzzo (1998); Phelps and Damon (1989). 137 Turner and Lapan (2005). 138 Guthrie, Wigfield, Barbosa, et al. (2004); Guthrie, Anderson, Alao, et al. (1999). 139 Cordova and Lepper (1996). 140 Parker and Lepper (1992). 141 Guthrie, Wigfield, Barbosa, et al. (2004). 142 Guthrie, Anderson, Alao, et al. (1999). 143 Cordova and Lepper (1996).
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pretest questionnaire; in the first personalized fantasy 

condition, the students had some choice regarding at 

least six details incidental to the game itself, whereas 

(e) in the second personalized fantasy condition, 

the students did not have a choice. Thus, the five 

conditions were: no-fantasy control condition; generic 

fantasy, no choice; generic fantasy, choice; personalized 

fantasy, no choice; personalized fantasy, choice. 

The intervention consisted of five sessions. In the first 

session, participating students were pretested on their 

knowledge of the target math skills, and also completed 

several measures of their global motivational orientation. In the next three sessions, each child played with 

one randomly assigned version of the computer games. 

These sessions were scheduled about five days apart 

and lasted about 30 minutes each. In the fifth session, 

students completed posttests on the target math skills, 

as well as several additional attitudinal measures. 

Dependent measures included self-reports of interest 

and enjoyment, behavioral commitments to continued 

task engagement, preferences for increasingly challenging tasks, and direct measures of students’ online 

involvement in the activities.

The results of the intervention indicate that students 

exposed to each of the three specific strategies designed 

to heighten student interest (contextualization, choice, 

and personalization) showed significantly greater motivation, involvement, and learning of the target math 

skills than those students in the control condition. 

Recommendation 5: 

Provide spatial skills training.

Level of evidence: Low

The panel rated the level of evidence as Low. That is, 

the evidence for the recommendation is based on the 

expert opinion of panel members, justified by highquality research in related domains. 

The panel located two high-quality studies of spatial 

skills training focused on skills that are generally 

considered important in math and science achievement. One study was a small-scale, random-assignment 

experiment with college students144; the other was a 

quasi-experiment with elementary or middle school 

students.145 Both studies focused on the improvement 

of specific spatial skills. Although there is agreement 

among experts that the relevant skills are important to 

specific aspects of math and science performance, the 

transfer of these skills more generally to achievement in 

math and science courses has not been directly demonstrated. The evidence supporting the practice of spatial 

skills training as a way to improve performance in math 

and science courses in K–12 is thus indirect. 

In the first study, 103 college students taking an 

introductory geology course were in one of four 

sections randomly assigned to either an experimental 

or a control condition.146 Both experimental and 

control sections used the same laboratory manual; 

however, the two experimental sections used additional 

computer-based modules that allowed extensive student 

involvement with images that could be manipulated. 

Students were administered a content assessment and 

two spatial-visual measures as pretests and posttests. 

Study results indicate that students in the experimental 

sections improved their spatial visualization skills 

significantly more than did students in the control 

sections and that pre-existing gender differences with 

regard to spatial visualization were eliminated in the 

experimental sections. That is, final posttest scores of 

males and females on the spatial visualization tasks were 

not different from one another.

In the second study, researchers examined the impact 

of spatial visualization skills training on about 1,000 

fifth- through eighth-grade students.147 Before instruction, there were significant differences by sex in spatial 

visualization performance (favoring boys). After the 

intervention, middle school students, regardless of sex, 

gained significantly from the training program. Retention of the impact persisted after a 4-week period and 

after 1 year. The persistent gender differences found 

in performance after training in this younger sample 

are important to note. This research suggests that the 

spatial skills of both boys and girls are susceptible to 

144 Piburn, Reynolds, McAuliffe, et al. (2005). 145 Ben-Chaim, Lappan, and Houang (1988). 146 Piburn, Reynolds, McAuliffe, et al. (2005). 147 Ben-Chaim, Lappan, and Houang (1988).
Encouraging Girls in Math and Science

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training; however, it leaves open the question of how 

to close the gender gap in spatial skills performance.

Example of intervention that improves 

spatial skills.

The quasi-experiment supports the practice of using 

spatial skills training to improve specific skills that 

experts consider to bear a relationship to performance 

in mathematics, science, and engineering.148 Spatial 

visualization is a subset of spatial skills that involves the 

ability to mentally manipulate and rotate objects. In 

this study, about 1,000 fifth- to eighth-grade students 

at three sites in and around a large midwestern city 

participated in a 3-week spatial visualization unit that 

engaged them in concrete activities with small cubes, 

such as building and drawing representations. The 

spatial visualization test was used as a pretest and posttest measure. After the instruction intervention, middle 

school students, regardless of sex, gained significantly 

from the training program in spatial visualization 

tasks. Boys and girls responded similarly to the training 

program, indicating that spatial visualization skills can 

be improved when appropriate training is provided. 

The retention of the training effects 4 weeks and 1 year 

later underscores the potential long-term benefits of 

spatial skills training.

148 Ibid. 
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