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ABSTRACT: In a "Science" article titled "Gender Similarities
Characterize Math Performance," Hyde et al. (2008)] reported their
analysis of scores for over 7 million students in state NCLB math
assessments, thereby stimulating four news reports. Two of them
[Lewin (2008) and Seattle Times (2008] focus on the near equality of
the *averages* for males and females and carry headings to the effect
that girls and boys perform equally well in math. One of them [Mac
Donald (2008)] focuses on the larger *variance* of male over female
scores, carries a heading with the opposite message "Math IS Harder
for Girls," and contains several misleading statements. A fourth
[Winstein (2008)] reports both the average and variance aspects of
the Hyde et al. report and carries a more neutral heading "Boys' Math
Scores Hit Highs and Lows." To dig deeper see the annotated
references given in Part 2 of Hake & Mallow (2008): 50 references to
"Sex Differences in Mathematical Ability: Fact or Artifact?" and 12
references to "Harvard President Summers' Speculation on Innate
Gender Differences in Science and Math."
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Among news reports stimulated by a recent "Science" article "Gender
Similarities Characterize Math Performance [Hyde et al. (2008)] are:
(a) "Math Scores Show No Gap for Girls, Study Finds" [Lewin (2008)],
(b "In math, girls and boys are equal" [Seattle Times News Service (2008)],
(c) "Math IS Harder for Girls" [Mac Donald (2008)],
(d) "Boys' Math Scores Hit Highs and Lows" [Winstein (2008)].
Why do the headings of reports "a" and "b" appear to be diametrically
opposite that in report "c' by Mac Donald?
The reason is that reports "a" and "b" focus on the Hyde et al.
statement that ". . . .[Cohen (1988) effect sizes "d"] . . . . for
gender differences, representing the testing of over 7 million
students in state assessments, are uniformly <0.10, representing
trivial differences."
On the other hand report "c" by Mac Donald emphasizes the Hyde et al.
statements:
A. "All . . .[male to female variance ratios]. . . . by state and
grade, are >1.0 [range 1.11 to 1.2]. Thus, our analyses show greater
male variability," and
B. "The bottom table on p. 494 shows data for grade 11 for the state
of Minnesota. For whites, the ratios of boys:girls scoring above the
95th percentile and 99th percentile are 1.45 and 2.06, respectively."
But Mac Donald deceptively generalizes "B" to "Among white
11th-graders, there were twice as many boys as girls above the 99th
percentile-that is, at the very top of the curve."
Among the caveats of Hyde et al. (2008) are:
(1) "the discrepancy in variances is not large,"
(2) "gender differences in math performance, even among high scorers
. . . .[found in this study]. . ., are insufficient to explain
lopsided gender patterns in participation in some STEM fields,"
(3) "an unexpected finding was that state assessments designed to
meet NCLB requirements fail to test complex problem-solving of the
kind needed for success in STEM careers, a lacuna that should be
fixed."
Mac Donald correctly points out that "3" diminishes the significance
of "2," but comments incorrectly on "3," stating:
"That a gender difference at the highest percentiles shows up on
tests pitched to such an elementary level of knowledge and skill
suggests that on truly challenging tests, the gender difference at
the top end of the distribution will be even greater. Indeed, between
five and ten times as many boys as girls have been found to receive
near-perfect scores on the math SATs among mathematically gifted
adolescents, for example."
Mac Donald is evidently referring to the widely cited work of Benbow
and her colleagues [see e.g. Benbow (1988)], but Rich Monastersky
(2005) pointed out that:
"Data from [Julian Stanley's] program, at Johns Hopkins, shows just
how strong the cultural factors are in determining math achievement.
In the early 1980s, he and [Camilla Benbow] reported. . . [Benbow &
Stanley (1980)]. . . . a whopping disparity in the numbers of
mathematically gifted boys and girls who scored 700 on the math
section of the SAT at the age of 13, a distinction achieved by one in
10,000 students. A quarter-century ago, there were 13 boys for every
girl at level. NOW THE RATIO IS ONLY 2.8 TO 1, A PRECIPITOUS DROP
THAT HAS NOT BEEN REPORTED IN THE NEWS MEDIA. [Our CAPS.] 'It's gone
way down as women have had an opportunity to take their math
earlier,' says Mr. Stanley."
To dig deeper see the annotated references given in Part 2 of Hake &
Mallow (2008): 50 references to "Sex Differences in Mathematical
Ability: Fact or Artifact?" and 12 references to "Harvard President
Summers' Speculation on Innate Gender Differences in Science and
Math."
Benbow, C.P. 1988. "Sex Differences in mathematical reasoning ability
in intellectually talented preadolescents: Their nature, effects, and
possible causes," Behavioral and Brain Sciences, 11:169-232; online
at <http://www.vanderbilt.edu/Peabody/SMPY/BBSBenbow.pdf> (33 MB).
Benbow's 15-page article, pp. 169-183, is followed by (a) 35 pages of
"Open Peer Commentary," pp. 183-217; (b) 9 pages of Benbow's
response, pp. 217-225; and (c) 8 pages of References, pp. 225-232.
Cohen, J. 1988. "Statistical power analysis for the behavioral
sciences." Lawrence Erlbaum, 2nd
ed. Amazon.com information at <http://tinyurl.com/2sjldk>.
Hake, R.R. & J.V. Mallow. 2008. Gender Issues in Science/Math
Education (GISME): Over 700 Annotated References & 1000 URL's:
*Part 1 - All References in Alphabetical Order
<http://www.physics.indiana.edu/~hake/GISME-5t-Part1.pdf> (8.5 MB);
*Part 2 - Some References in Subject Order
<http://www.physics.indiana.edu/~hake/GISME-5t-Part2.pdf> (4.8 MB).
Because periodic updates of GISME necessitate changing the URL's, an
address that will always work is "Reference 55 at
<http://www.physics.indiana.edu/~hake/>."
Part 2 subjects are:
(a) Affirmative Action;
(b) Constructivism: Educational and Social;
(c) Drivers Of Education Reform and Gender Equity: Economic Competitiveness and
Preservation of Life on Planet Earth;
(d) Education and the Brain;
(e) Gender & Spatial Visualization;
(f) HARVARD PRESIDENT SUMMERS' SPECULATION ON INNATE GENDER
DIFFERENCES IN SCIENCE AND MATH ;
(g) Hollywood Actress Danica McKellar's book "Math Doesn't Suck";
(h) Interactive Engagement;
(i) International Comparisons;
(j) Introductory Physics "Curriculum S" (for Synthesis);
(k) Is There a Female Science? - Pro & Con;
(l) Schools Shortchange Girls (or is it Boys)?;
(m) SEX DIFFERENCES IN MATHEMATICAL ABILITY: FACT OR ARTIFACT?;
(n) Status of Women Faculty at MIT.
Monastersky, R. 2005. 'Women and Science: The Debate Goes On: Primed
for Numbers - Are boys better at math? Experts try to divide the
influences of nature and nurture." Chronicle of Higher Education
51(26): A1, 4 March; online at
<http://chronicle.com/free/v51/i26/26a00102.htm>.
Seattle Times News Service. 2008. "In math, girls and boys are equal:
Sixteen years after Barbie dolls declared, 'Math class is tough!'
girls are proving that when it comes to math, they are just as tough.
. . . " online at
<http://seattletimes.nwsource.com/html/nationworld/2008071972_math250.html>.