Math and Science Achievement

Science ◽  
2005 ◽  
Vol 307 (5709) ◽  
pp. 481-481 ◽  
Author(s):  
R. W. Bybee
2010 ◽  
Vol 37 (3) ◽  
pp. 265-276 ◽  
Author(s):  
Tina Vršnik Perše ◽  
Ana Kozina ◽  
Tina Rutar Leban

2001 ◽  
Vol 9 ◽  
pp. 33 ◽  
Author(s):  
Algirdas Zabulionis

In 1991-97, the International Association for the Evaluation of Educational Achievement (IEA) undertook a Third International Mathematics and Science Study (TIMSS) in which data about the mathematics and science achievement of the thirteen year-old students in more than 40 countries were collected. These data provided the opportunity to search for patterns of students' answers to the test items: which group of items was relatively more difficult (or more easy) for the students from a particular country (or group of countries). Using this massive data set an attempt was made to measure the similarities among country profiles of how students responded to the test items.


2017 ◽  
Vol 61 (3) ◽  
pp. 250-261 ◽  
Author(s):  
Susan G. Assouline ◽  
Lori M. Ihrig ◽  
Duhita Mahatmya

High-potential students from underresourced rural schools face barriers that reduce options for academic advancement, which widens the excellence gap between them and their more affluent, but similar ability peers. The goal of this study was to investigate the effectiveness of an expanded above-level testing model to identify high-potential rural students for an extracurricular math and science enrichment program. Results from our analyses indicated that a more inclusive talent pool differentiated among high achievers to find greater percentages (13%) of talented students compared with most gifted programs (3% to 5%) or Talent Search programs (5%). Overall, students’ math and science scores were related to a 75% and 50%, respectively, greater odds in being identified for the extracurricular program. Regardless of program participation, all talent pool students increased their math and science achievement; however, there were some significant gender differences.


2007 ◽  
Vol 8 (1) ◽  
pp. 1-51 ◽  
Author(s):  
Diane F. Halpern ◽  
Camilla P. Benbow ◽  
David C. Geary ◽  
Ruben C. Gur ◽  
Janet Shibley Hyde ◽  
...  

Amid ongoing public speculation about the reasons for sex differences in careers in science and mathematics, we present a consensus statement that is based on the best available scientific evidence. Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive. Successful careers in math and science require many types of cognitive abilities. Females tend to excel in verbal abilities, with large differences between females and males found when assessments include writing samples. High-level achievement in science and math requires the ability to communicate effectively and comprehend abstract ideas, so the female advantage in writing should be helpful in all academic domains. Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized exams in mathematics and science. An evolutionary account of sex differences in mathematics and science supports the conclusion that, although sex differences in math and science performance have not directly evolved, they could be indirectly related to differences in interests and specific brain and cognitive systems. We review the brain basis for sex differences in science and mathematics, describe consistent effects, and identify numerous possible correlates. Experience alters brain structures and functioning, so causal statements about brain differences and success in math and science are circular. A wide range of sociocultural forces contribute to sex differences in mathematics and science achievement and ability—including the effects of family, neighborhood, peer, and school influences; training and experience; and cultural practices. We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics.


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