Gender and Education – Annotated Bibliography

Al Otaiba, Stephanie, Brandy Gatlin, Young-Suk Kim, and Jeanne Wanzek. “Toward an Understanding of Dimensions, Predictors, and the Gender Gap.” Journal of Educational Psychology. 107.1 (2015): 79 – 95. PsycARTICLES. Web. 12 Oct. 2015.

Stephanie Al Otaiba and her associates in this study examined the gender gap in writing in light of factors typically used to score writing assessments and indicator factors that help predict student success in writing. Over four hundred second and third graders were tested, many of which were in a lower income bracket and of a racial minority. This may provide some bias, though it seems to evidence the prevalence of this phenomenon.

The authors discuss how it has been evidenced that boys generally perceive less utility and intrinsic value for writing, which is supported by Michael Gurian’s book and provides comparison to the Dicke et al. study. The researchers found that within this study boys scored between 0.37 and 0.46 standard deviations lower than girls in writing quality, productivity, and incorporation of curriculum-based elements. However, when certain indicator factors, including reading, oral skills, spelling, letter writing automaticity, story copying, random automatized naming, and attention, were controlled for, this gap was reduced. This shows that gender differences in writing are partly influenced but cannot be totally explained by gender differences in these predictors. However, attention is one predictor that may really influence reading and writing gender gaps. Boys are much more likely to be diagnosed with attention problems, as explained in both this source and Guurian’s novel. This could prove a greater challenge in reading and writing because they are more sedentary. As such, this source contributes to answering why the gender gap in language arts exists, and helps me begin to understand how curriculum could be altered to benefit more active males in these subjects.


Andrews, Glenda, David L. Neumann, and David Reilly. “Sex Differences in Mathematics and Science Achievement: A Meta-Analysis of National Assessment of Educational Progress Assessments.” Journal of Educational Psychology. 107.3 (2015): 645 – 662. Ebscohost. Web. 7 Oct. 2015.

This scholarly article does a thorough job of mapping the terrain of and key players in the conversation happening around the gender gap in the STEM fields. The authors of this study provide arguments from the biological perspective, mostly provided by evidence from sex hormone research and evolutionary psychology. These same concepts are supported in greater detail by Michael Gurian in Boys and Girls Learn Differently. They also explain that many experts argue that social and cultural factors that contribute to gender stereotyping offer greater influence. Glenda Andrews and her associates, however, maintain that both make considerable contributions to the perceived gender gap in the STEM fields. This better contributes to my understanding of why gender gaps in education exist.

This particular source compiles a meta-analysis of mathematics and science data given for 1990-2011 by the National Assessment of Educational Data. The researchers detail the reliability of this method of assessment to avoid bias. However, these assessments rely heavily on multiple choice questions, which Gurian explains may also be tailored to male decisiveness. The authors of this meta-analysis have found that there is a definite gender gap in math and science that persisted throughout the twenty-two years of data collection. This could go against social theories. The gap widens as children age, which supports biological theories. There are two startling results of this study. There is more variance in math and science achievement among males, though the ratio of male to female high achievers in STEM is over 2:1. In addition, the life sciences showed little to no gap, possibly evidencing a difference in “patterns of interest and motivation toward people-oriented fields,” “rather than indicating any inherent lack of ability” (Andrews et al., p. 10).


Brisson, Maria Brigitte, Anna-Lena Dicke, Barbara Flunger, Hanna Gaspard, Isabelle Häfner, Benjamin Nagengast, and Ulrich Trautwein. “Fostering Adolescents’ Value Beliefs for Mathematics with a Relevance Intervention in the Classroom.” Developmental Psychology 51.9 (2015): 1226 – 1240. Ebscohost. Web. 19 Oct. 2015.

This source focuses on intrinsic and utility value of mathematics as motivators for higher achievement. Maria Brigitte Brisson and her associates developed two intervention strategies to be integrated in ninth grade math classes in Germany. This, therefore, may not be directly applicable to the US’s education system but certainly demonstrates that a gender gap in mathematics exists beyond the borders of the United States. Both interventions utilized a presentation that educated students on the importance of effort and self-efficacy for math achievement and a homework journal. The first intervention strategy, referred to as the quotation method, instructed students to read interview quotes from young adults giving personal examples of math’s usefulness and evaluate them. The second intervention, called the text method, required students to write an essay arguing math’s relevance to their current and future lives.

Based on surveys given before and after the intervention methods, it was shown that both interventions increased utility value for girls while the quotation method also increased intrinsic value of math. This and the fact that each intervention was given by women provides some basis for positive role modeling in the classroom as a possible strategy to narrow the gender gap. This idea is echoed in Michael Gurian’s novel, but for boys in particular. However, neither intervention showed much positive growth for males in motivational value of math. The authors speculate that perhaps the greater positive effects for girls in the interventions could be due to the incorporation of writing. This would be supported by biological differences outlined in Gurian’s book. It also provides further evidence in conversation with this novel that there should be overlap in teaching linguistic and spatial subjects. One aspect of this study that would support social theories detailed in the Andrews et al. article is that these interventions included utility value examples of math for more historically female-typed careers.


Dicke, Anna-Lena, Barbara Flunger, Hanna Gaspard, Isabelle Häfner, Benjamin Nagengast, Brigitte Schreier, and Ulrich Trautwein. “More Value through Greater Differentiation: Gender Differences in Value Beliefs about Math.” Journal of Education Psychology. 107.3 (2014): 663 – 677. PsycARTICLES. Web. 7 Oct. 2015.

In this study, through survey collection and analysis, researchers were able to deconstruct types of motivational factors into facets that offered greater insight into the “why” behind gender gaps in STEM subjects. In any survey study, and particularly since participation was voluntary based on parental consent, bias due to wording is a possible concern; however, these questions and statements appear to be simple enough to generally avoid much examiner bias. It should also be noted this source helps establish some of the key players in this scholarship, as some of the researchers involved in this study also co-authored the Brisson et al. article.

The study found that males show greater intrinsic and utility value for math, while girls associate a higher emotional cost with math. This emotional cost could manifest itself in anxiety, which has been demonstrated in other sources I have collected and corresponds to evidence provided in Gurian’s Boys and Girls Learn Differently as to how girls and boys manage emotion differently. The only facet that girls responded more positively to was that math was important for earning good grades. This suggests that girls put more weight on high achievement in academics, which could speak to the greater variance in male math performance evidenced in the Andrews et al. article.


Gurian, Michael and Kathy Stevens. Boys and Girls Learn Differently. San Francisco, CA: Jossey-Bass, 2011. Print.

Michael Gurian presents an argument for the biological reasons for gender differences in learning, maintaining that they firstly exist and secondly are predominantly the result of hormonal, brain developmental, and evolutionary biological differences. It should be noted that he allows for some social influence, which most of my other sources focus on. Brain differences as causative factors that influence gender gaps in language arts and STEM subjects are one partial answer to my question of why these gender gaps exist. Whereas the authors of most of my other sources write from the perspective of girls as disadvantaged by society, Gurian seems to stress boys as more disadvantaged by current school system structures due to biological factors. This may tie into my findings that there is more variance among males than females in scholastic achievement.

This source is exceedingly helpful for contributing to my question about how curriculum can be changed to better encourage success for both genders in all areas. Rather than just focusing on intervention strategies, like those within the Brisson et al. study, this book talks more about overarching teaching strategies that could be implemented earlier. Generally, Gurian encourages teaching methods that integrate spatial, tactile, and linguistic activities that tailor to a variety of learning styles. He also gives some biological background and strategies for helping each gender process emotively, which could help to narrow the gender gap. This could help girls gain higher self-efficacy and limit anxiety, which have both been shown in other sources to hinder female proficiency in mathematics and sciences.


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