Recent research in education and psychology points to the consequences of brain development on learning and an optimal educational environment. Current debate surrounds the extent to which the structures and functions of anatomy, physiology and personal experiences may be gender specific (Blakemore, 2005; CQ Press, 2005). As such, pre-determined. Furthermore, if learning is gender biased according to activity is this due to innate sex differences or socializing processes that have an affective result which can regulate hormones and neurotransmitters, and the brain has the ability for a degree of plasticity over the lifespan.
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One school of school of thought contends that matching a learning environment with the needs of the learner (e.g., color, setting, lighting, audio, scent, textures, aesthetics). This implies that an interactive process occurs between the individual and their external environment, which in turn leads to changes in neural pathways and memory cues. Also, curriculums can be tailored to meet the learning needs of students. Another approach takes this concept one step further and maintains that gender-specific stimuli and cues exist to aid learning. Suggesting that females and males are “wet-wired” differently and will likely excel in different areas of skill, knowledge and competency.
The consequence of accepting such an extreme viewpoint is the rigidity of the outcome that does not allow for variability; differences make the world go round. Mono-sex classrooms may constrain competition, flirting and posturing that hinders learning, however, they also enhance interpersonal skills, help to dispel stereotypes and cultivate a sharing of different understandings and ways of problem solving. It may be that at this point in time gender-specific learning can be of some aid to some students, given that western society upholds values that pressure girls and boys to “Keep up with the Joneses”, “Just do it” and “Stay Young”. However it is contended here that differences in the learning experiences that are found to be derived from gender will be the result of socialization into ways of interpreting and navigating the world.
The inferior parietal lobule (IPL) has been found to be one of many neocortical regions that exhibit gender diomorphic characteristics that can be attribute to the brain’s asymmetric form (Frederikse, Lu, Aylward, Barta, & Pearlson, 1999). Measuring IPL gray matter volume of the sulci and gyrus of the cortex as well as the magnetic resonance imaging of 15 matched pairs of females and males. Overall men had the significantly larger volumes of IPL, particularly in the left hemisphere. Also, males exhibited a left right asymmetry for IPL when compared to women. There also appeared to be less distinct asymmetry in female participants. It was concluded that these dimorphisms could be the result of cognitive differences observed decision making and actions across genders.
As structure is felt to influence and constrain function, avid research has been undertaken in exploring the structural differences across genders. These structural differences have been contended to explain gender differences in learning styles, ways of reading, communicating, memorizing, navigating and problem-solving (Sax, 2005). It has been suggested that women tend to rely more on emotional contexts during learning processes. It has also been put forth that the genders develop at different rates, affecting the acquisition of cognitive skills such as spatial memory, language, cooperation and interpersonal communication. It may be that hormones modulate other system functioning and so orient learning style in a particular direction.
Sax states that gender is not as fluid as previously thought especially during the formative years of childhood. According to the research reviewed and promoted by Sax, boys are inherently more aggressive, whilst girls naturally more shy. He goes on to argue that education needs to consider gender issues more carefully and debate more about the needs for single-sex education, he is the founder of the National Association for Single-Sex Public Education. He argues that girls are more likely to adopt the study of physics and boys literature if single-sex schools were introduced. A book on the subject by Gurian & Henley (2001) critically reviewed brain-based literature to determine if boys and girls do actually learn differently, and if they do how the processes compare and contrast. Their book also focuses on the practical application for parents and educators to target information acquisition during early childhood and elementary, as well as secondary teaching. The research approach was a three-pronged viewpoint; neurological and endocrinological effects on learning and behavior; developmental psychology; and gender-difference research. The book is also comprised of teacher experiences to provide guidance across all grades to create an ideal classroom learning experience. The evidence drawn on emphasizes how brain differences can induce gender differences in how girls and boys learn and apply multiple intelligences. Other issues cited as contextual to gender-based learning include; attachment patterns, nutrition, interpersonal skills, discipline and motivation techniques, managing conflict and the use of the outdoors as a “classroom”. Overall the book heralds a bright future guided by parents, teachers and administrators trained and oriented toward a gender-based education.
Increasingly it has been noted that young girls do not initially engage with computer games in the way that boys do, the games predominantly focusing on aggression, conflict, noise and continuous action (Gorriz & Medina, 2001). It has been suggested that software writers look to producing games of interest to girls to help motivate them into the study of computer sciences. They point to research that supports findings of girls are more collaborative instead of competitive as boys tend to be. Girls also appear to prefer using problem-solving skills as compared to boys’ preference of hand-eye reflex activities.
Gender differences in mathematics are often cited as a clear indication of gender-specific learning areas of the brain. Blakemore ( ) contends that these apparent differences are not attributable to biology, as it appears that across cultures variations in the size of gender effects exist. For example in China girls outperform boys in the USA in the area of mathematics. Further support for the non gender-specific nature of math is evident in the finding that girls from China who are educated in the USA tend to see their math scores decline after immigration.
Blakemore also notes that much literature is ignored that attests to a high degree of overlap between the math scores of girls and boys. It is evident that across the globe many girls do as well as or better than boys in mathematics. The research they cite points to a thirty year trend of a closing gap for differences in math ability across genders. Such a finding supports the argument that apparent gender differences in some learning are due to socio-cultural influences. In fact there seems to be a growing trend in the UK and the USA for girls to outperform boys on national math tests.
It is contended that culture is inherent to human social systems. Its importance to interpersonal and cognitive development that many researchers look to the structure and functioning of the human brain to define what it is to be human (Boesche, 2003). However it has been noted that different species exhibit cultural abilities. Social learning and the acquisition of cultural traits, of understanding and application of collective meaning and communication, show that differences may merely be variation. Looking to cross-cultural diversity in brain characteristics in humans, a contrast here is made with chimpanzees. Similarly, it is contended that gender studies would provide a range of learning behaviors that could inform about distances between types of learning, and the matching of particular skills to social roles tending to be adopted by a particular gender.
There have been studies into the effects of gender on neuropsychological systems like the executive functioning (EF). Seidman and colleagues (2005) compared girls with ADHD and their expression of neuropsychological features similar to those found in boys, to see whether these impairments are found in preteen samples. Blind testing of EF performance was collected in a clinical setting and regression analysis controlled for age, socioeconomic status, learning disability and psychiatric comorbidity. Both genders with ADHD were significantly more impaired on some EF tasks as compared to the non-ADHD groups. However within each of these groups, based on gender, there were no significant differences in performance. There were no observed significant interactions across gender and diagnosis than would be expected by chance.
Overall it appears that although differences in structure do exist, they are subtle. And they are likely due to socio-cultural and environmental interaction with the individual, functioning adapting to acquisition and ability. It is important to tailor curriculum across learning differences, inclusive of gender as a contributing factor to how a person may ideally learn. Differences do appear to exist but these also appear to be reducing, particularly in the last three decades.
This paper has demonstrated that apparent gender-differences in “intrinsic aptitude” (CQ Press, 2005. p.1) may be grounded more in sex discrimination and socialization. Of benefit to sourcing such differences in social differences empowers interventions to change the patterns of learning at present. The gender gap in education is something can be repaired with informed choices for; policy, procedures, commitment to student-focused learning and a passion for enabling and facilitating understanding in others will enable.
Blakemore, S-J. (2005) The Learning Brain: Lessons for education. Blackwell Publishing.
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Boesche, C. (2003) Is culture a golden barrier between human and chimpanzee? Evolutionary Anthropology: Issues, News, and Reviews, 12(2): 82 – 91. CQ Press (2005) Gender and learningL Are there innate differences? CQ Researcher, 15(19): 3 -13.
Frederikse, M. E., Lu, A., Aylward, A, Barta, P. & Pearlson, G. (1999) Sex differences in the inferior parietal lobule. Web.
Henley, P. & Gurian, M. (2001) Boys and Girls Learn Differently! A guide for teachers and parents. San Fransisco: Jossey-Bass Publishers.
Glazer, S. (2005). Gender and learning. CQ Researcher, 15(19): 3 -13.
Gorriz, C. M. & Medina, C. (2001) Engaging girls with computers through software games. Communications of the ACM, 43(1): 42 – 49.
Sax, L. (2005) Why Gender Matters. London: Double Day.
Seidman, L. J. et al. (2005) Impact of gender and age on Executive Functioning: Do girls and boys with and without Attention Deficit Hyperactivity Disorder differ neuropsychologically in preteen and teenage years? Developmental Neuropsychology, 27(1): 79-105.