Genders Impact on School Attitudes and School Performance - Essay Example

? Article critique: Gender’s impact on school attitudes and school performance 15 March Article critique: Gender’s impact on school attitudes and school performance Studies show mixed results on the impact of gender on school attitudes and performance. On the one hand, some studies demonstrate that students can score similarly in subtests of Mathematics (Rosselli et al. 2009; Tsui 2007). On the other hand, other studies note differences in school attitudes toward certain subjects (Francis 2000; Hargreaves, Homer, and Swinnerton 2008; Warrington, Younger, and Williams 2000) and differences in General Certificate of Secondary Education (GCSE) exam scores (Gray et al. 2004; Putwain 2008) and Science scores (Okoye 2009). Still, one study argues that gender differences can be found based on problem type: “boys outperformed girls on spatial/conceptual measurement, whereas girls outperformed boys on formula-based measurement, as well as on a test of computation skills” (Vasilyeva et al. 2009, p.401) or personality (Petrides et al. 2005), while others provide evidence that stereotype threats can lead to gender differences in female students' maths performance (Ahmavaara and Houston 2007; Good, Woodzicka, and Wingfield 2010; Keller 2007). This essay criticizes the articles “The gendered subject: students' subject preferences and discussions of gender and subject ability” by Francis (2000) and “Student attitudes, image and the gender gap” by Warrington, Younger, and Williams (2000). In “The gendered subject: students' subject preferences and discussions of gender and subject ability,” Francis (2000) examines whether there have been any changes in students’ constructions of gender and learning, because of changes in achievement trends and perceptions of gender. The author also studies their perceptions of most popular and least popular subjects and their beliefs about gender and ability. The study is a correlational design, wherein relations between gender and subject preferences and ability are determined. The sampling strategy is random sampling from three different mixed-sex schools in Greater London. Author conducted classroom observation and semi-structured interviews with one hundred 14 to 16 year old students. Findings showed blurring in gendered subject preferences, because boys favoured English, while girls preferred Math as the second favourite subject. However, in terms of students’ least preferred subjects, the sample was more traditional, with mathematics and science the least well-liked subjects among girls, and French the least well-liked among boys. Still, maths was rated second least preferred by boys, and French third least preferred among girls, which indicates greater diversity. As for responses on gender and subject ability, majority believed that ability at different subjects are not connected to gender. Still, those who believed that gender is a factor in different subjects agreed that girls were better at some or all subjects than boys. Francis concluded that stresses on female superiority should not be taken as an indication of absence of worry among educators, because it means that gender gap continues to persist, but at a different direction. It is important to stress the potential of both genders for all subjects to erase stereotyped images. Warrington, Younger, and Williams (2000) study the attitudes of students to GCSE work and explore why boys and girls seem to view their work in different ways, with emphasis on “image” in the article “Student attitudes, image and the gender gap.” Like Francis (2000), Warrington, Younger, and Williams (2000) conducted a correlational study using qualitative analysis. Warrington, Younger, and Williams (2000) used triangulation for data gathering: focus group interviews with groups of girls and boys, lesson observations and teacher interviews. Findings showed that girls are not stigmatised for hard work in class, while boys experience that their image is affected when they study hard in school. For them, it is not “cool” to be studious. Furthermore, there was evidence that boys were far less likely than girls to foresee failure or the effects of failure: they were more certain in themselves, believing either that they would do well in the examinations in spite of poor effort or that some subjects at least were insignificant and not worth focusing on. They were also less concerned of the future and were more confident in attaining their long-term goals. This essay proceeds to criticising these articles. In terms of research design, the correlational design enables both Francis (2000) and Warrington, Younger, and Williams (2000) to answer their research questions. They are comparing gender differences with respect to subject preferences and subject ability or student attitudes and image and results can be gained from a qualitative correlational research design (Francis 2000; Hargreaves, Homer, and Swinnerton 2008). These articles shared weaknesses in lack of discussion of threats to internal and external validity. This is problematic, because it might suggest that if they have not identified these threats, then they may also not have properly responded to them. Some of the identified internal threats for both articles are history and instrumentation. History may affect student responses, where external variables can make self-reports less reliable. For instance, the presence of female observer in the study of Warrington, Younger, and Williams (2000) and Francis (2000) might have motivated girls to think positively of working hard, while demotivating boys about their subject abilities and attitudes. Unreliable operationalisations of constructs or discrepancy in giving instructions to participants, or training to assessors can weaken internal validity. Authors of both studies lacked explanation on how they operationalised their constructs, how instructions were provided, and training of assessors. The potential threats to the studies’ external validity were people, place, and time. The setting might have variables that can impact student responses. The students might not represent the population enough, because the sampling was small and the time may not have been right for taking the survey. There should have been efforts to have greater control of the data collection process, such as choosing certain and similar timeframe and place conditions. Researchers can and should use a variety of strategies to engage with issues of external validity and advance generalizability of findings. Both studies ensured that the groups are equivalent. Francis (2000) used equal number of boys and girls. Warrington, Younger, and Williams (2000) prevented the potential for bias in the understanding of the systematic observations, by analysing data in terms of mean levels of communication per girl and boy to consider the ratio of boys and girls present in each lesson. Authors of both studies provided overviews of the settings. For instance, Francis (2000) mentions that the schools are mixed-sex and that they are made of a Catholic school (St. Mark’s) and two comprehensive (Richardson and Sandyfields) schools. They are situated in the inner city, a semi-suburban area (St. Mark’s: Zone 3) and Greater London (Richardson: Zone 4) areas. However, Francis (2000) does not mention the setting of the actual interviews. Warrington, Younger, and Williams (2000) provide more explanation that they considered seating location, for instance. Their methodology section also states that they made a more qualitative descriptive ethnographic description of the events which took place in the classrooms and that they focused on: the substance of the questions that students asked; the movement of the teacher and students; the teaching activities; and the teachers’ views on background factors that might help the observer better comprehend the class or lesson. The sampling methods for Francis (2000) and Warrington, Younger, and Williams (2000) are random sampling methods, because the participants are chosen randomly from the whole sampling. Each member of the population has an equal and predictable chance of being selected. There was no special condition or any other factor that narrowed the participation of other students. The sampling method could have provided representative sampling, but the sampling is too small to provide generalisable results. The design is further connected to the sampling method, because the researchers wanted to discover correlations on the subject and the right population characteristics are present for the sampling method. Francis (2000) and Warrington, Younger, and Williams (2000) did not sufficiently discuss their major instruments, including type (e.g. Likert scale.) and level of measurement. This is problematic, because readers could not ascertain if measurement methods adequately measure their variables. The measurements have questionable reliability and validity, without discussions and samples of questionnaires. The absences of pre-testing for the self-made questionnaires also weaken their reliability and validity scores. The implications for the findings of the study is that if there was inadequate information about reliability or validity testing, the findings may be inaccurate and invalid to the sample and the findings will no longer be that useful to other educators and school administrators. Francis (2000) and Warrington, Younger, and Williams (2000) did not fully discuss the data collection methods. Still, at least Warrington, Younger, and Williams (2000) considered other variables, such as seating arrangements, substance of the questions that students asked; the movement of the teacher and students; the teaching activities; and the teachers’ views on background factors that might help the observer better comprehend the class or lesson, in their data collection measures. Furthermore, they conducted triangulation for data gathering, which enhances validity. Because of lack of information on data collection methods, I cannot answer if these measures addressed all the major research questions or hypotheses. Francis (2000) and Warrington, Younger, and Williams (2000) lacked a theoretical framework to base their findings on. One possible ground for gender difference in performance has been explained by the ‘Stereotype Threat Theory’ (STT). Stereotype threat happens when there is an unconstructive stereotype about a specific group which then weakens that group’s test performance (Steele 1997; Walsh et al. 1999 cited in Hargreaves, Homer, and Swinnerton 2008, p.22). The threat may be overtly stimulated by telling the group it is there for that test or domain or it may be secretly incited if it happens without any allusion (Hargreaves, Homer, and Swinnerton 2008, p.22). This can happen for mathematics, which is considered as a traditional male domain. Research indicates that if girls participate in a mathematical test condition along with boys, this can negatively affect the girls’ performance and when the threat is high, girls can hardly perform problem-solving strategies (Smith and White 2002 cited in Hargreaves, Homer, and Swinnerton 2008, p.22). These situations suggest that girls may not necessarily have lower competence in mathematics, but stereotypes are powerful enough to decrease performance motivation. STT indicates that if stereotype threat is strong, the effect will be larger (Inzlicht and Ben-Zeev 2000 cited in Hargreaves, Homer, and Swinnerton 2008, p.22). Hence, as a whole, the strengths of Francis (2000) and Warrington, Younger, and Williams (2000) are their correlational designs and sampling strategies. However, they both lacked discussions of theoretical frameworks (and biases), data collection methods, major instruments, including type and level of measurement, settings, and threats to internal and external validity. Furthermore, Warrington, Younger, and Williams (2000) exerted greater effort in equivalizing the groups under study and ensuring tconsistency of settings. Their study also has higher validity, because of triangulation for data gathering methods. Reference List Ahmavaara, A. and Houston, D.M., 2007. The effects of selective schooling and self-concept on adolescents' academic aspiration: an examination of Dweck's Self-Theory. British Journal of Educational Psychology, 77 (3), 613-632. Francis, B., 2000. The gendered subject: students' subject preferences and discussions of gender and subject ability. Oxford Review of Education, 26 (1), 35-4. Good, J.J, Woodzicka, J. A., and Wingfield, L.C., 2010. The effects of gender stereotypic and counter-stereotypic textbook images on Science performance. Journal of Social Psychology, 150 (2), 132-147. Gray, J., Peng, W., Steward, S., and Thomas, S., 2004. Towards a typology of gender-related school effects: some new perspectives on a familiar problem. Oxford Review of Education, 30 (4), 529-550. Hargreaves, M., Homer, M., and Swinnerton, B., 2008. A comparison of performance and attitudes in Mathematics amongst the "gifted": are boys better at Mathematics or do they just think they are? Assessment in Education: Principles, Policy & Practice, 15 (1), 19-38. Keller, J., 2007. Stereotype threat in classroom settings: The interactive effect of domain identification, task difficulty and stereotype threat on female students' maths performance. British Journal of Educational Psychology, 77 (2), 323-338. Okoye, N. S., 2009. The effect of gender, socio-economic status and school location on students performance in Nigerian integrated science. Education, 129 (3), 561-568. Petrides, K. V., Chamorro-Premuzic, T., Frederickson, N., and Furnham, A., 2005. Explaining individual differences in scholastic behaviour and achievement. British Journal of Educational Psychology, 75 (2), 239-255. Putwain, D.W., 2008. Test anxiety and GCSE performance: the effect of gender and socio-economic background. Educational Psychology in Practice, 24 (4), 319-334. Rosselli, M., Ardila, A., Matute, E., and Inozemtseva, O., 2009. Gender differences and cognitive correlates of Mathematical skills in school-aged children. Child Neuropsychology, 15 (3), 216-231. Tsui, M., 2007. Gender and mathematics achievement in China and the United States. Gender Issues, 24 (3), 1-11. Vasilyeva, M., Casey, B.M., Dearing, E., and Ganley, C.M. , 2009. Measurement skills in low-income elementary school students: exploring the nature of gender differences. Cognition & Instruction, 27 (4), 401-428. Warrington, M., Younger, M., and Williams, J., 2000. Student attitudes, image and the gender gap. British Educational Research Journal, 26 (3), 393-407. Read More