Gender difference on self-esteem and math engagement
Gender difference on self-esteem and math engagement
The categorization of men coming from Mars and women coming from Venus can more than substantiate that each gender is definitive. Case in point, men are known to be physically stronger, temperamental, and hard headed compared to women who are known to be emotionally stable, svelte, and composed. Even in terms of moral development both gender have different scale to measure what is morally correct. So it is not hard to assume that on other aspects of life this difference will continue.
For example on the field of education, women who are less aggressive take up mainly those that rely on discourse such as philosophy, anthropology, creative writing, and theater while men who are known to be aggressive will mainly take courses on engineering ad math-related courses (National Center for Educational Statistics, 2007). In the same vein, the paper would like to address the issue on gender difference centered on self-esteem and math engagement. The paper would like to hypothesize on the two variables. For self-esteem we hypothesize only an inequality frame by gender interaction on self-esteem. Specifically, we hypothesize that when gender inequality in math is framed as females being disadvantaged, women will have higher self-esteem then men. In contrast, when the gender inequality is framed as males being advantaged, men will have higher self-esteem then women. For Math engagement, We hypothesize only an inequality frame by gender interaction on math engagement. Specifically, we hypothesize that when gender inequality in math is framed as females being disadvantaged, men will be more engaged in math then women. In contrast, when the gender inequality is framed as males being advantaged, women will be more engaged in math then men.
Review of related literature
The theory on disengagement started from the belief that because of cultural gender stereotyping the gender who is perceived to be of lesser importance will automatically withdraw and subsequently not participate in a field of discourse (Schmader, Major, Gramzow, 2001). Since self-esteem is an integral factor in growing is was best advised by Cast and Burke (2002) that it is important to cultivate view of oneself. For this will not only help you through negative predicaments but can also help you verify your identity which leads to motivation (Cast Burke, 2002). If a person has enough motivation they become more capable of out performing their definition on the cultural context.
On Schwalbe and Staples (1999) research about gender difference and self-esteem they found that a genders role in society affects a persons view on worth. The study concluded that women are greatly affected by feedback. If a woman, for example, tried playing golf and came in last she automatically feels bad and prevents from playing the game. For men, they view self-esteem if there is basis for comparison. For example, a young man tries to run a 400-meter course and the time he clocked was better than other men he will have greater self-esteem compared to those who clocked at longer time. If this is true then it can imply that men will strive to compete more to assure themselves the knowledge that they are greater than the rest increasing their self-worth in the end.
The implication of gender difference can greatly be seen on the academic setting. It has been concluded by a dozen of research that women are superior in terms of achievement in the academe but some research suggested otherwise. On Gorard, Rees, and Salisbury s (2001) study they were able to test the hypothesis by measuring level of achievements of both gender onn the most common subject matters Math, Science, and English. The conclusion they arrived to was that the gap that people thought of between genders is not at all significant. Both gender are evenly matched. Though some of the results presented slightly elevated numbers for the women sample it was not statistically significant to make a case. This only implies that both gender can easily adapt to its environment. The conclusion derived from the study was also the same conclusion on Ding, Song, and Richardsons (2002) study. They were able to conclude that there is not enough evidence to suggest that women or men is greater when it comes to academic achievement. The results of the examination showed that both gender have the same growth in Mathematics performance. The only contrasting description that came out of the study was the higher grade-point average of women. But on Felson and Trudeaus (1991) study the findings were different the study showed that men have higher test results o mathematics while women have higher test results on subjects other than Mathematics. What these implies is that there is not enough data to assume which gender is better.
Method
Participants
The proposed number of participants was set at 80 but due to unavoidable circumstances the total number of participants became 79. 40.5 of the participants were females while 59.5 were males. The age range of the participants is 47, the minimum age of the participant was 12 and 59 as the maximum. The mean age is 25.04, and standard deviation at 9.26.
Out of all who participated 71 were able to give their school year. There were participants from all the year levels. Seven participants came from first year, 8 from second year, 19 from the third year, 21 from the fourth year, and 16 from the fifth year students. While 8 students were not able to give out their age. With standard deviations at 1.239 years. The mean years in school was 3.44. 40.5 of the sample came from the female population while 59.5 from the male population.
Materials and design
A ready made questionnaire was used to measure mathematical ability of the participants. It was a 7-minute standardized math exam used by students on Psychology 311 that is designed to measure gender inequalities in Mathematics. The tests is a 20-item arithmetic test that is focused on the four basic operations.
The questionnaire also asks about the participants attitude to oneself and their math ability before and after taking the 7-minute arithmetic operations test. They are presented with a 7-point Likert-type scale to assess, questions like how do they feel when they do well on math and at times I think I am no good at all.
The demographics part asked for age, year in school, gender, and racial background. It also asked for the participants GPA, math SATACT score, verbal SATACT score, and the percentile rank o the math exam. And the last part asked about the cause of gender inequality.
Procedure
Participants are randomly selected to avoid affecting the reliability of the results of the examination. After being briefed about the study they were asked to take the examination for 10-15 minutes. There were two specific conditions before and after taking the math examination. The first condition was that not all participants are going to read the same article on gender disadvantage. Half of the participants read women are at a disadvantage while the other half read that men are at a disadvantage. After taking the math exam a feedback was given, another condition was given here again. All participants received false feedback on their results. All participants were told that they performed badly on the examination before they proceeded to rate their self-esteem to measure how negative feedback affects ones self-esteem. The test was administered for a whole day.
Results
All the participants were able to gauge their self-esteem and were able to take the examination. For self-esteem the minimum rate they were bale to rate themselves was at 1.80 indicating low self-esteem with a maximum value on 6. Compared to self-esteem questions participants viewed themselves at extreme.
For participants who read the article on female disadvantage the mean value of their self-esteem is M4.75058. With female participants mean at M4.7375 and male participants at M4.6828. For participants who read male disadvantage the mean value of their self-esteem is slightly higher at M4.8640. With the female population increasing their self-esteem with mean score at M5.1375 and men having lower self-esteem with mean score at M4.6889.
Under math engagement, those who read about female disadvantage had mean score of M4.75 while those who read about male disadvantage had mean score of 4.8049. The general SD for math engage is SD4.7785. Male participants who read about female disadvantage had greater means score compared to the female counterpart, the means score for male was M5.2727 compared to female participants who had 4.0313 with SD at SD4.750. While the same effect happened female participants read about male disadvantage. The female participants had M5.0625 while the male population had M4.6400 and the SD was at SD4,8049.
The result showed that majority of the male participants who were given articles on gender advantage were eager to solve the math problems even though they were given negative feedback their self-esteem was never affected. On the other, when the male participants were given article on female disadvantage, they would not feel eager, and when given the negative feedback their self-esteem decreases. The same notion applies to females.
The results did not revealed a significant main effect of inequality framing, F(1,75) 1.56, p .05, or of gender, F(1,75) 2.39, p .05 for self-esteem. In contrast to our hypothesis, there was not a significant interaction between inequality frame and gender, F(1,75) 1.47, p .05.
The results did not revealed a significant main effect of inequality framing, F(1,75) .55, p .05, or of gender, F(1,75) 2.31, p .05 for math engagement. There was a significant inequality frame by gender interaction, F(1,75) 9.55, p .05. In partial support of our hypothesis, when the inequality was framed as female disadvantage, men were more engaged in math then women. In contrast to our hypothesis, when the inequality was framed as male advantage, men and women did not differ in their level of math engagement.
Discussion
The purpose of the study is to gauge how gender has effect on self-esteem and mathematical ability. Based on the findings there were no significant results to indicate that self-esteem is affected by gender nor can did it affect mathematical enagement. The findings were not able to support claims that women show poor self-esteem because they are not good in mathematics as well as for me.
The study easily appended the findings done by other researchers wherein they hypothesized that there was no truth in regard to gender gap on self-esteem and math engagement. The issue on gender gap might have just been an issue on double standards. The findings of the study were the same as those that indicated that women are less competitive just because they see obstacles in front of them.
The result of the study could have been affected by the variables. Since it only measured the difference on arithmetic ability, the result is one-sided. To further prove that there is no existing gender difference in regard to education, other variables such as Science and English should be taken into consideration. The apparatus used on the study should have more items to increase the reliability to measure knowledge.
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