Self Monitoring and Self Esteem Have a Positive Relationship for Students - Research Paper Example

Self Monitoring and Self Esteem Have a Positive Relationship and are Both the Same for Male and Female September Table of Contents Table of Contents i List of Tables i Literature Review 1 Hypotheses 2 Study Design 2 Methodology 2 Data Collected 3 Results 3 Discussion 7 References 8 List of Tables Table 1: Descriptive Statistics 3 Table 2: Correlations 3 Table 3: ANOVA 4 Table 4: Coefficients 4 Table 5: Self Esteem Test of Normality 4 Table 6: Self-Esteem Test Statistics 5 Table 7: Self Esteem Descriptive Statistics By gender 5 Table 8: Self-Monitoring Tests of Normality 6 Table 9: Self-Monitoring Test Statistics 6 Table 10: Self Monitoring Descriptive Statistics By gender 6 Literature Review Self-esteem is related to self-monitoring in that being sensitive to how you appear to others is like being positive to your view and how you view others. High self-monitors always observe constantly what others are doing, how they do it in addition to how they respond to a behaviour associated with other people. Being a high self-monitor makes one self-conscious to an extend of wanting to look good at all times. This makes them good adaptors to different situations. Low self-monitors on the other hand tend to be oblivious of what others will think of them and always acts in such a manner that they tend to impress themselves and not others; to look good for themselves alone. For an example, in a dance floor, some people take the floors with wildness while others are calm and composed. In this case, the wild are said to be low self-monitors while the calm and composed are high self-monitors. According to Bommer, Miles and Grover (2003); Borman and Motowidlo (1993), self-esteem is a personal understanding in a quiet manner that you are worth being loved and accepted in society. The understanding that there is a form of reward in terms of love and respect makes some to be high self-monitors. Flynn, F. J. et al. (2006) in a study to investigate the impact of reward knowledge after performing a certain act using two groups; those informed of the rewards and those not, found out that those informed had more high self-monitors than low self-monitors while those not told had few high self-monitors than low self-monitors. According to Andersson and Bateman (1997); Blakely, et al. (2003), what are referred to as descriptive helping norms, individual helping norms and personal monitoring perceptions often have a positive relationship with perceived individual intentions capable of performing helping behavior. To Andersson and Bateman further, individuals in a certain group are in general influenced by the so called descriptive helping norms within groups although Andersson and Bateman argument is hinged on the fact that some group members are more influenced by such norms more compared to the other group members. According to Ehrhart and Naumann (2004), individuals with high self-monitoring levels are more influenced by the descriptive helping norms as compared to those individuals with low levels of self-monitoring. To Ehrhart and Naumann, this is so because individuals with high self-monitoring levels pay much attention to the social context around them and tend to attend closely the behaviours of immediate environment occupants in addition to being extra sensitive to group behavioral norms. This makes them to be more versed with the feelings of those they are with in the same group when compared to low level self-monitors. According to Johns, G. (2006), women rely entirely on self-monitoring so as to do away with negative gender autism in certain contexts. In a study with both male and females, Johns, found out that female participants had very high self-monitoring influential than low self-monitors while their male counterparts were benefiting less from self-monitoring behavior. Hypotheses Hypothesis 1: Individuals’ self-monitoring is positively associated with self esteem Hypothesis 2: Individuals’ self-monitoring and self esteem are the same for males and females. Study Design Methodology Students were required to use the Mel Lab to complete five tests measuring various personality traits. They were required to follow the usual steps in conducting a research project i.e. Design, conduct experiment, collect data, analyse the data using a statistical package, in this case SPSS and discuss the results. They were supposed to log on with your password, go to Network neighborhood, then to City_ac, software, psychology, mel_lab and copy the whole folder entitled mel_lab to their desktop. Open the application called “experime.” And complete all tests and record their scores and erase the mel_lab folder from the desktop. Data Collected Data of interest was recorded in a data sheet which had the following parts; Name, Age, Gender and 1st year’s GPA. Personality measures your score from Anomy, Locus of control scale, Self-esteem scale, Social desirability scale, and Self-monitoring scale were saved in the folder. Each student then collected the scores from all classmates and typed them SPSS in order to use them as their data for the lab report. Results Table 1: Descriptive Statistics N Minimum Maximum Mean Std. Deviation Self-Esteem 86 30.00 100.00 81.6279 18.20539 Self-Monitoring 86 .00 100.00 47.8837 21.51520 A total of 86 students participated in this study and had a minimum self-esteem score of 30 and maximum of 100 with a mean of 81.63. The students had a self-monitoring score of 47.88 on average with a minimum and maximum value of 0 and 100. The amount of variation was much higher in self-monitoring than in self-esteem. 31.4% were males while the remaining 68.6% were female participants. The mean age of the participants was 21.95 years while the mean score for 1st year’s GPA was 56.7. Table 2: Correlations ESTEEM MONITOR Self-Esteem Pearson Correlation 1 .034 Sig. (2-tailed) . .757 N 86 86 Self-Monitoring Pearson Correlation .034 1 Sig. (2-tailed) .757 . N 86 86 Self-esteem and self-monitoring have a weak positive association (r = 0.034) which is not significant at 5% level of significance (p = 0.757, p>0.05). Self-Monitoring explains about 0.1% of the total variations in self-esteem among the students. A simple regressions models with Self-Esteem as the DV and Self-Monitoring as the IV confirms this (see table 3). The model is also not significant at 5% level of significance (F (1, 84) = 0.096, p = 0.757, p>0.05). Table 3: ANOVA Model Sum of Squares Df Mean Square F Sig. Regression 32.239 1 32.239 .096 .757 Residual 28139.854 84 334.998 Total 28172.093 85 Predictors: (Constant), Self-Monitoring. Dependent Variable: Self-Esteem Table 4: Coefficients Un-standardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta (Constant) 80.257 4.839 16.585 .000 Self-Monitoring .029 .092 .034 .310 .757 Dependent Variable: Self-Esteem The regression model (see table 4) shows that self-monitoring is not a significant contributor to self-esteem (p = 0.757, p>0.05). The regression model can be formulated as shown; SE = 80.257 + 0.029SM, where SE = self-esteem and SM = self-monitoring. This means that a unit increase in self-monitoring leads to 0.029 units increase in self-esteem although this contribution is not significant. To determine whether the two are the same for both sexes, t-test is used. However, the first test carried out is the normality test to determine whether parametric or non-parametric test is used. For self-esteem, the normality tests using Lilliefors Significance Correction shows that, the scores are not normally distributed (p = 0.000, p Read More