ACADEMIC SELF-HANDICAPPING AND THEIR CORRELATES IN ADOLESCENCE

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Bulletin of the Transilvania University of Braşov Vol. 4 (53) No. 2-2011 Series VII: Social Sciences Law ACADEMIC SELF-HANDICAPPING AND THEIR CORRELATES IN ADOLESCENCE Elena COCORADĂ 1 Abstract: The self-handicapping has been examined as a self-protective strategy, used by adults and young, males and females, in different situations assessed as threatening for the positive self-esteem. The purpose of this study is to explore the relations between self-handicapping and some variables relevant in the academic field as learning motivation, academic results, selfesteem. Age and gender are the criteria of our analysis. The results suggest the males and later adolescents (males and females) self-handicap more that the females and the young adolescents. Self-esteem and some components of learning motivation are the variables that influence self-handicapping at significant levels. Key words: self-handicapping, learning motivation, adolescents. 1. Introduction Self-handicaps are obstacles created or claimed by the individual in anticipation of a failure and can influence their performance and mood [1]. Selfhandicapping offers the opportunity to protect the persons fragile image, to externalize failure and internalize success. Often, the barrier is evaluated as external, but sometimes, it is evaluated as internal to the self-handicappers, excluding their competencies and abilities [4], [1]. Past studies examined self-handicapping as a motivational strategy used by adults and young adolescents [22], [16]. Selfhandicapping is conceptualized as a defensive strategy, similar to rationalization. The individual builds an excuse for a potential failure, but the built defence sometimes affects performance, because it reduces the effort necessary to obtain success [20]. Numerous studies that examined gender differences found inconsistent results: they found that males and females were equally likely to claim a handicap [15], while others found effects only for males [1], [10-11], [18]. The recent researches suggest that both women and men self-handicap in different situations [8], [10]. Concerning the age, the results have proven the tendency of older girls to score higher on self-handicapping than younger girls did [8]. The negative correlations between self-handicapping and self concept clarity, self-oriented perfectionism and higher self-esteem have been identified [3], [14], [16]. Positive correlations have been detected between 1 Faculty of Psychology and Educational Sciences, Transilvania University of Braşov.

58 Bulletin of the Transilvania University of Braşov. Series VII Vol. 4 (53) No. 2-2011 self-handicapping and: procrastination [4], depressed mood in adolescents [7], lower levels of obtained results satisfaction, higher levels of anxiety [20], lower academic self-efficacy [6]. Other studies highlight the predictors of selfhandicapping as low self-esteem, performance goal orientation [5], [12], self-concept clarity, low learning selfregulation, superficial learning strategies [19], and defensive pessimism [13]. In the academic context, there have been investigated the relationships between goals achievement, and performance, coping and self-handicapping [16], [18], [22]. Self-handicapping is negatively associated in-depth learning and selfregulated learning. As far as the exam performance is concerned, the results have inconsistent findings [19]. The very recent researches have explored the students samples with greater selfhandicapping tendencies reported to motivational factors, including achievement of goals on cognitive engagement and academic achievement, more superficial learning strategies [6], [12]. The results showed that masteryavoidance and performance-avoidance goals partially mediated the relationship between fear of failure and selfhandicapping [2]. A performance goal orientation is a positive predictor of selfhandicapping depending on the school level. In upper elementary and junior high schools, the association between achievement in mathematics and selfhandicapping was mediated by performance goals. In senior high school, only task goal orientation was a predictor of self-handicapping [12]. In the academic field, the studies have examined the relationship between self-handicapping and various variables within the context of mathematics, physical education, writing, science, other courses [2], [6], [12-13]. 2. Method 2.1. Research objectives and hypothesis The purpose of this study is to explore the relations between self-reported handicapping and several variables relevant in the academic field. We investigated the association between the tendency to self-handicapping and the levels and components of learning motivation (self-efficacy, controllability, cognitive engagement, and perception of the learning value), self-esteem, and academic results. Age and gender are the criteria of our analysis. 2.2. Participants Participants were 232 adolescents (males and females), aged from 15 to 25 years old (m = 18.84, σ = 2.57). All participants learn in the high schools and faculties of Braşov County, Romania. There are 90 participants older than 18, and 132 females. 2.3. Procedure All instruments have been administered during the classes, after having obtained the informed consent from the participants. All data were collected via paper and pencil. The students were not remunerated for their participation in the research. 2.4. Measures The Self-handicapping Scale in Academic Field (SHSAF), developed by us, measures the tendency to claim/ selfreport self-handicapping in different learning situations (8 items) and in general situations (6 items). For each item, the students are invited to indicate their option on a 5-point Likert scale, ranging from 1 (Disagree very much) to 5 (Agree very

COCORADĂ, E.: Academic self-handicapping and their correlates in adolescence 59 much). Higher scores indicate higher selfhandicapping. Alpha Cronbach for the scale is 0.81. Item example: Before a test, semester paper or exam, I tell my colleagues that I feel tired, in order to excuse a potential failure. The Learning Motivation Inventory (LMI) is developed by a team of authors for the diagnosis of four dimensions: controllability, cognitive engagement, selfefficacy, and perception of the learning value. The LMI has 39 items and uses the model of Viau [21]. For each item, the students are invited to indicate their option on a 5-point Likert scale, ranging from 1 (Disagree very much) to 5 (Agree very much). Higher scores indicate the strongest learning motivation. Alpha Cronbach for entire tool is.81; for the enumerated dimensions, the intern consistency has the following coefficients:.81 (perception of learning value);.79 (self-efficacy);.80 (controllability); and.82 (cognitive engagement) [17]. Items examples: A) I am sure that I can complete the tasks at the indicated deadline. B) Many of the low marks of the students are due to bad luck. The Rosenberg Self-Esteem Scale - RSE (Rosenberg, 1965) is the knowing scale designed to measure global feelings of self-worth and self-acceptance. We have used the short variant with 10 items scored on a 5 point response, on which 5 is strongly agree and 1- strongly disagree. The higher scores indicate higher selfesteem. For the RSE, we found in the present study an Alpha Cronbach equal to 0.86. School performance has been measured by the overall average obtained by pupils and students, on a scale from 1 to 10. 3. Findings The descriptive statistics and the t Test for gender and age, only for the variables with significant differences are presented in Table 1. Effect sizes enrich the data. Variable G Mean Std. Dev. t Sig. t Test for gender and age groups Table 1 Cohen d Age Mean Marks M 7.82 1.15 <18 8.55.62 5.22.001 0.75 medium F 8.51.62 >18 7.95 1.06 Learning M 96.61 18.82 <18 134.85 15.77 motivationtotal F 124.10 22.99 >18 93.45 13.21 9.50.001 1.30 Self- M 38.02 7.21 <18 29.43 5.77 6.05.001 0.81 handicapped F 32.20 7.08 >18 39.15 6.08 M 33.24 4.26 <18 38.39 6.07 Self-esteem 4.92.001 0.63 F 36.63 6.19 >18 32.44 3.56 M 34.27 6.11 <18 37.21 5.26 Self-efficacy 3.91.001 0.53 F 37.28 5.03 >18 35.09 5.84 M 32.62 4.75 <18 34.34 4.48 Controllability 2.63.009 0.35 F 34.27 4.56 >18 32.97 4.81 Cognitive M 25.19 5.02 <18 31.92 5.08 7.36.001 1.00 engagement F 30.42 5.41 >18 25.09 4.30 Learning M 31.72 6.05 <18 31.64 6.57 value 3.845.001 0.41 perception F 34.29 6,35 >18 27.85 6.35 Note: G = Gender, M = Male, F = Female, 18 (age) = 18 year Std. Dev. t Sig. Cohen d 12.46.000 0.69 21.72.000 2.84 12.46.000 1.63 9.17.000 1.19 2.88.004 0.38 2.24.026 0.32 10.94.000 1.45 6.07.001 0.58

60 Bulletin of the Transilvania University of Braşov. Series VII Vol. 4 (53) No. 2-2011 Bivariate correlations were conducted in the entire sample for each variable, but we present only the significant correlations in Table 2. Significant correlations between variables Table 2 Spearman's Bravais-Pearson s r Coefficients rho Variables (2) (3) (4) (5) (6) (7 (8) (9) Self-handicapping (1) -.278** -.711** -.453** -.390** -.331** -.530** -.419** - Marks (2).382**.254**.292**.203**.303** -.061 - Learning motivation (3).560**.607**.462**.825**.744** -.229** Self-esteem (4).307**.232**.419**.088 - Self-efficacy (5).389**.554**.415** - Controllability (6).276**.227* - Cognitive engagement (7).251** -.159* Perception of value of learning (8) - -.225* Year of study (9) - *p <.05, **p <.01. Several hierarchical regressions with self-handicapping as a dependent variable were conducted (Table 3 and Table 4). The basic assumptions of regression were confirmed: it is a minimum of 20 cases for each independent variable used, the psychometric qualities of tools are acceptable, and the Kolmogorov-Smirnov test shows the normality of distributions for more variables. For the Academic results, Self-esteem and Cognitive engagement, we have applied the log transformation of data. The coefficient correlation between the independent variables used in regression is not higher than.50. Also, in regression there is not a multi-collinear problem. We have not used the scores of overall learning motivation in hierarchical regression, but the scores of their components: Cognitive engagement Self-efficacy, Controllability, and Perception of the value of learning. We preferred to use motivation subscales in order to explore the separate effects of the variables. Hierarchical regression for the entire sample Table 3 R 2 F change Sig. β Model 1.130 12.53.001 Gender.043 Age.098 Academic results log -.128 Self-esteem log -.322** Model 2.380 10.6.001 Gender.12 Age.01 Academic results log -.016 Self-esteem log -.163 Self-efficacy -.319** Cognitive engagement -.080 log Controlla bility -.094 Perception of value of --.247** learning * p <.05, ** p <.01.

COCORADĂ, E.: Academic self-handicapping and their correlates in adolescence 61 Overall results concerning selfhandicapping with women and men Table 4 Models R 2 F Change Sig. β Females sample Model 3.112 3.95.01 Age.091 Marks -.092 Self-esteem -.311** Model 4.375 9.48.001 Age.009 Marks -.013 Self-esteem -.143 Self-efficacy -.279** Controllability -.123 Cognitive -.106 engagement Perception of -.249** value of learning Males sample Model 1.075 3.06.083 Age.205* Marks/grades -.181 * p <.05, ** p <.01. 4. Discussion The present study has examined the relations between self-handicapping and several demographic and personality variables, and academic performance in early and late adolescence. Our findings confirm the results obtained by other researches: a) males and females were equally likely to claim a handicap; b) males self-handicap more than females; c) later adolescents self-handicap more that the younger. The personality variables, such as self-esteem can be a significant criterion for self-reported handicapping. In our research, the academic results do not constitute a significant variable in explaining self-handicapping, neither for the whole sample, nor for the group of males and females. The t Test for gender shows that the scores obtained by women are significantly lower with self-handicapping than those obtained by men, thus confirming most of the previous researches. The scores for the rest of the relevant variables, on the other hand, are significantly higher for women as compared to men. Similarly to the females group, act the participants younger than 18 (early adolescents). Exploring the Cohen s d for the gender and age differences, we can conclude that perhaps the difference between the groups is conspicuous, clearly concerning the Selfhandicapped, Learning motivation and Cognitive engagement; for other variables, the effect size is medium or small. The previous analysis has been completed by a more punctilious one, which shows that age induces differences in the female sample. Thus, female students (women older than 18) register lower scores with learning motivation (t = 16.16; p =.001) have a lower selfesteem (t = 7.27; p =.001), the cognitive engagement is lower (t = 7.38; p =.001) and school results are poorer (t = 2.57; p =.01) than in the case of high-school students (younger than 18). Female students self-handicap more than highschool students. These results confirmed the previous findings [8]. Similar tendencies are met in the male group as well. Males older than 18 self-handicap more as compared to the high-school students (t = 5.98; p =.001), but have a lower learning motivation, (t = 8.25; p =.001), lower self-esteem (t = 4.48; p =.001), and a lower cognitive engagement in school tasks (t = 3.46; p =.001). Although male participants older than 18 (late adolescents) register lower academic results as compared to highschool students, the difference in the male subsample is not statistically significant, as in the case of the girls subsample. Selfhandicapping correlates positively, at the

62 Bulletin of the Transilvania University of Braşov. Series VII Vol. 4 (53) No. 2-2011 significant levels, with the participants age and years of study and correlates negatively with the academic performances as is the case in other studies [16], [18]. We have identified the significant negative correlations of claimed Self-handicapping with learning motivation and its components (self-efficacy, controllability, cognitive engagement, and perception of learning value). Although the values of r are low or medium, they are strongly significant (p>.001). As an exception, the association between self-handicapping and learning motivation is negative and strong (r =.771). The analysis of the regression equations, with self-handicap as a dependent variables, has been done for the whole sample, and separately considering the gender variable. Self-esteem becomes a highly significant criterion for the whole sample, when keeping gender and age constant (model number 1), with a negative beta coefficient (model number 1). The second model is the best, and it is significantly different from the first (F change = 10.60, sig. =.001). In this model, we have added the four components of learning motivation. This model has R 2 of 0.38. Two of the four added variables are negatively involved in explaining selfhandicapping, self-efficacy and perception of learning value (Table 4). In other words, if the participants have the same age, gender and level of self-esteem, the strongest influence is given by the level of self-efficacy in learning (β = -.319), followed by the perception on the value of learning (β = -.247). Separately analysing the effect of the independent variables on self-handicapping, we come to the conclusion that in the column <correlations/part>, 9% of the dispersion of the self-handicapping strategy is explained by self-esteem. When self-esteem is constant, the perception on the value of learning explains more than 4% of the dispersion while self-efficacy in learning explains 3.8 of it. Concerning the gender (Table 4), we present first the hierarchical regression in the female sample. The predictors used and their R 2 of each model are: a) age (model 1 with R 2 =.007%); b) Academic results (model 2 with R 2 =.017); c) Cognitive engagement, self-esteem (model 3, with R 2 =.112); d) self-efficacy, learning value perception and controllability (Model 4, with R 2 =.375). Models 3 and 4, presented in Table 4, explain self-handicapping to a significant extent. In the 3 rd model, self esteem negatively and significantly influences self-handicapping (β = -.311, t = 3.19, sig. =.002). The good model is 4, whose 2 personality variables selfefficacy and perception of learning value are an important and negative criterion for self-handicapping. A similar hierarchical regression runs in the male sample. We have used the same predictors: a) age, academic results (model 1 with R 2 =.075); b) self-esteem, cognitive engagement, controllability, self-efficacy and learning value perception (model 2) (β = -.247). Of these, only model 1 (Table 3) explains selfhandicapping to a slight extent. In this model, age directly influences selfhandicapping (β = -.247). In the case of male students, unlike in that of female students, the personality variables do not contribute decisively to explaining selfhandicapping, age being the only relevant variable. Our findings suggest that men and women use self-reported handicaps, but men are more likely to report self-handicap than women. According to other studies, the difference in values of learning can be an explanation for gender differences in self-handicapping [8-9], [18]. These results suggest that gender may have a moderating effect between self-

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