Printer Friendly

Explicit and implicit school satisfaction.

In recent years, positive psychology has become a research paradigm focused on positive human experiences, traits, and institutions (Seligman & Csikszentmihalyi, 2000). Subjective well-being in general, and more specifically life satisfaction, is an important construct embedded within this orientation, considering the number of important and positive outcomes associated with higher levels.

School is an important part of an adolescent's life, considering the large amount of time spent in this environment, and the sizeable amount of variance attributed to global satisfaction that stems from adolescents' experiences with their school (Baker, Dilly, Aupperlee, & Patil, 2003). Nevertheless, although researchers have consistently found that elevated school satisfaction contributes to a number of important psychological, psychosocial, and educational outcomes (e.g., Huebner & Gilman, 2006; Katja, Paivi, Marja-Terttu, & Pekka, 2002; Konu, Lintonen, & Rimpela, 2002; Liu & Tian, 2006), schools often rely on objective academic indicators (e.g., results from standardized tests, drop-out rates) to determine how students perceive their school experiences in China, rather than measuring these perceptions directly. The distinction between objective indicators and subjective perceptions is important, considering that the former captures only a small portion of variance attributed to students' perception of the overall quality of their school experiences (Gilman & Huebner, 2008; Gilman, Huebner, & Furlong, 2009).

Nevertheless, although conceptually important, potential concerns regarding the measurement of school satisfaction remain. For example, extant school satisfaction measures appropriate for school-aged youth are based on self-reported explicit perceptions, that is, conscious evaluative judgments of school. Recent evidence from social cognition literature illustrates that individuals also process information about themselves and their environment using implicit, that is, automatic or unconscious judgments (Fazio, 1990; Wilson, Lindsey, & Schooler, 2000). In Wilson et al.'s (2000) Dual Attitude Model, people had two different views of an event. The implicit attitude is practiced and automatic. When people lack the psychological energy or motivation to search for a proximate attitude, the implicit attitude is used as a substitute. When people have enough psychological energy or motivation to exhibit a proximate attitude, the explicit attitude will appear and affect people's behavioral response. Even if the explicit attitude is retrieved from one's memory, the implicit attitude will still affect behavioral responses that are not consciously controlled (e.g., nonverbal behaviors). So, we determined that there are two constructs in school satisfaction too: explicit satisfaction, which can be seen in self-reports, and implicit satisfaction from automatic or unconscious processes.

Kim (2004) applied the concept of implicit social cognition to global life satisfaction, and from findings obtained using the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) found that implicit life satisfaction was independent of the measure of explicit life satisfaction. This suggested that people's cognitive perceptions of their overall quality of life could be further reduced to two basic components. Similar findings were noted by Zheng and Geng (2006).

None of these implicit studies have been extended to adolescents, nor were they based on specific well-being domains. Given that school satisfaction reflects one's attitude towards one's school life, the construct is an important component of subjective well-being (SWB) for adolescents across many nations (Gilman et al., 2008). Thus, it is important to explore whether perceptions of school satisfaction include both explicit and implicit components. That is, to what degree do conscious cognitive appraisals about the quality of school experiences match unconscious or automatic appraisals? When the real construct is found and the relationship between different constructs on an adolescent's school satisfaction is understood, the measurement of school satisfaction will be more comprehensive. This will promote further research on adolescents' SWB.

METHOD

PARTICIPANTS

A total of 124 students from a senior high school in Guangzhou city participated in this study. There were 66 from 10th-grade and 58 from 11th-grade. Females comprised 54% of the sample. The average age was 17.45 (SD = 0.91).

INSTRUMENTS

Explicit measure of school satisfaction The School Satisfaction Subscale (SSS) of the Adolescent's School Well-being Scale (Tian, 2008) consists of 36 items aimed at assessing six different dimensions of school experiences. Students are asked to rate each item on a 6-point scale, ranging from 1 (strongly disagree) to 6 (strongly agree). Internal consistency has been estimated at .94 for the general (i.e., overall) score and between .80 and .87 for the domain scores in this study.

Implicit measure of school satisfaction The Single Category Implicit Association Test (SC-IAT; Karpinski & Steinman, 2006) was based on the IAT (Greenwald et al., 1998) and involved students responding to a series of adjectives and nouns describing school experiences. Using a separate sample of 120 students from grades 10 to 12 in senior high school, students were asked to provide attributes (using either adjectives or nouns) that expressed their feelings about their school life. Results yielded 50 positive (good) attribute words and 57 negative (bad) attribute words. There were 19 active words that were mentioned by more than 50% of students, while 14 negative words were mentioned by more than 50% of students. The researcher amalgamated some words with similar meanings. For example, "merry", "happy", and "amused" were combined to form the general label of "amused". The final attribute words list consisted of 16 adjectives (8 positive and 8 negative).

Results yielded 87 category words. In order to match the numbers of attribute words, the eight most commonly mentioned from the positive and negative lists were selected. These words were mentioned by 63% to 90% of students. The SCIAT stimuli examples are found in Table 1.

PROCEDURE

The SSS was administered to the students in classrooms and was completed in one session. Each student's gender and grade were collected at the same time as the survey.

For the SC-IAT, which was computer administered, the experiment was described to the participants as a study on association and reaction time. Participants were asked to categorize the words presented on the center of computer screen as quickly and accurately as possible by pressing one of two labeled keys. All participants completed two stages, with two separate blocks comprising each stage. Each stage consisted of 24 practice trials (blocks 1 and 3) immediately followed by 72 test trials (blocks 2 and 4). In the first stage (bad + school life), participants were asked to sort the attribute words (good, bad) and category words (school life). For the bad or school life category they pressed the "I" key, and for the good category they pressed the "E" key. In the second stage (good + school life), participants were asked to sort the attribute words (good, bad) and the category words (school life). For the good or school life category they pressed the "E" key, and for the bad category they pressed the "I" key.

To avoid order bias, half of the participants first completed the SSS, followed by the SC-IAT three days later, while the other half completed the SC-IAT first and the SSS three days later.

DATA ANALYSIS

Using the D-score algorithm developed by Greenwald, Nosek, and Banaji (2003), participants with an error rate of more than 20% on the SC-IAT were excluded from analysis. The 24 practice trials in each stage were discarded. Responses under 350ms were eliminated, and error responses were replaced with the block mean plus an error penalty of 400ms. The average response times of block 2 (bad-school life) were subtracted from the average response times of block 4 (good-school life). This quantity was divided by the standard deviation of all correct response times within blocks 2 and 4, to gain the final D-score. If a single-sample t test shows that the average D-score differs from 0, then the implicit effect of school satisfaction exists. One participant was eliminated because s/he had a mistake percentage of over 20%. In the end, 124 participants contributed valid measures.

RESULTS

EXPLICIT SCHOOL SATISFACTION

Gender and grade effects on explicit school satisfaction To explore the effects of demographic variables for adolescents' school lives, a multivariate analysis of variance (MANOVA) was conducted for gender and grade across the SSS domains. The results showed there was no significant interaction effect: Pillai's Trace = 0.06, F(1, 120) = 1.20, p > 0.05, and the multivariate effect size ([[eta].sup.2]) was 0.06. However, there were significant main effects on gender and grade. For gender, Pillai's Trace = 0.15, F(1, 120) = 3.48, p < 0.01, [[eta].sup.2] = 0.15. For grade, Pillai's Trace = 0.12, F(1, 120) = 2.57, p < 0.05, [[eta].sup.2] = 0.12. Further, a univariate test showed that there was a significant gender effect in the domain of lesson study. Male students reported higher satisfaction than female students ([M.sub.male] = 4.03, [M.sub.female] 3.68 = [M.sub.mean different] = 0.35, p < 0.05, [[eta].sup.2] = 0.04). There were significant differences among different grades in the domains of achievement, school management, teacher-student relationships, and peer relationships. Students in grade 1 reported higher satisfaction than those in grade 2.

IMPLICIT SCHOOL SATISFACTION

Reliability of the SC-IAT and D Score To determine the reliability of the SC-IAT, we used the approach Karpinski and Steinman (2006) developed. We divided each SC-IAT into three parts (blocks of 24 test trials) and calculated a SC-IAT score separately for each part of the trials without dividing by the standard deviation of correct response times. A measure of internal consistency was obtained by calculating the average intercorrelation among these scores. Dividing the task into three parts or halves underestimates the reliability of the entire measure. The Spearman-Brown correction can be applied to compensate for this underestimate of the true internal consistency for the entire measure (designated adjusted r; Nunnally, 1978). The internal consistency correlations have been adjusted using the Spearman-Brown correction. These adjusted reliability coefficients are conceptually equivalent and directly comparable to the Cronbach's alphas computed for explicit measures. The adjusted reliability coefficient was .67 and the D-Score (i.e., the implicit school satisfaction effect) was .25 (SD = 0.34). A single-sample t test indicated that as the average D-score differed from 0, therefore an implicit effect of school satisfaction existed.

Gender and grade effects on implicit school satisfaction A univariate analysis of variance was conducted for gender and grade on implicit school satisfaction (i.e., the D-Score). The results showed there were no significant interaction and main effects: for gender x grade, F(1, 120) = 0.30, p > 0.05, [[eta].sup.2] = 0.00, for gender, F(1, 120) = 0.95, p > 0.05, [[eta].sup.2] = 0.01 and for grade, F(1, 120) = 3.18, p > 0.05, [[eta].sup.2] = 0.03.

Correlations between explicit and implicit school satisfaction Pearson correlations between explicit and implicit school satisfaction are shown in Table 3. Each correlation coefficient for implicit school satisfaction with the domains of explicit school satisfaction is close to 0, and none of the correlations are significant. The results showed that participants' explicit and implicit school satisfactions are two relatively independent structures.

DISCUSSION

The internal consistency reliability for the implicit school satisfaction test was acceptable in this study, and it was close to the numerical value of the indicator for the results of Karpinski and Steinman's (2006) SC-IAT research, although it was lower than the numerical value of indicator on Kim's (2004) implicit life satisfaction test. Owing to the lack of implicit studies of well-being, further evidence is required to validate our findings. However, in the present research we showed primarily that the SC-IAT is feasible for research on satisfaction and well-being in specific life domains. We found that students tended to associate school life with positive words and their implicit cognitions regarding school life were also positive. The results validate the use of the SC-IAT to measure participants' implicit cognitions regarding their school life in their unconsciousness.

We found that gender and grade significantly influenced explicit school satisfaction, but not implicit school satisfaction, for senior high school students. The correlation between explicit and implicit school satisfaction was very low. This result was consistent with the result of Kim's (2004) explicit and implicit life satisfaction study and the concept of implicit cognition proposed by Greenwald, and also the findings of Zheng and Geng (2006) that subjective well-being included dual constructs. For example, in the research on social information automatization conducted by Bargh (1996), it was considered that any kind of psychological process was the combination of controllability and automatism process. The cognition-experience theory put forward by Epstein (1994) divides the human information process into two types: rational, involving running on a conscious level characterized by the impetus of responsibility, the media of language, and the characteristics of deep consideration; and automatic, involving running on an unconscious level characterized by the impetus of sensibilities and the combination of integration, swiftness, and high-effectiveness in information processing. Rational systems operate mainly in explicit assessment, and experience systems operate mainly in implicit assessment (Epstein, 1994). In the implicit measure, as participants lacked the time and energy to search using the explicit attitude, they showed more implicit school satisfaction. In the self-reported scale measure, participants had rich cognitive resources to search using their explicit attitude, and the implicit component was suppressed. The separation between the two kinds of test results showed that explicit and implicit school satisfaction were independent constructs.

There are several theories about explicit versus implicit cognition, in some of which it is argued that the rational and automatic processes are apart in the dual-process model (Wilson et al., 2000), while in others it is argued that the two processes are in one continuum (Cunningham, Zelazo, Packer, & Van Bavel, 2007). The basic difference is considered to be that the automatic processes run by the unconscious mind require much less information and take less time than the rational processes run by the conscious mind. According to this viewpoint, two main factors should be considered that may influence the correlation effect between explicit and implicit test results in an attitude study.

One factor is the complexity and extent of the context information on the attitude target in a study. If the context information is simple and compact, the correlation between explicit and implicit test results on the attitude target will be significant, because the information involved in the rational process is that involved in the automatic process, and is therefore common and general. For instance, if a study was carried out investigating the participants' attitudes toward cockroaches in both explicit and implicit tests, the results would be identical regardless of how long participants spend completing their cognitive processing. In reality almost all the subjects of interest to scholars involve morals, values, emotions, socialization, experiences, and other such meanings so that the attitude target is associated with the amount of diverse information stored in people's memories and retrieved when necessary. When people confront this type of subject in the rational process, with the diverse information involved, the attitude may be different that used in the automatic process, which depends on the types of information.

Because of the diversity of the types of information, the attitude cannot be measured in terms of an approximate trend for participants in a test. Since most theorists have acknowledged that the automatic process involves little information, the correlation between explicit and implicit tests is unlikely to be high unless the main part of the content, proportion, processing mode, category, and other important characteristics of information in the rational process share some comparability, according to the theories in which it is proposed that the two processes are in one continuum. The counterpart demand that the attitude influenced by diverse information is similar to that produced by the unconscious mind, according to the dual process model, is far more difficult to fulfill.

However, the above theories do not mean that there is any consistency among individuals' rational processes. Some variables are open to interpretation regarding the dependent variables in the explicit text, which can involve very limited comparability of information.

DOI 10.2224/sbp.2010.38.10.1345

REFERENCES

Baker, J. A., Dilly, L. J., Aupperlee, J. L., & Patil, S. A. (2003). The developmental context of school satisfaction: Schools as psychologically healthy environments. School Psychology Quarterly, 18(2), 206-221.

Bargh, J. A. (1996). Automaticity in social psychology. In E. T. Higgins & A. W. Kruglanski (Eds.), Social psychology: Handbook of basic principles (pp. 169-183). New York: Guilford Press.

Cunningham, W. A., Zelazo, P. D., Packer, D. J., & Van Bavel, J. J. (2007). The iterative reprocessing model: A multilevel framework for attitudes and evaluation. Social Cognition, 25(5), 736-760.

Epstein, S. (1994). Integration of the cognitive and the psychodynamic unconscious. American Psychologist, 49(8), 709-724.

Fazio, R. H. (1990). Multiple processes by which attitudes guide behavior: The MODE model as an integrative framework. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 23, pp. 75-109). San Diego, CA: Academic Press.

Gilman, R., & Huebner, E. S. (2008). Positive schooling. In S. J. Lopez (Ed.), Positive psychology: Exploring the best in people (Vol. 4, pp. 87-98). Westport, CT: Greenwood Publishing Group.

Gilman, R., Huebner, E. S., & Furlong, M. J. (Eds.). (2009). Handbook of positive psychology in schools. New York: Routledge.

Gilman R., Huebner, E. S., Tian, L., Park, N., O'Byrne, J., Schiff, M., et al. (2008). Cross-national adolescent multidimensional life satisfaction reports: Analyses of mean scores and response style differences. Journal of Youth and Adolescence, 37(2), 142-154.

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: The Implicit Association Test. Journal of Personality and Social Psychology, 74(6), 1464-1480.

Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the Implicit Association Test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85(2), 197-216.

Huebner, E. S., & Gilman, R. (2006). Students who like and dislike school. Applied Research in Quality of Life, 1(2), 139-150.

Karpinski, A., & Steinman, R. B. (2006). The Single Category Implicit Association Test as a measure of implicit social cognition. Journal of Personality and Social Psychology, 91(1), 16-32.

Katja, R., Paivi E. K., Marja-Terttu, T., & Pekka, L. (2002). Relationships among adolescent subjective well-being, health behavior, and school satisfaction. Journal of School Health, 72(6), 243-249.

Kim, D. Y. (2004). The Implicit Life Satisfaction Measure. Asian Journal of Social Psychology, 7(3), 236-262.

Konu, A. I., Lintonen, T. P., & Rimpela, M. K. (2002). Factors associated with school children's general subjective well-being. Health Education Research, 7(2), 155-165.

Liu, W., & Tian, L. L. (2006). Relationship between quality of school life and life satisfaction in junior high school students [In Chinese]. Chinese Journal of Clinical Rehabilitation, 10(2), 65-67.

Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill.

Seligman, M. E., & Csikszentmihalyi, M. (2000). Positive psychology: An introduction. American Psychologist, 55(1), 5-14.

Tian, L. L. (2008). Development of the Adolescents' School Well-being Scale [In Chinese]. Psychological Development and Education, 24(3), 100-106.

Wilson, T. D., Lindsey, S., & Schooler, T. Y. (2000). A model of dual attitudes. Psychological Review, 107(1), 101-126.

Zheng, Q. Q., & Geng, X. W. (2006). A study on the predictive validity of self-concept for subjective well-being with the approach of implicit social cognition [In Chinese]. Psychological Science, 29(3), 558-562.

LI LI TIAN

South China Normal University, Guangzhou, People's Republic of China

WANG LIU

Shaanxi Normal University, Xi'an, People's Republic of China

RICH GILMAN

University of Cincinnati Medical School, Cincinnati, OH, USA

Li li Tian, PhD, Associate Professor, Department of Psychology, South China Normal University, Guangzhou, People's Republic of China; Wang Liu, Department of Psychology, Shaanxi Normal University, Xi'an, People's Republic of China; Rich Gilman, Department of Pediatrics, University of Cincinnati Medical School, Cincinnati, OH, USA.

This research was funded by the Fundamental Research Funds for the central universities (China) (O9SZZD10).

Appreciation is due to reviewers including: Begumhan Yuksel, Akdeniz University, Egitim Fakultesi, Dumlupinar Bulvari 07058, Kampus Antalya, Turkey, Email: begumhanyuksel@gmail.com

Please address correspondence and reprint requests to: Li li Tian, Department of Psychology, South China Normal University, Shipai, Guangzhou 510631, People's Republic of China. Phone: 00-86020-3195-1253; Fax: 00-86-020-8521-6033; Email: tlllw@yahoo.com.cn
TABLE 1
SC-IAT STIMULI EXAMPLES

Category            Attribute
school life
              good          bad

teacher       excited       depressed
classmate     comfortable   angry
playground    happy         bored
schoolwork    nice          painful
classroom     comfy         distracted
examination   confident     helpless
lesson        amused        blue
campus        substantial   nervous

Table 2
IMPLICIT SCHOOL SATISFACTION MEASURE

Block     Trials   Task and function            E-key response

Stage 1
1         24       Initial combined practice    Good
2         72       Initial combined test        Good

Stage 2
3         24       Reversed combined practice   Good + school life
4         72       Reversed combined test       Good + school life

Block     I-key response

Stage 1
1         Bad + school life
2         Bad + school life

Stage 2
3         Bad
4         Bad

Note: N = 124

TABLE 3
PEARSON CORRELATIONS BETWEEN EXPLICIT
AND IMPLICIT SCHOOL SATISFACTION

           Achievement         School        Teacher-student
                             management       relationships

SC-IAT        0.131             0.045             0.109

              Peer           Quality of        Quality of
          relationships       teaching        lesson study

SC-IAT        0.088             0.013            -0.002

Note: N = 124
COPYRIGHT 2010 Scientific Journal Publishers, Ltd.
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2010 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Tian, Li li; Liu, Wang; Gilman, Rich
Publication:Social Behavior and Personality: An International Journal
Article Type:Report
Geographic Code:9CHIN
Date:Nov 1, 2010
Words:3462
Previous Article:The actor-observer effect as a function of performance outcome and nationality of other.
Next Article:The value of peace: subjective importance and perceived self-efficacy in promoting pacific cohabitation.
Topics:

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters