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Implicit theories of intelligence and academic locus of control as predictors of studying behaviour
Learning and Individual Differences 27 (2013) 163–166
Contents lists available at ScienceDirect
Learning and Individual Differences journal homepage: www.elsevier.com/locate/lindif
Implicit theories of intelligence and academic locus of control as predictors of studying behaviour Kate Bodill, Lynne D. Roberts ⁎ Curtin Health Innovation Research Institute, Curtin University, Australia
a r t i c l e
i n f o
Article history: Received 24 September 2011 Received in revised form 2 July 2012 Accepted 28 August 2013 Keywords: Dweck Locus of control Implicit theories of intelligence Academic effort University students
a b s t r a c t Dweck's social-cognitive approach to implicit theories of intelligence posits that entity beliefs and incremental beliefs are associated with, and precede the development of, external and internal locus of control respectively. To date, this proposition underlying the theory has not been adequately tested. An online questionnaire including measures of implicit intelligence beliefs, academic locus of control and hours studying per week was completed by 94 Australian university students. Multiple regression analysis supported the posited relationship between entity beliefs and external locus of control, but not that between incremental beliefs and internal locus of control. While providing partial support for Dweck's proposition, further longitudinal testing is required to determine causal ordering. A second multiple regression indicated that academic locus of control was a significant predictor of hours studying per week, but implicit theories of intelligence were not, suggesting that locus of control beliefs are the more appropriate target of efforts at improving academic effort. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Individuals have their own ‘lay’ or implicit theories about psychological concepts such as intelligence that influence the way people view themselves and others (Heider, 1958), providing a framework when attempting to explain human actions (Dweck, Chiu, & Hong, 1995). However, because theories are often hidden or poorly articulated, it is sometimes difficult to identify the effect they have on different life domains (Dweck et al., 1995). A dominant social-cognitive approach to the study of implicit theories of intelligence is that developed by Dweck and colleagues (Dweck, 1986, 1999; Dweck & Leggett, 1988; Dweck et al., 1995). This approach identified two types of implicit beliefs about intelligence: entity beliefs and incremental beliefs. People who endorse an entity theory of intelligence believe that intelligence is a fixed ability and tend to adopt performance goals with the aim of gaining approval from outsiders. They believe that if effort is required to achieve a goal, that this is indicative of limited ability and therefore seek challenges that are fairly easy and require less effort to ensure they can perform well in light of others (Dweck, 1999). Conversely, people who endorse an incremental theory of intelligence believe that intelligence is malleable and can be improved. They set mastery goals which require the learning of new skills in order to increase competence and seek challenging tasks based on the belief in effort (Dweck, 1999). ⁎ Corresponding author at: School of Psychology and Speech Pathology, Curtin Health Innovation Research Institute, Curtin University, GPO Box U1987, Perth, WA 6845, Australia. Tel.: +61 8 9266 7183; fax: +61 8 9266 2464. E-mail address: [email protected] (L.D. Roberts). 1041-6080/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.lindif.2013.08.001
Originally, Dweck and Leggett (1988) proposed that people believe in either an incremental theory of intelligence or an entity theory of intelligence and conceptualised the two sets of beliefs as belonging on opposite ends of a continuum. More recent research by Hong, Chui, Dweck, Lin, and Wan (1999) suggests that people can hold both entity and incremental beliefs simultaneously. Entity and incremental beliefs are moderately negatively correlated (r = −.35 to −.55; Abd-El-Fattah & Yates, 2006; Dupeyrat & Mariné, 2005) suggesting that they are separate, yet correlated constructs, rather than two ends of a continuum. In theorising about implicit theories of intelligence Dweck et al. (1995) posited that implicit beliefs about intelligence are associated with locus of control. Locus of control refers to whether an individual attributes events and outcomes to external or internal influences (Cooper, Burger, & Good, 1981). People with an internal locus of control believe that outcomes arise from effort and therefore view their actions to be influential over life outcomes (Cooper et al., 1981). Conversely, individuals with an external locus of control believe that the environment and situational factors are responsible for life outcomes and are likely to attribute success or failure to chance or unfavourable circumstances, rather than to lack of effort (Cooper et al., 1981). Locus of control can be measured across domains, or within specific domains to predict different social behaviours and psychological states, including academic task persistence (Trice, Ogden, Stevens, & Booth, 1987). Academic locus of control refers to an individual's perceived control over academic achievement, with internal academic locus of control indicating that the individual believes effort is a requirement for academic success (Trice et al., 1987). Dweck and Leggett (1988) posited that entity beliefs about intelligence are associated with external and incremental beliefs with internal locus of control.
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K. Bodill, L.D. Roberts / Learning and Individual Differences 27 (2013) 163–166
Dweck et al. (1995) further posited that implicit beliefs about intelligence precede the development of locus of control. While both relate to perceptions of control over important life domains (Dweck & Leggett, 1988) implicit beliefs relate to perceptions of control over intelligence, whereas locus of control relates to perceptions of control over events and outcomes. Dweck and Leggett (1988) posited that people who hold entity beliefs are likely to have trouble perceiving control over intelligence and therefore negative outcomes in associated areas (such as academic failure) are viewed to be out of their control, representing an external locus of control. Conversely, individuals who hold incremental beliefs about intelligence will view outcomes as under their control and interpret outcomes from an internal locus of control perspective. Contrary to this Graham (1995) suggested that the evidence is unclear as to whether control attributions are guided by implicit theories of intelligence, or if past experiences of academic failures promote the endorsement of an entity view. There is a dearth of published empirical research regarding the relationship between implicit theories of intelligence and locus of control. Only one published study could be located that has directly assessed the relationship between the two constructs, reporting a significant positive relationship between incremental beliefs and internal locus of control, but with neither correlation coefficient nor effect size reported (Dweck et al., 1995). The implicit theory measure used in this study consisted of three items reflecting entity statements only and as such does not provide an adequate test of the proposition that implicit theories of intelligence are associated with locus of control. Academic task persistence (effort) is a core domain of relevance to intelligence. According to Dweck and Leggett (1988) individuals who hold entity beliefs exert less effort to produce academic success and where they believe their intellectual ability is low, become helpless when faced with academic failures and consequently withdraw effort to save face. Conversely, individuals who endorse an incremental theory are concerned with the processes involved in mastering challenging tasks and may attribute unfavourable outcomes to poor strategy or lack of effort, rather than ability (Grant & Dweck, 2003). They are therefore more likely to persevere when faced with negative feedback (Dweck & Leggett, 1988). One study to date has reported that entity beliefs were significantly negatively correlated with effort (r = −.23), operationalised as the number of homework activities completed in the academic year (Dupeyrat & Mariné, 2005). Locus of control has also been associated with effort, with internal locus of control associated with greater effort. Based on a metaanalysis of 75 studies (Findley & Cooper, 1983) the effect size is small, suggesting that academic performance is multiply determined, with other variables also playing an important role. No study to date has attempted to examine whether Dweck's implicit theories of intelligence or academic locus of control can better predict effort within a university setting. 1.1. Current study The current study has two main aims. The first aim is to test Dweck and Leggett's (1988) theoretical proposition that implicit theories of intelligence and ALC are related, a proposition that has not been fully tested to date. Gender will be controlled for in this analysis as previous research suggests that females are more likely than males to hold entity beliefs of intelligence (Pepi, Faria, & Alesi, 2006) and internal locus of control (Cooper et al., 1981). It is hypothesised that incremental beliefs will be correlated with internal locus of control and entity beliefs with external locus of control. The second aim is to determine whether implicit theories of intelligence or academic locus of control are better predictors of academic effort, operationalised as the number of hours spent studying per week. The mode of study (full time or part time) will be controlled for as this is likely to affect the number of hours an individual would spend studying per week. If, as proposed by Dweck and Leggett (1988),
implicit theories of intelligence precede locus of control, then implicit theories of intelligence should be a distal predictor and locus of control a proximal predictor of study behaviour, with locus of control the stronger predictor of study behaviour. 2. Method 2.1. Participants A snowball sampling method through Facebook and inviting students on campus to participate in the research was utilised to recruit a convenience sample of 102 university students enrolled across a range of faculties at a Western Australian university. Eight cases were removed from the initial sample due to incomplete data (missing more than 10%), leaving 94 participants remaining in the sample for analysis. Participants were predominantly female (69.1%), full-time (87.2%) students with a mean age of 20.8 years (SD = 2.3 years). Prior to conducting the research, an a-priori power analysis was conducted. In order to detect a medium size effect, with a power of .80 at a significance level of .05, 91 participants were required. The final sample size of 94 participants meets this requirement. 2.2. Measures An online questionnaire was developed consisting of measures of implicit theories of intelligence, academic locus of control and single item measures of age, gender, faculty, study status (part-time or fulltime) and effort (hours spent studying per week). 2.2.1. Implicit Theory of Intelligence Scale (ITIS) The ITIS is a self-report measure comprising seven entity and seven incremental items representing beliefs about intelligence (Abd-ElFattah & Yates, 2006). Example items are “You are born with a fixed amount of intelligence” (entity subscale) and “Good preparation before performing a task is a way to develop your intelligence” (incremental scale). Participants were required to respond to the items according to a 4-point Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree). Previous research has suggested that the measure consists of two factors representing entity and incremental beliefs, both with acceptable reliability (Cronbach's alpha above .75) and demonstrating discriminant validity (r = −.35; Abd-El-Fattah & Yates, 2006). In the current sample, the internal reliability was adequate (Cronbach's alpha = .70 incremental and .65 entity). Scores on the entity and incremental subscales of the ITIS have a possible range from 7 to 28 with higher scores reflecting a stronger agreement with the statements on each of the subscales. 2.2.2. Academic Locus of Control Scale (ALCS) The ALCS is a 28 item true–false scale measuring perceptions of control over academic outcomes (Trice, 1985). Items were written to reflect Rotter's I–E scale within the specific domain of academic effort within college. Individual scores are calculated by summing the number of externally answered items and can range from 0 through to 28. Higher scores are indicative of a more external locus of control over academic outcomes. Example items are “What I learn is more determined by college and course requirement than by what I want to learn” and “Studying every day is important” (reverse coded). Higher scores convey external perceptions of control over academic outcomes, with lower scores conveying internal perceptions that academic success requires personal effort. Previous research suggests the ALCS has acceptable internal consistency (Cronbach's alpha = .70), good test–retest reliability over a five week interval (r = .92; Trice, 1985), is not associated with socially desirable responding, and has adequate construct validity with Rotter's I–E scale (r = .50, Trice, 1985). In the current sample the scale had acceptable reliability (Cronbach's alpha = .72).
K. Bodill, L.D. Roberts / Learning and Individual Differences 27 (2013) 163–166
2.3. Procedure Prior to commencing data collection, ethics approval was obtained. The online questionnaire was developed and hosted on SurveyMonkey.com. Two versions of the questionnaire were created, with the ITIS and ALCS counter-balanced to remove the influence of order effects. As an incentive for participation, entry into a prize draw for a $50 AUD iTunes gift voucher was offered. The questionnaire remained available for 50 days. After this time the survey was removed. A preliminary inspection of the data using Missing Values Analysis was conducted to determine the extent of missing data. Four missing data points were replaced using mean substitution. 3. Results and discussion Descriptive statistics and correlations between key variables are presented in Table 1. The proposed control variables for the analysis were gender and study mode. As gender was not significantly associated with the other variables it was dropped from further analyses. Mode of study was retained for the second regression analysis. The assumptions underlying multiple regression analysis were tested. Hours of study was transformed with a logarithm transformation due to its substantial positive skewness. Two univariate outliers were brought in closer to the distribution. A multiple regression analysis was utilised to test Dweck and Leggett's (1988) theoretical proposition that implicit theories of intelligence and academic locus of control are related. Total scores on the ‘entity’ and ‘incremental’ scales from the ITI scale were entered simultaneously into the multiple regression model as predictors with ALCS scores as the criterion variable. In combination, entity and incremental scores accounted for a significant 11.2% of the variance in ALCS scores, R2 = .112, adjusted R2 = .092, F (2, 91) = 5.72, p = .005 (small to medium effect size). The unstandardised (B) and standardised (β) regression coefficients, and squared semipartial correlations (sr2) for each predictor are presented in Table 2. Entity scores accounted for a significant 8.1% of unique variance in ALCS scores with incremental scores not accounting for any significant variance. A hierarchical multiple regression analysis with hours of study as the criterion variable was conducted to test whether implicit theories of intelligence or academic locus of control were better predictors of academic effort. The control variable, study mode, was entered in step 1 and accounted for a significant 7.8% of the variance in hours of study R2 = .078, F (1, 92) = 7.76, p = .006. Entity, incremental and ALCS scores were entered as predictors in step 2 and accounted for an additional 22.3% of variance in hours of study, Δ R2 = .223, Δ F (3, 89) = 9.47, p b .001. In combination the predictors were able to account for 30.1% of the variance in hours of study, R2 = .301, adjusted R2 = .269, F (4, 89) = 9.477, p b .001 (medium to large effect size). The unstandardised (B) and standardised (β) regression coefficients and squared semipartial correlations (sr2) for each predictor on each step of the hierarchical MRA are presented in Table 3. In the final model, Table 1 Correlation matrix of key variables. Variable
Mean
SD
1
1. 2. 3. 4. 5. 6.
16.51 21.94 13.68 1.01
3.20 2.91 4.10 0.34
−.30⁎⁎ .33⁎⁎
Entity Incremental ALCS Hours studya Study modeb Genderc
−.08 .06 .11
2
3
4
5
6
Table 2 Unstandardised (B) and standardised (β) regression coefficients and squared semipartial (or part) correlations (sr2) for each predictor in a multiple regression model predicting academic locus of control. Variable
B [95% CI]
β
sr2
Entity Incremental
.400 [.126, .674]⁎⁎ −.122 [−.423, .497]
.300 −.083
.081 .007
Note. N = 94. CI = confidence interval. ⁎⁎ p b .01.
study mode accounted for a significant 3.5% of the variance in hours spent studying per week with academic locus of control scores accounting for a further significant 18.2%. Entity and incremental scores did not account for significant variance in hours studying per week. The results from the first multiple regression analysis partially supported Dweck and Leggett's (1988) proposition that implicit theories of intelligence and locus of control are associated. Entity scores were significantly positively associated with academic locus of control scores, demonstrating the association between entity beliefs and an external academic locus of control. However, there was no support for the predicted association between incremental beliefs and an internal locus of control. As the current research utilised a cross sectional research design, the causal direction between the constructs was unable to be tested. Future longitudinal research is required to determine whether the development of implicit theories do in fact precede locus of control. The results of the second hierarchical multiple regression analysis suggest that while neither incremental nor entity beliefs are directly associated with academic effort, entity beliefs are associated with external academic locus of control, which in turn was found to be a significant predictor of hours studied per week. One possible reason for these findings is that academic locus of control measures are specifically designed to predict studying behaviour within the academic domain (Trice et al., 1987), whereas implicit theories of intelligence measures are based on the broader domain of intelligence. Another possible reason for the lack of association found between implicit theories of intelligence and hours spent studying is the use of a university student sample. University students have an average IQ above that of the general population and are generally highly motivated to perform well in order to produce academic success (Siegle, Rubenstein, Pollard, & Romey, 2010). Dweck and Leggett (1988) posited that individuals who endorse an entity theory of intelligence will only exert less effort if low intellectual ability is perceived. If university students believe that they are highly competent, holding an entity view of intelligence may neither facilitate nor hinder the amount of effort exerted in academic studies. It is possible that implicit beliefs act as moderators, rather than direct predictors, of studying behaviour. Further disentanglement of effort and ability when examining relationships between implicit theories, locus of control and academic outcomes is desirable. Overall, the results obtained suggest that academic locus of control is directly associated with studying behaviour in university students, Table 3 Unstandardised (B) and standardised (β) regression coefficients, and squared semipartial (or part) correlations (sr2) for each predictor on each step of the hierarchical MRA predicting hours of study. Variable
−.17 .16 −.12 −.11
Notes: N = 94. a Transformed variable. b Part-time coded as 0 and full-time coded as 1. c Male coded as 1 and female as = 0. ⁎⁎ Correlation significant at p b .01 (2-tailed). ⁎ Correlation significant at p b .05 (2-tailed).
−.49⁎⁎ −.20 .07
.24⁎ −.13
−.02
165
Step 1 Study mode Step 2 Study mode Entity Incremental ALCS
B [95% CI] .279 [.080, .478]⁎⁎ .195 [.012, .378]⁎ .006 [−.014, .027] .013 [−.009, .034] −.037 [−.052, −.022]⁎⁎
Note. N = 94. CI = confidence interval. ⁎⁎ p b .01. ⁎ p b .05.
sr2
β .279
.078
.195 .061 .112 −.467
.035 .003 .011 .182
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while entity beliefs are associated with academic locus of control but not directly related to studying behaviour. This requires further testing in longitudinal research. Given the restricted range of IQ within university students (Siegle et al., 2010) the results from the current study cannot be generalised to the wider population. Future research should be conducted on a wider population in order to determine whether the same findings emerge when the sample consists of a more diverse IQ range. The negative association found between external academic locus of control and academic effort is consistent with previous research (e.g., Onwuegbuzie & Daley, 1998; Trice, 1985; Trice et al., 1987) and has important implications within the academic domain. Previous research (e.g., Aronson, Fried, & Good, 2002; Blackwell & Trzesniewski, 2007) has indicated that it is possible to successfully induce people to believe in incremental beliefs, resulting in behaviour that is more driven and mastery oriented. However, our research suggests that in terms of changing study behaviour in university students, challenging implicit beliefs about intelligence may be important only to the extent that it results in increasing internal academic locus of control. If the aim is to increase academic effort, academic locus of control beliefs may be the more appropriate target. This provides support for the concept termed ‘attributional retraining’ which refers to the process of educating individuals to endorse an internal locus of control and to make unstable attributions, in order to improve motivation and enhance achievement striving (Perry, Hechter, Menec, & Weinberg, 1993). A limitation of the current study is that the criterion variable ‘studying behaviour’ was measured using a single item, self-report measurement of the approximate number of hours spent studying per week. Research indicates that time spent studying is a poor predictor of academic achievement (Plant, Ericsson, Hill, & Asberg, 2005) and is only a significant predictor of academic achievement when the study is undertaken under quiet conditions and previously attained performance and quality of study are taken into consideration. A more nuanced measure of effective studying behaviour conceptualising studying as a multidimensional construct (Plant et al., 2005) is required for future research in this area. In conclusion, the findings from the present study partially support Dweck and Leggett's (1988) proposition that implicit theories are associated with locus of control. Entity beliefs about intelligence were significantly positively associated with an external academic locus of control, while incremental beliefs were not significantly related to academic locus of control. However, only academic locus of control was a significant predictor of studying behaviour in university students.
References Abd-El-Fattah, S. M., & Yates, G. C. R. (2006). Implicit Theory of Intelligence Scale: Testing for factorial invariance and mean structure. Paper presented at the Australian Association for Research in Education Conference, Adelaide, South Australia. Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. Journal of Experimental Social Psychology, 38, 113–125. Blackwell, L. S., & Trzesniewski, K. H. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246–263. Cooper, H. M., Burger, J. M., & Good, T. L. (1981). Gender differences in the academic locus of control beliefs of young children. Journal of Personality and Social Psychology, 40, 562–572. Dupeyrat, C., & Mariné, C. (2005). Implicit theories of intelligence, goal orientation, cognitive engagement, and achievement: A test of Dweck's model with returning to school adults. Contemporary Educational Psychology, 30, 43–59. Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040–1048. Dweck, C. S. (1999). Self-theories: Their role in motivation, personality, and development. Philadelphia, PA: Psychology Press. Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256–273. Dweck, C. S., Chiu, C., & Hong, Y. (1995). Implicit theories and their role in judgements and reactions: A world from two perspectives. Psychological Inquiry, 6, 267–285. Findley, M. J., & Cooper, H. M. (1983). Locus of control and academic achievement: A literature review. Journal of Personality and Social Psychology, 44, 419–427. Grant, H., & Dweck, C. S. (2003). Clarifying achievement goals and their impact. Journal of Personality and Social Psychology, 85, 541–553. Graham, S. (1995). Implicit theories as conceptualized by an attribution researcher. Psychological Inquiry, 6, 294–297. Heider, F. (1958). The psychology of interpersonal relations. New York, NY: John Wiley & Sons. Hong, Y., Chui, C., Dweck, C. S., Lin, D.M. S., & Wan, W. (1999). Implicit theories, attributions, and coping: A meaning system approach. Journal of Personality and Social Psychology, 77, 588–599. Onwuegbuzie, A. J., & Daley, C. E. (1998). Study skills of undergraduates as a function of academic locus of control, self-perception, and social independence. Psychological Reports, 83, 595–598. Pepi, A., Faria, L., & Alesi, M. (2006). Personal conceptions of intelligence, self esteem, and school achievement in Italian and Portuguese students. Adolescence, 41(164), 616–631. Perry, R., Hechter, F. J., Menec, V. H., & Weinberg, L. E. (1993). Enhancing achievement motivation and performance in college students: An attributional retraining perspective. Research in Higher Education, 34(6), 687–723. Plant, A. E., Ericsson, K. A., Hill, L., & Asberg, K. (2005). Why study time does not predict grade point average across college students: Implications of deliberate practice for academic performance. Contemporary Educational Psychology, 30(1), 96–116. Siegle, D., Rubenstein, L. D., Pollard, E., & Romey, E. (2010). Exploring the relationship of college freshman honours students' effort and ability attribution, interest and implicit theory of intelligence with perceived ability. Gifted Child Quarterly, 54, 92–101. Trice, A.D., Ogden, E. P., Stevens, W., & Booth, J. (1987). Concurrent validity of the Academic Locus of Control Scale. Educational and Psychological Measurement, 47, 483–486. Trice, A.D. (1985). An academic locus of control scale for college students. Perceptual and Motor Skills, 61, 1043–1046.
Contents lists available at ScienceDirect
Learning and Individual Differences journal homepage: www.elsevier.com/locate/lindif
Implicit theories of intelligence and academic locus of control as predictors of studying behaviour Kate Bodill, Lynne D. Roberts ⁎ Curtin Health Innovation Research Institute, Curtin University, Australia
a r t i c l e
i n f o
Article history: Received 24 September 2011 Received in revised form 2 July 2012 Accepted 28 August 2013 Keywords: Dweck Locus of control Implicit theories of intelligence Academic effort University students
a b s t r a c t Dweck's social-cognitive approach to implicit theories of intelligence posits that entity beliefs and incremental beliefs are associated with, and precede the development of, external and internal locus of control respectively. To date, this proposition underlying the theory has not been adequately tested. An online questionnaire including measures of implicit intelligence beliefs, academic locus of control and hours studying per week was completed by 94 Australian university students. Multiple regression analysis supported the posited relationship between entity beliefs and external locus of control, but not that between incremental beliefs and internal locus of control. While providing partial support for Dweck's proposition, further longitudinal testing is required to determine causal ordering. A second multiple regression indicated that academic locus of control was a significant predictor of hours studying per week, but implicit theories of intelligence were not, suggesting that locus of control beliefs are the more appropriate target of efforts at improving academic effort. © 2013 Elsevier Inc. All rights reserved.
1. Introduction Individuals have their own ‘lay’ or implicit theories about psychological concepts such as intelligence that influence the way people view themselves and others (Heider, 1958), providing a framework when attempting to explain human actions (Dweck, Chiu, & Hong, 1995). However, because theories are often hidden or poorly articulated, it is sometimes difficult to identify the effect they have on different life domains (Dweck et al., 1995). A dominant social-cognitive approach to the study of implicit theories of intelligence is that developed by Dweck and colleagues (Dweck, 1986, 1999; Dweck & Leggett, 1988; Dweck et al., 1995). This approach identified two types of implicit beliefs about intelligence: entity beliefs and incremental beliefs. People who endorse an entity theory of intelligence believe that intelligence is a fixed ability and tend to adopt performance goals with the aim of gaining approval from outsiders. They believe that if effort is required to achieve a goal, that this is indicative of limited ability and therefore seek challenges that are fairly easy and require less effort to ensure they can perform well in light of others (Dweck, 1999). Conversely, people who endorse an incremental theory of intelligence believe that intelligence is malleable and can be improved. They set mastery goals which require the learning of new skills in order to increase competence and seek challenging tasks based on the belief in effort (Dweck, 1999). ⁎ Corresponding author at: School of Psychology and Speech Pathology, Curtin Health Innovation Research Institute, Curtin University, GPO Box U1987, Perth, WA 6845, Australia. Tel.: +61 8 9266 7183; fax: +61 8 9266 2464. E-mail address: [email protected] (L.D. Roberts). 1041-6080/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.lindif.2013.08.001
Originally, Dweck and Leggett (1988) proposed that people believe in either an incremental theory of intelligence or an entity theory of intelligence and conceptualised the two sets of beliefs as belonging on opposite ends of a continuum. More recent research by Hong, Chui, Dweck, Lin, and Wan (1999) suggests that people can hold both entity and incremental beliefs simultaneously. Entity and incremental beliefs are moderately negatively correlated (r = −.35 to −.55; Abd-El-Fattah & Yates, 2006; Dupeyrat & Mariné, 2005) suggesting that they are separate, yet correlated constructs, rather than two ends of a continuum. In theorising about implicit theories of intelligence Dweck et al. (1995) posited that implicit beliefs about intelligence are associated with locus of control. Locus of control refers to whether an individual attributes events and outcomes to external or internal influences (Cooper, Burger, & Good, 1981). People with an internal locus of control believe that outcomes arise from effort and therefore view their actions to be influential over life outcomes (Cooper et al., 1981). Conversely, individuals with an external locus of control believe that the environment and situational factors are responsible for life outcomes and are likely to attribute success or failure to chance or unfavourable circumstances, rather than to lack of effort (Cooper et al., 1981). Locus of control can be measured across domains, or within specific domains to predict different social behaviours and psychological states, including academic task persistence (Trice, Ogden, Stevens, & Booth, 1987). Academic locus of control refers to an individual's perceived control over academic achievement, with internal academic locus of control indicating that the individual believes effort is a requirement for academic success (Trice et al., 1987). Dweck and Leggett (1988) posited that entity beliefs about intelligence are associated with external and incremental beliefs with internal locus of control.
164
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Dweck et al. (1995) further posited that implicit beliefs about intelligence precede the development of locus of control. While both relate to perceptions of control over important life domains (Dweck & Leggett, 1988) implicit beliefs relate to perceptions of control over intelligence, whereas locus of control relates to perceptions of control over events and outcomes. Dweck and Leggett (1988) posited that people who hold entity beliefs are likely to have trouble perceiving control over intelligence and therefore negative outcomes in associated areas (such as academic failure) are viewed to be out of their control, representing an external locus of control. Conversely, individuals who hold incremental beliefs about intelligence will view outcomes as under their control and interpret outcomes from an internal locus of control perspective. Contrary to this Graham (1995) suggested that the evidence is unclear as to whether control attributions are guided by implicit theories of intelligence, or if past experiences of academic failures promote the endorsement of an entity view. There is a dearth of published empirical research regarding the relationship between implicit theories of intelligence and locus of control. Only one published study could be located that has directly assessed the relationship between the two constructs, reporting a significant positive relationship between incremental beliefs and internal locus of control, but with neither correlation coefficient nor effect size reported (Dweck et al., 1995). The implicit theory measure used in this study consisted of three items reflecting entity statements only and as such does not provide an adequate test of the proposition that implicit theories of intelligence are associated with locus of control. Academic task persistence (effort) is a core domain of relevance to intelligence. According to Dweck and Leggett (1988) individuals who hold entity beliefs exert less effort to produce academic success and where they believe their intellectual ability is low, become helpless when faced with academic failures and consequently withdraw effort to save face. Conversely, individuals who endorse an incremental theory are concerned with the processes involved in mastering challenging tasks and may attribute unfavourable outcomes to poor strategy or lack of effort, rather than ability (Grant & Dweck, 2003). They are therefore more likely to persevere when faced with negative feedback (Dweck & Leggett, 1988). One study to date has reported that entity beliefs were significantly negatively correlated with effort (r = −.23), operationalised as the number of homework activities completed in the academic year (Dupeyrat & Mariné, 2005). Locus of control has also been associated with effort, with internal locus of control associated with greater effort. Based on a metaanalysis of 75 studies (Findley & Cooper, 1983) the effect size is small, suggesting that academic performance is multiply determined, with other variables also playing an important role. No study to date has attempted to examine whether Dweck's implicit theories of intelligence or academic locus of control can better predict effort within a university setting. 1.1. Current study The current study has two main aims. The first aim is to test Dweck and Leggett's (1988) theoretical proposition that implicit theories of intelligence and ALC are related, a proposition that has not been fully tested to date. Gender will be controlled for in this analysis as previous research suggests that females are more likely than males to hold entity beliefs of intelligence (Pepi, Faria, & Alesi, 2006) and internal locus of control (Cooper et al., 1981). It is hypothesised that incremental beliefs will be correlated with internal locus of control and entity beliefs with external locus of control. The second aim is to determine whether implicit theories of intelligence or academic locus of control are better predictors of academic effort, operationalised as the number of hours spent studying per week. The mode of study (full time or part time) will be controlled for as this is likely to affect the number of hours an individual would spend studying per week. If, as proposed by Dweck and Leggett (1988),
implicit theories of intelligence precede locus of control, then implicit theories of intelligence should be a distal predictor and locus of control a proximal predictor of study behaviour, with locus of control the stronger predictor of study behaviour. 2. Method 2.1. Participants A snowball sampling method through Facebook and inviting students on campus to participate in the research was utilised to recruit a convenience sample of 102 university students enrolled across a range of faculties at a Western Australian university. Eight cases were removed from the initial sample due to incomplete data (missing more than 10%), leaving 94 participants remaining in the sample for analysis. Participants were predominantly female (69.1%), full-time (87.2%) students with a mean age of 20.8 years (SD = 2.3 years). Prior to conducting the research, an a-priori power analysis was conducted. In order to detect a medium size effect, with a power of .80 at a significance level of .05, 91 participants were required. The final sample size of 94 participants meets this requirement. 2.2. Measures An online questionnaire was developed consisting of measures of implicit theories of intelligence, academic locus of control and single item measures of age, gender, faculty, study status (part-time or fulltime) and effort (hours spent studying per week). 2.2.1. Implicit Theory of Intelligence Scale (ITIS) The ITIS is a self-report measure comprising seven entity and seven incremental items representing beliefs about intelligence (Abd-ElFattah & Yates, 2006). Example items are “You are born with a fixed amount of intelligence” (entity subscale) and “Good preparation before performing a task is a way to develop your intelligence” (incremental scale). Participants were required to respond to the items according to a 4-point Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree). Previous research has suggested that the measure consists of two factors representing entity and incremental beliefs, both with acceptable reliability (Cronbach's alpha above .75) and demonstrating discriminant validity (r = −.35; Abd-El-Fattah & Yates, 2006). In the current sample, the internal reliability was adequate (Cronbach's alpha = .70 incremental and .65 entity). Scores on the entity and incremental subscales of the ITIS have a possible range from 7 to 28 with higher scores reflecting a stronger agreement with the statements on each of the subscales. 2.2.2. Academic Locus of Control Scale (ALCS) The ALCS is a 28 item true–false scale measuring perceptions of control over academic outcomes (Trice, 1985). Items were written to reflect Rotter's I–E scale within the specific domain of academic effort within college. Individual scores are calculated by summing the number of externally answered items and can range from 0 through to 28. Higher scores are indicative of a more external locus of control over academic outcomes. Example items are “What I learn is more determined by college and course requirement than by what I want to learn” and “Studying every day is important” (reverse coded). Higher scores convey external perceptions of control over academic outcomes, with lower scores conveying internal perceptions that academic success requires personal effort. Previous research suggests the ALCS has acceptable internal consistency (Cronbach's alpha = .70), good test–retest reliability over a five week interval (r = .92; Trice, 1985), is not associated with socially desirable responding, and has adequate construct validity with Rotter's I–E scale (r = .50, Trice, 1985). In the current sample the scale had acceptable reliability (Cronbach's alpha = .72).
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2.3. Procedure Prior to commencing data collection, ethics approval was obtained. The online questionnaire was developed and hosted on SurveyMonkey.com. Two versions of the questionnaire were created, with the ITIS and ALCS counter-balanced to remove the influence of order effects. As an incentive for participation, entry into a prize draw for a $50 AUD iTunes gift voucher was offered. The questionnaire remained available for 50 days. After this time the survey was removed. A preliminary inspection of the data using Missing Values Analysis was conducted to determine the extent of missing data. Four missing data points were replaced using mean substitution. 3. Results and discussion Descriptive statistics and correlations between key variables are presented in Table 1. The proposed control variables for the analysis were gender and study mode. As gender was not significantly associated with the other variables it was dropped from further analyses. Mode of study was retained for the second regression analysis. The assumptions underlying multiple regression analysis were tested. Hours of study was transformed with a logarithm transformation due to its substantial positive skewness. Two univariate outliers were brought in closer to the distribution. A multiple regression analysis was utilised to test Dweck and Leggett's (1988) theoretical proposition that implicit theories of intelligence and academic locus of control are related. Total scores on the ‘entity’ and ‘incremental’ scales from the ITI scale were entered simultaneously into the multiple regression model as predictors with ALCS scores as the criterion variable. In combination, entity and incremental scores accounted for a significant 11.2% of the variance in ALCS scores, R2 = .112, adjusted R2 = .092, F (2, 91) = 5.72, p = .005 (small to medium effect size). The unstandardised (B) and standardised (β) regression coefficients, and squared semipartial correlations (sr2) for each predictor are presented in Table 2. Entity scores accounted for a significant 8.1% of unique variance in ALCS scores with incremental scores not accounting for any significant variance. A hierarchical multiple regression analysis with hours of study as the criterion variable was conducted to test whether implicit theories of intelligence or academic locus of control were better predictors of academic effort. The control variable, study mode, was entered in step 1 and accounted for a significant 7.8% of the variance in hours of study R2 = .078, F (1, 92) = 7.76, p = .006. Entity, incremental and ALCS scores were entered as predictors in step 2 and accounted for an additional 22.3% of variance in hours of study, Δ R2 = .223, Δ F (3, 89) = 9.47, p b .001. In combination the predictors were able to account for 30.1% of the variance in hours of study, R2 = .301, adjusted R2 = .269, F (4, 89) = 9.477, p b .001 (medium to large effect size). The unstandardised (B) and standardised (β) regression coefficients and squared semipartial correlations (sr2) for each predictor on each step of the hierarchical MRA are presented in Table 3. In the final model, Table 1 Correlation matrix of key variables. Variable
Mean
SD
1
1. 2. 3. 4. 5. 6.
16.51 21.94 13.68 1.01
3.20 2.91 4.10 0.34
−.30⁎⁎ .33⁎⁎
Entity Incremental ALCS Hours studya Study modeb Genderc
−.08 .06 .11
2
3
4
5
6
Table 2 Unstandardised (B) and standardised (β) regression coefficients and squared semipartial (or part) correlations (sr2) for each predictor in a multiple regression model predicting academic locus of control. Variable
B [95% CI]
β
sr2
Entity Incremental
.400 [.126, .674]⁎⁎ −.122 [−.423, .497]
.300 −.083
.081 .007
Note. N = 94. CI = confidence interval. ⁎⁎ p b .01.
study mode accounted for a significant 3.5% of the variance in hours spent studying per week with academic locus of control scores accounting for a further significant 18.2%. Entity and incremental scores did not account for significant variance in hours studying per week. The results from the first multiple regression analysis partially supported Dweck and Leggett's (1988) proposition that implicit theories of intelligence and locus of control are associated. Entity scores were significantly positively associated with academic locus of control scores, demonstrating the association between entity beliefs and an external academic locus of control. However, there was no support for the predicted association between incremental beliefs and an internal locus of control. As the current research utilised a cross sectional research design, the causal direction between the constructs was unable to be tested. Future longitudinal research is required to determine whether the development of implicit theories do in fact precede locus of control. The results of the second hierarchical multiple regression analysis suggest that while neither incremental nor entity beliefs are directly associated with academic effort, entity beliefs are associated with external academic locus of control, which in turn was found to be a significant predictor of hours studied per week. One possible reason for these findings is that academic locus of control measures are specifically designed to predict studying behaviour within the academic domain (Trice et al., 1987), whereas implicit theories of intelligence measures are based on the broader domain of intelligence. Another possible reason for the lack of association found between implicit theories of intelligence and hours spent studying is the use of a university student sample. University students have an average IQ above that of the general population and are generally highly motivated to perform well in order to produce academic success (Siegle, Rubenstein, Pollard, & Romey, 2010). Dweck and Leggett (1988) posited that individuals who endorse an entity theory of intelligence will only exert less effort if low intellectual ability is perceived. If university students believe that they are highly competent, holding an entity view of intelligence may neither facilitate nor hinder the amount of effort exerted in academic studies. It is possible that implicit beliefs act as moderators, rather than direct predictors, of studying behaviour. Further disentanglement of effort and ability when examining relationships between implicit theories, locus of control and academic outcomes is desirable. Overall, the results obtained suggest that academic locus of control is directly associated with studying behaviour in university students, Table 3 Unstandardised (B) and standardised (β) regression coefficients, and squared semipartial (or part) correlations (sr2) for each predictor on each step of the hierarchical MRA predicting hours of study. Variable
−.17 .16 −.12 −.11
Notes: N = 94. a Transformed variable. b Part-time coded as 0 and full-time coded as 1. c Male coded as 1 and female as = 0. ⁎⁎ Correlation significant at p b .01 (2-tailed). ⁎ Correlation significant at p b .05 (2-tailed).
−.49⁎⁎ −.20 .07
.24⁎ −.13
−.02
165
Step 1 Study mode Step 2 Study mode Entity Incremental ALCS
B [95% CI] .279 [.080, .478]⁎⁎ .195 [.012, .378]⁎ .006 [−.014, .027] .013 [−.009, .034] −.037 [−.052, −.022]⁎⁎
Note. N = 94. CI = confidence interval. ⁎⁎ p b .01. ⁎ p b .05.
sr2
β .279
.078
.195 .061 .112 −.467
.035 .003 .011 .182
166
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while entity beliefs are associated with academic locus of control but not directly related to studying behaviour. This requires further testing in longitudinal research. Given the restricted range of IQ within university students (Siegle et al., 2010) the results from the current study cannot be generalised to the wider population. Future research should be conducted on a wider population in order to determine whether the same findings emerge when the sample consists of a more diverse IQ range. The negative association found between external academic locus of control and academic effort is consistent with previous research (e.g., Onwuegbuzie & Daley, 1998; Trice, 1985; Trice et al., 1987) and has important implications within the academic domain. Previous research (e.g., Aronson, Fried, & Good, 2002; Blackwell & Trzesniewski, 2007) has indicated that it is possible to successfully induce people to believe in incremental beliefs, resulting in behaviour that is more driven and mastery oriented. However, our research suggests that in terms of changing study behaviour in university students, challenging implicit beliefs about intelligence may be important only to the extent that it results in increasing internal academic locus of control. If the aim is to increase academic effort, academic locus of control beliefs may be the more appropriate target. This provides support for the concept termed ‘attributional retraining’ which refers to the process of educating individuals to endorse an internal locus of control and to make unstable attributions, in order to improve motivation and enhance achievement striving (Perry, Hechter, Menec, & Weinberg, 1993). A limitation of the current study is that the criterion variable ‘studying behaviour’ was measured using a single item, self-report measurement of the approximate number of hours spent studying per week. Research indicates that time spent studying is a poor predictor of academic achievement (Plant, Ericsson, Hill, & Asberg, 2005) and is only a significant predictor of academic achievement when the study is undertaken under quiet conditions and previously attained performance and quality of study are taken into consideration. A more nuanced measure of effective studying behaviour conceptualising studying as a multidimensional construct (Plant et al., 2005) is required for future research in this area. In conclusion, the findings from the present study partially support Dweck and Leggett's (1988) proposition that implicit theories are associated with locus of control. Entity beliefs about intelligence were significantly positively associated with an external academic locus of control, while incremental beliefs were not significantly related to academic locus of control. However, only academic locus of control was a significant predictor of studying behaviour in university students.
References Abd-El-Fattah, S. M., & Yates, G. C. R. (2006). Implicit Theory of Intelligence Scale: Testing for factorial invariance and mean structure. Paper presented at the Australian Association for Research in Education Conference, Adelaide, South Australia. Aronson, J., Fried, C. B., & Good, C. (2002). Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. Journal of Experimental Social Psychology, 38, 113–125. Blackwell, L. S., & Trzesniewski, K. H. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246–263. Cooper, H. M., Burger, J. M., & Good, T. L. (1981). Gender differences in the academic locus of control beliefs of young children. Journal of Personality and Social Psychology, 40, 562–572. Dupeyrat, C., & Mariné, C. (2005). Implicit theories of intelligence, goal orientation, cognitive engagement, and achievement: A test of Dweck's model with returning to school adults. Contemporary Educational Psychology, 30, 43–59. Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41, 1040–1048. Dweck, C. S. (1999). Self-theories: Their role in motivation, personality, and development. Philadelphia, PA: Psychology Press. Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256–273. Dweck, C. S., Chiu, C., & Hong, Y. (1995). Implicit theories and their role in judgements and reactions: A world from two perspectives. Psychological Inquiry, 6, 267–285. Findley, M. J., & Cooper, H. M. (1983). Locus of control and academic achievement: A literature review. Journal of Personality and Social Psychology, 44, 419–427. Grant, H., & Dweck, C. S. (2003). Clarifying achievement goals and their impact. Journal of Personality and Social Psychology, 85, 541–553. Graham, S. (1995). Implicit theories as conceptualized by an attribution researcher. Psychological Inquiry, 6, 294–297. Heider, F. (1958). The psychology of interpersonal relations. New York, NY: John Wiley & Sons. Hong, Y., Chui, C., Dweck, C. S., Lin, D.M. S., & Wan, W. (1999). Implicit theories, attributions, and coping: A meaning system approach. Journal of Personality and Social Psychology, 77, 588–599. Onwuegbuzie, A. J., & Daley, C. E. (1998). Study skills of undergraduates as a function of academic locus of control, self-perception, and social independence. Psychological Reports, 83, 595–598. Pepi, A., Faria, L., & Alesi, M. (2006). Personal conceptions of intelligence, self esteem, and school achievement in Italian and Portuguese students. Adolescence, 41(164), 616–631. Perry, R., Hechter, F. J., Menec, V. H., & Weinberg, L. E. (1993). Enhancing achievement motivation and performance in college students: An attributional retraining perspective. Research in Higher Education, 34(6), 687–723. Plant, A. E., Ericsson, K. A., Hill, L., & Asberg, K. (2005). Why study time does not predict grade point average across college students: Implications of deliberate practice for academic performance. Contemporary Educational Psychology, 30(1), 96–116. Siegle, D., Rubenstein, L. D., Pollard, E., & Romey, E. (2010). Exploring the relationship of college freshman honours students' effort and ability attribution, interest and implicit theory of intelligence with perceived ability. Gifted Child Quarterly, 54, 92–101. Trice, A.D., Ogden, E. P., Stevens, W., & Booth, J. (1987). Concurrent validity of the Academic Locus of Control Scale. Educational and Psychological Measurement, 47, 483–486. Trice, A.D. (1985). An academic locus of control scale for college students. Perceptual and Motor Skills, 61, 1043–1046.