65 Empirical Review
66
their cognitive performances interacts with their perceived self-efficacy, second-graders and fourth-graders were assigned to a training group and a control group. The only difference between the control group and the treatment group is that metacognitive awareness was encouraged in the treatment group. All the students were taught two different strategies to memorise words: rote-repetition method and sentence elaboration method. These children‘s memorisation of the words was measured afterwards. Regardless of grade or group, all participants exhibited gains in self-efficacy from pre-test to post-test. The successful learning performance by the children led to enhanced self-efficacy, which also generated to other similar tasks such as remembering numbers.
Research investigations on academic self-efficacy demonstrate that acquisition of cognitive skills, modelling effects, attributional feedback and goal setting influence the development of self-efficacy beliefs and that these beliefs, in turn, influence academic performances. Relich, Debus, and Walker (1986) report that self-efficacy mediated the role of skill training and attributional feedback and had a direct effect on the performance of division problems of learned helpless sixth graders. Attributional feedback showed a moderate direct effect on performance and a strong indirect effect mediated by self-efficacy. In another study, Schunk (1984b) further reports that mathematics self-efficacy influenced mathematic performance directly and indirectly through persistence. Although students with similar previous performance attainments and cognitive skills may differ in subsequent performance as a result of differing self-efficacy perceptions because these perceptions mediate between prior attainments and academic performances. In effect, such performances are generally better predicted by self-efficacy than by the prior attainments.
Pintrich and De Groot (1990) report a correlation between global academic self-efficacy and cognitive strategy use and self-regulation through use of metacognitive strategies. In addition, academic self-efficacy correlated with academic performances such as semester and final year grades, in-class seat work and homework, exams and quizzes and essays and reports. They report that perceived importance of academic achievement is associated with the outcome variables but is not a significant predictor. Pintrich and De Groot conclude that self-efficacy played a mediational or "facilitative" role in relation to cognitive engagement, that improving self-efficacy might lead to increased use of cognitive strategies and thereby higher performance, and that students must possess the will and skill to be successful in any academic task.
Zimmerman, Bandura, and Martinez-Pons (1992) used path analysis to demonstrate that academic self-efficacy mediated the influence of self-efficacy for self-regulated learning
67
on academic achievement. They observe that academic self-efficacy influences achievement directly as well as indirectly by raising students' scores. Correspondingly, Schunk (1982b, 1985); Fincham and Cain (1986); Paris and Oka (1986); Feather (1988); Pokay and Blumenfeld (1990); and Pintrich and Schrauben (1992) have found that self-efficacy is related to self-regulated learning variables. Their findings in this area suggest that students who believe they are capable of performing academic tasks use more cognitive and metacognitive strategies and persist longer than those who do not (Pintrich & Garcia, 1991).
A meta-analytic research into self-efficacy in educational settings conducted by Multon, Brown and Lent (1991) provided a support for the facilitating effects of self-efficacy on academic performance and concluded that self-efficacy beliefs accounted for approximately 14 per cent of the variance in students‘ academic performance. Lane and Lane (2001) affirm while reporting similar findings among a sample of postgraduate students.
Research has shown that metacognition is an important predictor of academic performance; students are able to effectively distinguish information they know and do not know are more likely to review and retain new information (Dunslosky & Thiede, 1998;
Kruger & Dunning, 1999; Dunning, Johnson, Ehrlinger, & Kruger, 2003). Pajares (1996) observes that the self-efficacy of gifted students is based on perceptions of their cognitive ability. Metacognition has been described as a discrepancy-reduction strategy where the learner begins study by setting a specific desired state of learning for the material (Dunslosky
& Thiede, 1998; Thiede, Anderson, & Therriault, 2003). The student allocates resources to learn new information and monitors the degree to which new material has been learned but learning is discontinued when the student believes that he or she has mastered the information and achieved the desired state of learning.
People with strong self-efficacy focus their energy on analysing and resolving problems. People with weak self-efficacy become preoccupied with evaluation concerns, doubt their skills and abilities, and anticipate failure even before investing effort in problem-solving (Bandura & Wood, 1989). These negative beliefs heighten stress, undermine the effective use of cognitive strategies and eventually result in failure. Moderately overconfident and optimistic students tend to be the best performing students (Pajares & Miller, 1994;
Pajares & Kranzler, 1995). People use their past performance to infer their level of ability and extent of success on a task (Gist & Mitchell, 1992). Those who receive positive feedback are likely to believe they have the capabilities to perform a task. Conversely, those who receive poor performance assessments are likely to have low efficacy beliefs regarding the task. Self-efficacy is a good predictor of academic performance (GPA) in higher education plans
68
(Lalonde, 1980; Multon, Brown, & Lent, 1991). Metacognitive knowledge and training have been reported effective in improved self-efficacy (Butler, 1993; Schmidt & Ford, 2003).
According to Flavell (1979), who coined the term, metacognition is a regulatory system that includes knowledge, experiences, goals and strategies. Metacognitive knowledge is stored knowledge or beliefs about oneself and others as cognitive agents; tasks; actions or strategies and how all these interact to affect the outcome of any intellectual undertaking.
Metacognitive experiences are conscious cognitive or affective experiences that concern any aspect of an intellectual undertaking. Knowledge is considered metacognitive (as opposed to simply cognitive) if it is used in a strategic manner to meet a goal. According to Sternberg (1986) it is figuring out how to do a particular task or set of tasks and then making sure that the task or set of tasks are done correctly. Metacognition is similar to self-efficacy in that metacognitive self-assessments have been related to an individual's ability to perform a task, solve problems, or acquire new skills (Paris & Winograd, 1990; Davidson et al., 1994;
Hartman, 2001; Cuevas et al., 2004). Improving the accuracy of metacognitive judgments has also been found to lead to an improvement in learning or task performance (Kruger &
Dunning, 1999). The similarity in the dependent variable often results in measurement instruments that use very similar items. In particular, self-efficacy and metacognition are measured with respect to some level of achievement in performing a task.
Studies have shown that the relationship between self-efficacy and performance is partially mediated by metacognition (Kanfer & Ackerman, 1989; Bouffard-Bouchard, Parent,
& Larivee, 1991). Kanfer and Ackerman (1989) observe that people with strong self-efficacy are more likely to use metacognitive strategies when working on a task and they performed better than those with weak self-efficacy. A similar conclusion comes from Bouffard-Bouchard, Parent, and Larivee. Students with strong self-efficacy engage in more metacognitive skills and have better performance scores than students with weak self-efficacy, irrespective of differences in school grade and cognitive ability. Bandura and Wood (1989) observe self-efficacy influences performance directly and indirectly through its effects on analytical strategies, suggesting a mediating effect of metacognition in the relationship between self-efficacy and performance. Students with good metacognition demonstrate good academic performance compared to students with poor metacognition.
Students with poor metacognition may benefit from metacognitive training to improve their metacognition and performance. On the contrary, Coutinho (2008) conducted a regression analysis and found out that the relationship between self-efficacy and performance was not mediated by metacognition. However, another analysis showed that the relationship
69
between metacognition and performance was fully mediated by self-efficacy. This suggests that students with effective metacognitive strategies also have strong belief in their capabilities to successfully perform a task. These findings lend support to training programmes for students that enhance self-efficacy and strengthen their metacognitive strategies and skills.
Notably, there are three key differences between self-efficacy and metacognition.
First, according to Bandura's general model of Social Cognitive Theory, self-efficacy is a determinant of behaviour and indirectly affects performance. Given the difficulty in measuring the behaviour that goes into accomplishing a task it is no surprise to find that most studies choose to relate self-efficacy directly to (measurable) performance. Metacognition, on the other hand, has a complex relationship with behaviour and performance, initiating the (problem solving) behaviour, monitoring performance and changing behaviour if things are not going as expected. This difference makes metacognition useful in enhancing end-user training since the dependent variable of most concern is not only whether someone will use a computer (behaviour), but whether employees can use a computer to become more effective at accomplishing job related tasks (performance). In order to go beyond an understanding of behaviour, therefore, we need to examine the relationship between behaviour and attained levels of performance. It is the role of metacognition to provide the necessary feedback loop between performance and behaviour by monitoring levels of performance and controlling subsequent behaviour (Nelson & Narens, 1996).
Second, metacognition is generally considered to be a uni-dimensional construct, and is often measured as a declaration of confidence or certainty in the accuracy or adequacy of performance (McGuire & Maki, 2001; Nelson et al., 2004), as a judgment of learning (Kelemen, 2000), or as a feeling of knowing (Metcalfe, Schwartz & Joaquim, 1993) either just before or just after the behaviour of interest. As such, the method of measurement is generally a Likert-type confidence scale (Schwartz, 1994). On the other hand, self-efficacy is a three-dimensional construct including level, strength and generality, with measurement usually focusing on only one or two of the dimensions (e.g., strength).
Self-efficacy instruments are normally developed as a related set of items that increase or decrease in task difficulty (Compeau & Higgins, 1995a; Johnson & Marakas, 2000). Third, while self-efficacy is usually defined as positively correlated with behaviour and performance, metacognitive judgments are often at odds with objective measures of learning or task performance. This results from a phenomenon known as metacognitive miscalibration (MM) where an individual misjudges his/her level of proficiency by being
70
either overconfident or under-confident and can lead to premature termination of task effort.
For instance, a student may stop studying for a test based on erroneous judgment of being good enough already (overconfident), or simply expecting to fail (under-confident). Some hypothesised reasons for MM include cue familiarity (Metcalfe et al. 1993) and the above average effect (Alicke, Klotz, Breitenbecher, Yurak & Vredenburg, 1995; Dunning et al., 1989). Put simply, familiarity results in over-confidence, while few people are willing to admit they are "below average." Whether inaccurate beliefs about one's self-efficacy poses a concern continues to generate debate (Vancouver et al., 2002; Bandura & Locke, 2003).
Knowing how to use a combination of strategies in an orchestrated fashion is an important metacognitive skill. Research has shown that successful learners tend to select strategies that work well together in a highly orchestrated way, tailored to the requirements of any learning task (Chamot & Kupper, 1989; Wenden, 1998). These learners can easily explain the strategies they use and why they employ them (O'Malley & Chamot, 1990).
According to Chamot and Kupper (1989), certain strategies or clusters of strategies are linked to particular language skills or tasks. For example, L2 writing, like L1 writing, benefits from the learning strategies of planning, self-monitoring, deduction, and substitution. L2 speaking demands strategies such as risk-taking, paraphrasing, circumlocution, self-monitoring, and self-evaluation. L2 listening comprehension gains from strategies of elaboration, making inferences, selective attention and self-monitoring. Reading comprehension uses strategies like reading aloud, guessing, deduction and summarising. Research shows that use of appropriate language learning strategies often results in improved proficiency or achievement overall or in specific skill areas (Oxford, Park-Oh, Ito, & Sumrall, 1993).
One of the most important metacognitive strategies is to evaluate effectiveness of strategy use. Self-questioning, debriefing discussions after strategies practice, learning logs in which students record the results of their learning strategies applications, and checklists of strategies used can be used to allow the student reflect through the cycle of learning. At this stage of metacognition, the whole cycle of planning, selecting, using, monitoring and orchestration of strategies is evaluated. It should be noted that different metacognitive skills interact with each other. The components are not used in a linear fashion. More than one metacognitive process along with cognitive ones may be working during a learning task (Anderson, 2002b), therefore, the orchestration of various strategies is a vital component of learning in general. Allowing learners opportunities to think about and talk about how they combine various strategies facilitates strategy use.
71
Active-coping efforts were associated with higher self-efficacy scores and good dissertation grades by Devonport et al, (2003). Self-efficacy reflects a person‘s realistic expectations and degree of certainty about the ability to achieve success (Anshel, Kim, Kim, Chang & Eom, 2001). The finding that active coping and self-efficacy appear to be predictive of each other is important because efficacy expectations are proposed to influence task selection and the effort expended in task completion. The implication of this may be that academics should encourage the appropriate selection of coping options. Doing so may enhance self-efficacy and consequently academic performance, which in turn could reduce dropout rates. Again, Devonport, et al (2003) in their investigation into the relationships between self-efficacy and dissertation performance among a sample of undergraduate sports studies students reveal that the sum of self-efficacy factors such as obtaining support, understanding theory and writing skills significantly correlates with performance. Their findings lend credence to Lane, Hall and Lane (2002) assertion that self-efficacy can significantly predict academic performance.
Zimmerman and Schunk (2001) in a study observe that students who have been taught metacognitive (self-regulated learning) skills learn better than students who have not been taught these skills. This finding lends credence to the works of Pressley and Ghatala (1990);
Mace, Belfiore and Hutchinson (2001). McCombs and Marzano (1990) and Schunk (1990) explain that increased self-confidence and a sense of personal responsibility instilled through metacognitive training may provide motivation for learning and also produce better learners.
Metacognitive strategies have been proved to attribute to the success of reading strategy use (Lin, 2009; Hamzah & Abdullah, 2009). Vandergrift (2003) trained students in the use of prediction, individual planning, peer discussions and post listening reflections that made up the metacognitive strategies in beginner elementary school and university contexts in France.
Students in both groups were more focused on the advantages of predictions for successful listening, the place of collaboration with a partner for monitoring and the confidence-building function of this approach for developing listening comprehension ability. Hoffman and Spatariu‘s (2007) findings in a regression design also support the unique and interactive effects of self-efficacy beliefs and metacognitive prompting on solving mental multiplication problems. Self-efficacy and metacognitive prompting increased problem-solving performance and efficiency separately through activation of reflection and strategy knowledge.
Javanmard, Hoshmandja and Ahmadzade (2013) investigated the relationship between self-efficacy, cognitive and metacognitive strategies and academic self-handicapping with academic achievement in male high school students in the tribes of Fars Province, Iran.
72
A descriptive, correlational method was used to analyse the data collected among high school students studying in the academic year 2010-2011. They report that cognitive and metacognitive strategies are not good predictors of academic achievement. Moreover, their results demonstrated that different groups of students had different fields of study and were in different grades – were not significantly different with regard to academic self-efficacy, academic self-handicapping, and cognitive and metacognitive strategies. However, there were significant differences in employing metacognitive strategies with regard to students‘ grades and fields of study