Applications of self-efficacy theory straddle across areas ranging from health rehabilitation to social movements (Bandura, 1982), and the accumulating research has devoted to the instrumentation of self-efficacy beliefs in academic arenas (Pajares, 1996). Academic studies on self-efficacy peek through every member of schools, ranging from students, teachers to administrative staff. (Bandura, 1986; Pajares, 1996).
Students’ self-efficacy in assorted subject areas such as math, science and literature are investigated, and in language classes, self-efficacy in four language skills as well as the overall L2 learning self-efficacy are inspected respectively (Wang, 2011; Mills, Pajares
41
& Herron, 2006). A general consensus affirms Bandura’s (1986) proposal that self-efficacy predicts learning outcomes (Graham, 2006), and the more specific the task, the more accurate its prediction is (Schunk, 1989).
Research of self-efficacy seeks to apply the concept to different fields of study. It could, for instance, be analyzed under family structures, career developments, and health-promotion. Across diverse areas, one’s self-efficacy varies in level, generality, and strength. When self-efficacy is put in the academic arena, it involves students’
judgments of their capability in performing the required activities.
Self-efficacy is multidimensional, differing from subject to subject, and so is its measurement. Students evaluate themselves depending on a mastery criterion rather than normative comparison with others. And it is generally measured before the real tasks, as prior weighing of self-efficacy proves to have no influence on students’
consequential performance (Zimmerman, 1995; Bandura, 2006).
Study has proved that self-efficacy affects students’ effort, persistence and choice of activities. Guided instruction with frequent feedback helps sustain and intensify students’ efficacy. When students are led to set their own proximal goals, their self-efficacy would increase. Students’ self-self-efficacy also predicts their ultimate achievement as well as anxiety level. In fact, it is shown that self-efficacy contributes to 14 % variance for performance, and its predictive power is greater than instruction (Zimmerman, 1995).
Schunk (1985) proposes a model of motivated learning and situates self-efficacy as both instrumental expectancies and cues (see figure 2).
Based on the social cognitive view of the triadic relation among personal, behavioral and environmental influences, a self-regulated academic learning model is proposed as an optimal learning process. Zimmerman (1989) positions self-observation,
42
self-judgment, and self-reaction as paramount in learning. Systemic monitoring of students’ own performance by either verbal reporting or written recording is influenced by self-efficacy, goal-setting, metacognitive planning and behavioral influences. When students compare and judge their performance with their goals, they rely on their self-efficacy and knowledge of standards. Students’ self-reactions involve responses to their own performance. These again could be related to students’ self-efficacy, goal setting, and behavioral outcomes. As students utilize self-efficacy in goal setting and strategy use, outcomes of the events tweak their later estimation of self-efficacy. The reciprocal nature of self-efficacy among other factors demonstrates its importance through the process.
Student Expectancies Task engagement Efficacy characteristics variables cues
Figure 2. A model of motivated classroom learning of cognitive skills (Schunk, 1985).
As the academic area offers contexts for standards, personal goals, and self-efficacy to take effect mutually, a cyclic model of self-regulated learning is promoted (see figure 3). In this model, students are encouraged to detect and evaluate their self-efficacy and then set specific learning goals by breaking tasks into smaller components.
Aptitude
43
The application of strategies is accompanied with constant self-monitoring to cope with intervening events. The final rating of self-efficacy following outcomes is vital in increasing future self-monitoring. When outcomes are compared with students’
estimation of self-efficacy, more realistic self-monitoring and self-efficacy evaluation arise (Zimmerman, Bonner & Kovach, 1996).
In Schunk’s (1985) motivated learning model, it is assumed that student characteristics, such as aptitudes toward the targeted subject or its prior learning experiences, would contribute to students’ expectations. Students’ self-efficacy as well as outcome expectancy, which is students’ beliefs concerning results of their actions, further influences students’ motivation. Self-efficacy conveys a sense of personal control during the cognitive processing. While engaging in tasks, educational practices provide salient cues for students to appraise their self-efficacy. Successful performance strengthens students’ self-efficacy while unsuccessful experiences reduce it. Students attribute their outcome to ability, effort, task difficulty, and luck, and these attributions affect efficacy appraisals. Situational circumstances contain situations when students attempt tasks with or without helps from others as well as students’ conditions such as fatigue, distractions, and physical illnesses. The pattern of success or failure could promote or demote students’ self-efficacy. When students see successful models and believe in those credible persuaders, their self-efficacy improves.
In social learning theory, self-regulation takes effect when students have firm believes about their capability to persist in the face of difficulties, stressors, or competing attractions. The higher their self-efficacy on regulating one’s own motivation and learning activities, the more their efficacy to master the targeted subjects.
High academic efficacy increases ultimate achievements and positive academic results strengthens self-efficacy (Bandura, 1995).
44
Figure 3. A cyclic model of self-regulated learning (Zimmerman, Bonner & Kovach, 1996. p.11).