Session Information
09 SES 04 B, Exploring Educational Dynamics and Academic Performance
Paper Session
Contribution
Metacognition or metacognitive skills refer to students’ “understanding and control of their own cognition” (Sternberg, 2007, p. 18). Metacognition or knowledge about thinking includes declarative, procedural, and conditional knowledge (McCormick, 2003). Students who have well developed metacognitive skills tend to thrive academically. For example, research shows that systematic metacognitive monitoring leads to better understanding and academic performance (Zimmerman & Cleary, 2009). However, many studies in education report on low to medium associations between metacognition and academic achievement (Fleur et al., 2021; Winne & Azevedo, 2022).
Self-efficacy is another construct that relates to academic achievement across educational settings and age groups (DiBenedetto & Schunk, 2022). Self-efficacy refers to students’ beliefs that they can successfully tackle a task (Anderman & Wolters, 2008; Bandura, 2006). Students’ self-efficacy is related to their engagement with a task and the types of strategies they use (Bandura, 1994). Years of research indicate that self-efficacy relates to students’ learning, motivation, achievement, and self-regulated learning (DiBenedetto & Schunk, 2022). High self-efficacy is a strong predictor of students’ achievement and success (DiBenedetto & Schunk, 2022) and strongly relates to academic achievement for middle school students (Carpenter, 2007).
Available research studies suggest positive yet small correlations between metacognition and general and domain-specific self-efficacy (Cera et al., 2013; Ridlo & Lutfia, 2016). In addition, metacognitive scaffolding improved metacognitive awareness, academic self-efficacy, and learning achievement of biology students (Valencia-Valejo et al., 2019). Research evidence from other countries provides support in positive relationships among metacognition, self-efficacy, and academic achievement. However, it is not clear how these constructs relate to each other in other contexts such as Russia. Therefore, the goal of this study is to examine the role of metacognitive skills and self-efficacy in predicting middle school students’ academic results.
Theoretical framework
The role of metacognition and self-efficacy in students’ academic results in this study is examined through a Model of Self- and Socially Regulated Learning (Author). The model is organized around three broad areas: self-regulated learning (SRL; C–I, M–N), socially regulated learning (SoRL; A–B, J–N), and culture (O). Each area has its own set of processes contributing to the development of self-/socially regulated skills. Thus, SoRL includes instructional techniques (A–B) and formative assessment practices, such as feedback, which occur in classrooms (J–N). SRL includes the processes that activate student’s background knowledge and motivational beliefs, which lead to the choice of goals and strategies to do the task (C–I, M–N). Finally, culture (O) situates both types of processes within a socio-cultural context.
This model reflects the complexity of school classrooms and includes a number of variables. In this paper, however, the focus is on such components of SRL as metacognition and self-efficacy. For the purposes of this study, metacognition includes the processes of planning, progress monitoring, and reflection. According to Albert Bandura (2006), self-efficacy is domain-specific, whichis why separate self-efficacy scales were developed for each of the domains. The main purpose of this study was to examine the role of metacognition and self-efficacy in predicting middle school students’ academic results. The study addresses the following research questions:
- Are there differences in middle school students’ metacognitive skills, self-efficacy, and academic results by gender and grade?
- Do metacognition and self-efficacy predict students’ academic results by subject domains?
Method
This study employed a cross-sectional survey design. Sample. The sample included 1,167 students (55.3% girls, n = 645) from seventh (n = 345), eights (n = 514), and nineth (n = 308) grades. Instruments. The metacognition subscale is an adaptation from the SRL survey for DAACS (Lui et al., 2018). It includes the subscales of planning (5 items), monitoring (6 items), and reflection (7), using a Likert-type scale (4 – almost always, 1 – almost never), indicating good internal consistency estimate for the scale (α = 0.92; ω = 0.93). Example item: “I plan when I am going to do my homework”. The self-efficacy surveys for mathematics (4 items, α = 0.85, ω = 0.9), Russian (4 items, α = 0.79, ω = 0.85), reading (4 items, α = 0.84, ω = 0.86), foreign language (5 items, α = 0.93, ω = 0.94), biology (4 items , α = 0.87, ω = 0.9), and physics (5 items, α = 0.93, ω = 0.95) used a Likert-type scale (4 – I can do it well, 1– I cannot do it at all) with good reliability estimates. An example item: “Can you solve a math problem?”. Procedures. After receiving approval from the Ethics Committee, the data were collected online in public schools. Parents signed online consent forms, and children provided their assent to participate. The data analyses were conducted in R Studio. Results RQ1: While no differences were observed for planning and reflection, girls showed higher scores for monitoring than boys, t = 2, df = 1090.6, p = 0.04, d = 0.12. No differences were observed in self-efficacy for math, reading, foreign language, and biology. However, girls had higher self-efficacy for Russian, t = 7.81, df = 1023.6, p < 0.0001, d = 0.47. Boys had higher self-efficacy for physics, t = -3.72, df = 1095.9, p < 0.001, d = 0.22. Girls reported higher scores across all subjects than boys. Examination by grade levels revealed that students form the 9th grade had higher estimates for planning, reflection, and self-efficacy across most subjects than students from the 7th and 8th grades. RQ2: Linear regression analyses revealed that planning predicted students’ scores in foreign language and biology, and reflection predicted scores for foreign language and physics. For all other subjects, contributions of metacognition were not significant. In contrast, self-efficacy significantly predicted scores for all subjects, explaining between 16% and 32% of variance in scores.
Expected Outcomes
This paper examined the role of metacognition and self-efficacy in predicting middle school students’ academic results. The group comparison results revealed that girls had higher scores in metacognitive monitoring than boys. No differences were observed for metacognitive planning and reflection. Also, girls indicated higher self-efficacy in Russian and boys higher self-efficacy in physics. These results are partially in line with research studies, showing gender differences with boys scoring higher in mathematics (Breda & Napp, 2019) and research on perceived self-efficacy (Pajares & Valiante, 2002). Students from the 9th grade seemed to have higher scores for planning, reflection, and self-efficacy across all subjects. Ninth grade is considered a final grade of the middle school in Russia and students take the final examination, and then decide if they continue in high school or switch to other educational institutions. In 9th grade, students’ abstract thinking and analysing skills necessary to reflect on behaviours and emotions are developed enough to engage in metacognitive thinking (Uytun, 2018). The results of the regression analysis indicated that metacognition was not as strong in predicting students’ scores in respective subjects as self-efficacy. However, planning and reflection contributed to scores in foreign language, biology, and physics. These results support research studies reporting weak and moderate relationships of metacognition with academic results (Cera et al., 2013; Ridlo & Lutfia, 2016) and significant contributions of self-efficacy to academic achievement (DiBenedetto & Schunk, 2022). The scholarly significance of this study is that it examined the relationships among metacognition, self-efficacy by domains, and academic achievement of middle school students, using a relatively large sample in Russia. It provides evidence of the links between students perceived self-efficacy beliefs and their results in subject domains, and positive role of planning and reflection for some subjects.
References
Anderman, E. M., & Wolters, C. A. (2008). Goals, values, and affect: Influences on student motivation. In P. A. Alexander and P. H. Winne (Eds.), Handbook of educational psychology, 369–390, 2nd ed. Lawrence Erlbaum Associates Publishers. Bandura, A. (2006). Toward a psychology of human agency. Perspectives on psychological science, 1(2), 164-180. Breda, T. & Napp, C. (2019). Girls’ comparative advantage in reading can largely explain the gender gap in math-related fields.” Proceedings of the National Academy of Sciences, 116(31), 15435-15440. https://doi.org/10.1073/pnas.1905779116 Carpenter, S. L. (2007). A comparison of the relationships of students' self-efficacy, goal orientation, and achievement across grade levels: a meta-analysis. https://summit.sfu.ca/_flysystem/fedora/sfu_migrate/2661/etd2816.pdf DiBenedetto, M. K., & Schunk, D. H. (2022). Assessing academic self-efficacy. In M. S. Khine and Tine Nielsen (Eds.), Academic Self-Efficacy in Education: Nature, Assessment, and Research 11-37. Springer. Cera, R., Mancini, M., & Antonietti, A. (2013). Relationships between metacognition, self-efficacy and self-regulation in learning. Journal of Educational, Cultural and Psychological Studies (ECPS Journal), 4(7), 115-141. Fleur, D.S., Bredeweg, B. & van den Bos, W. Metacognition: ideas and insights from neuro- and educational sciences. npj Sci. Learn. 6, 13 (2021). https://doi.org/10.1038/s41539-021-00089-5 McCormick, C. B. (2003). Metacognition and learning. In W. M. Reynolds & G. E. Miller (Eds.), Handbook of psychology: Educational psychology (Vol. 7, pp. 79-102). John Wiley & Sons Inc. Pajares, F., & Valiante, G. (2002). Students’self-efficacy in their self-regulated learning strategies: a developmental perspective. Psychologia, 45(4), 211-221. Ridlo, S., & Lutfiya, F. (2017, March). The correlation between metacognition level with self-efficacy of biology education college students. In Journal of Physics: Conference Series (Vol. 824, No. 1, p. 012067). IOP Publishing. Sternberg, R. J. (2007). Intelligence, competence, and expertise. In A. J. Elliot, & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 15–30). The Guilford Press. Uytun, M. C. (2018). Development period of prefrontal cortex. In A. Starcevic and B. Filipovic (Eds.), Prefrontal Cortex. IntechOpen. DOI: 10.5772/intechopen.78697 Valencia-Vallejo, N., López-Vargas, O., & Sanabria-Rodríguez, L. (2019). Effect of a metacognitive scaffolding on self-efficacy, metacognition, and achievement in e-learning environments. Knowledge Management & ELearning, 11(1), 1–19. https://doi.org/10.34105/j.kmel.2019.11.001 Winne, P., & Azevedo, R. (2022). Metacognition and self-regulated learning. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences, 93-113. Cambridge University Press. Zimmerman, B. J., & Cleary, T. J. (2009). Motives to self-regulate learning: A social-cognitive account. In K. Wentzel, & A. Wigfield (Eds.), Handbook on Motivation at School. Taylor & Francis.
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