11 SES 13, Teaching and Cognitive Development
Social cognition has traditionally been defined in terms of processes by which an individual to monitor oneself, understand others, and control the interaction between self and others (Lieberman, 2007). However, increasing attention has been directed to the actions taken to mentalize (i.e., to infer other people’s mental states), the so-called theory of mind (Blakemore, Boyer, Pachot-Clouard, Meltzoff, Segebarth, & Decety, 2003), with particular emphasis on metacognition, that is, knowledge of the self. Theory of mind plays a critical role in building successful social interaction as it allows one to understand the intentions of others’ behavior and to predict forthcoming behavior (Brown, Tas, Gonzalez, & Brüne, 2014). These skills are important for undergraduate students as it can help them to manage their emotions, relationships, and to learn self-control within the university life (Pintrich, 2004). Along this continuum, metacognition sets the stage for individuals to reflect upon, understand, monitor, and control their own cognitive processes. In relation to social cognition, metacognition includes everything one knows about the mental states and processes of one’s self and others such as intraindividual (e.g., I learn better by listening than reading) and interindividual (e.g., My friend is better in algebra than geometry) differences (Corkill, 1996). The implication is that good metacognition leads to effective interpretation of the mental and physical world or vice versa. Research supports the significant relationship between social cognition and metacognition (Sperling, Walls, & Hill, 2000) as well as the role of metacognition as a key determinant of learning and achievement (Van der Stel & Veenman 2010). Fewer studies have looked at the relations between social cognition and learning, yet they confirm the beneficent effects of effective theory of mind in infants and young children (Wang, 2015). Researchers documented that children with more advanced mental state understanding demonstrated more advanced learning skills (e.g., language acquisition; math and literacy ability) compared to children with low mental state understanding (Blair & Razza, 2007). Social cognition and metacognition can, therefore, bring together experiences that interactively contribute to academic performance.
Within this framework, the primary aim of the present study will be to examine the causal relations between social cognition, metacognition, and academic performance. In particularly, we focus on links between social cognition and the two components of metacognition: knowledge of cognition and regulation of cognition. An additional goal will be to consider the broader links that social and metacognitive variables might have with grade point average (GPA) as an index of academic performance. This study will be the first to establish the joint relationships among social cognition, and metacognition, along with highlighting links to academic performance. In doing so, the findings will provide support for the consistently found relations between effective social cognition and metacognition on the one hand, and between metacognition and academic performance on the other hand (e.g., Sperling et al., 2000).
To provide a broader understanding of this phenomenon, this study will examine the links between social cognition, metacognition, and academic performance by testing path models whereby social cognition contributes to knowledge of cognition and regulation of cognition. Additional links with academic achievement will be examined. The present study will test the following hypotheses (see Figure1):
(1) Social cognition indirectly and positively predicts academic performance via its positive associations with knowledge of cognition and regulation of cognition.
(2) Knowledge of cognition and regulation of cognition directly and positively predicts academic performance.
Knowledge of Cognition
Regulation of Cognition
Figure 1.Hypothesized path model.
Methodology Participants The study will contain cross-sectional data from Turkish undergraduates, who is majoring in mathematics education, science education, early childhood education, and classroom teaching at Faculty/School/College of Education in a public university. Metacognitive Awareness Inventory (MAI). The 52-item MAI, originally, developed by Schraw and Dennison (1994), and adapted into Turkish by Akın, Abacı, & Çetin (2007). It includes two subscales: Knowledge of cognition (“I understand my intellectual strengths and weaknesses.”) and Regulation of cognition (“I consider several alternatives to a problem before I answer.”). The items were rated on a 5-point scale (1= absolutely inappropriate to 5= absolutely appropriate). The Turkish version of the MAI demonstrated adequate internal reliability and three-week test-retest reliability (α= .95 and α= .95, respectively) (Cohen, 1988). Reading the Mind in the Eyes Test (RMET). The RMET, originally developed by Baron-Cohen, Wheelwright, Hill, Raste, & Plumb (2001), and adapted into Turkish by Yıldırım, Kasar, and Güdük (2011) includes 32 items with still pictures of the eye regions illustrating emotionally charged or neutral mental states. Students respond to each item by matching among four descriptive words of a mental state (e.g., ‘serious’, ‘ashamed’, ‘alarmed’, and ‘bewildered’). Each test picture is scored 1 (correct) and 0 (incorrect). The total score on the RMET ranges from 0 to 32 (0= low social cognition; 32= high social cognition). The Turkish version of the RMET demonstrated adequate internal reliability with Kuder-Richardson 20 coefficient (.72) and acceptable test-retest reliability with an Intraclass Correlation Coefficient (.65) (Cohen, 1988). Academic performance. The GPA, which was figured by dividing the grade points earned by the number of credits attempted in the previous semester, will serve as an indicator of students’ current academic achievement at the university (0= very poor performance; 100= excellent performance). Statistical Analysis Path analyses using LISREL 9.2 program (Jöreskog & Sörbom, 1993) will be performed to examine if the hypothesized model fits the data. First, the complete hypothesized model (see Figure 1) will be tested, including social cognition, the two components of metacognition and their connection with academic performance. This model will be considered as the baseline, target model in the analyses. Regarding the modification suggestions, the baseline model, including both direct and indirect effects, will be tested against alternative models. To decide which model is better, at least empirically, model comparisons will be performed using the chi-square difference test.
Results Major findings from the model will indicate that (1) social cognition indirectly and positively effects academic performance via knowledge of cognition, (2) social cognition indirectly and positively effects academic performance via regulation of cognition and regulation of cognition, (3) knowledge of cognition has a positive direct effect on academic performance, and (4) regulation of cognition has a positive direct effect on academic performance.
Akın, A., Abacı, R., & Çetin, B. (2007). The validity and reliability of the Turkish version of the metacognitive awareness inventory. Educational Sciences: Theory & Practice, 7(2), 671-678. Baron-Cohen, S., Wheelwright, S., Hill, J., Raste, Y., & Plumb, I. (2001). The “Reading the Mind in the Eyes” Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 42(2), 241-251. Blair, C., & Razza, R. P. (2007). Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Development, 78(2), 647–663. Blakemore, S. J., Boyer, P., Pachot-Clouard, M., Meltzoff, A., Segebarth, C., & Decety, J. (2003). The detection of contingency and animacy from simple animations in the human brain. Cerebral Cortex, 13(8), 837–844. Brown, E. C., Tas, C., Gonzalez, C., & Brüne, M. (2014). Neurobiologic underpinnings of social cognition and metacognition in schizophrenia spectrum disorders. In P. Lysaker, G. Dimaggio, & M. Brüne (Eds.), Social cognition and metacognition in schizophrenia: Psychopathology and treatment approaches (pp. 1–18). Elsevier. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum. Corkill, A. J. (1996). Individual differences in metacognition. Learning and Individual Differences, 8(4), 275-279. Jöreskog, K., & Sörbom, D. (1993). Structural equation modeling with the SIMPLIS command language. Hillsdale, NJ: Lawrence Erlbaum Associates. Lieberman, M. D. (2007). Social cognitive neuroscience: A review of core processes. Annual Review of Psychology, 58, 259–289. Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385-407. Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460–475. Sperling, R. A., Walls, R. T., & Hill, L. A. (2000). Early relationships among self-regulatory constructs: Theory of mind and preschool children’s problem solving. Child Study Journal, 30(4), 233–252. Van der Stel, M., & Veenman, M. V. J. (2010). Development of metacognitive skillfulness: a longitudinal study. Learning and Individual Differences, 20(3), 220–224. Wang, Z. (2015). Theory of mind and children’s understanding of teaching and learning during early childhood. Cogent Education, 2(1), 1-10. Yıldırım, E. A., Kasar, M., & Güdük, M. (2011). Investigation of the Reliability of the ‘Reading the Mind in the Eyes Test’ in a Turkish Population. Turkish Journal of Psychiatry, 22(3), 177-186.
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