The Association between Mathematics Self-Efficacy Beliefs and Self-Regulated Learning Strategies of Middle School Students
Author(s):
Başak Çalık (presenting / submitting) Yeşim Çapa Aydın (presenting)
Conference:
ECER 2017
Format:
Paper (Copy for Joint Session)

Session Information

Joint Paper Session NW 24 and NW 31

Time:
2017-08-24
17:15-18:45
Room:
K6.04
Chair:
Javier Diez-Palomar

Contribution

Social Cognitive Theory deals with people’s knowledge, skills, strategies, beliefs, and emotions based on their interactions with and observation of others (Pintrich & Schunk, 2002).  Self-efficacy as an affective construct is described in this theory, “the beliefs in one’s capabilities to organize and execute the courses of action required producing given attainment”(Bandura, 1997, p.3). Considering the domain specific nature of the construct, mathematics self-efficacy is defined as “a situational or problem-specific assessment of an individual's confidence in her or his ability to successfully perform or accomplish a particular task or problem” (Hacket & Betz, 1989, p.262).

On the other hand, self-regulation is concerned as an interaction between personal, behavioral, and environmental triadic processes (Zimmerman, 2000). The link between these factors implies the cyclical structure of self-regulation. Of the three factors, self-regulated learning is previewed under the personal influences involving self-efficacy perceptions of individuals depending on their knowledge, metacognitive processes, goals, and affect. Zimmerman (1989) contended that students are self-regulated if they use specific strategies to obtain desired goals based on their perceived level of self-efficacy. Learning strategies are defined as “behaviors and thoughts in which a learner engages and which are intended to influence learners’ encoding process” (Weinstein & Mayer, 1983, p. 3). Individuals’ affective states, ways of knowledge selection, and organization are influenced by these strategies. In this manner, self-regulated learners are active on the learning process metacognitively, motivationally, and behaviorally by directing their efforts to gain knowledge and skills instead of being passive receivers of information (Zimmerman, 1989). Actually, cognitive and metacognitive strategy use of students is important in classroom settings (Zimmerman & Martinenz- Pons, 1986).

Pintrich and De Groot (1990) examined the relation between motivational orientations, self-regulated learning and performance of seventh grade students in English and science classes. Self-efficacy was one of the motivational orientations of individuals while self-regulated learning was implied through measuring cognitive and metacognitive strategies. Findings of the study revealed that self-efficacy was positively related to cognitive (r = .33) and metacognitive strategy use (r = .44). Gholomoli Lavasani, Mirhosseini, Hejazi and Davodi (2011) reported the positive impact of the training of self-regulated learning strategies on fifth graders’ academic motivation and self-efficacy beliefs. Ocak and Yamaç (2013) investigated the predictive and explanatory relationship among fifth graders’ motivational beliefs including self-efficacy, cognitive and meta-cognitive self-regulation, their attitude toward mathematics and mathematics achievement. Self-efficacy beliefs of students were found to be the positive predictor of their cognitive and meta-cognitive strategy use. As self-efficacy is domain- and task-specific, examining the nature of relationship between mathematics self-efficacy and self-regulated learning strategies would be more practical and meaningful to help educators to arrange learning and teaching environments as students experience less enjoyment and interest in mathematics compared to other subject domains (Tulis & Ainley, 2011). Hence, the current study investigates whether there is a relationship between mathematics self-efficacy beliefs and self-regulated learning strategies of middle school students considering the grade levels. The learning strategy use was contended to be different based on the culture, grade level and subject areas (Purdie & Hattie, 1996). Thus, this study will provide an opportunity to examine the nature of the relationship between two major constructs in a different culture and learning environment. 

Method

The study utilized correlational design, in which data were collected from 2,250 middle school students selected from fourteen schools located in four central districts of Ankara, Turkey. In the sample, there were 1.164 female (51.7%) and 1.085 male students (48.2%). Moreover, 690 students were from sixth grade (30.7%), 772 students were from seventh grade (34.3%), and 784 of them were from eighth grade (34.8%). Data collection instruments were Math Skills Self-Efficacy Scale (MSSE; Usher, 2007), Self-Efficacy for Self-Regulated Learning Scale (SESRL; Usher, 2007), and Self-Regulated Learning Strategies subscale of Motivated Strategies for Learning Questionnaire (MSLQ: Pintrich et al. 1991). MSSE scale measures middle school students’ beliefs in their capabilities to solve mathematical problems. It includes 24 items on a 100-point rating scale. The sample item can be given as “How confident are you that you can successfully solve math exercises involving rounding and estimating?” SESRL scale, comprising of 11 items on a 6-point rating scale, assesses students’ judgments in their capabilities to use self-regulated learning strategies in mathematics. The sample item reads “How well can you participate in math class?” Cognitive and metacognitive strategies of middle school students were measured by Learning Strategies section of MSLQ. There are five dimensions with 50 items in this section: rehearsal, elaboration, organization, critical thinking, and metacognitive self-regulation. The scale was designed as a 7-point rating scale from 1 (not at all true of me) to 7 (very true of me). Confirmatory factor analyses (CFA) were conducted to test the factorial structure of each scale and yielded satisfactory fit indices. Besides, the reliability estimates of each scale for the present study were found as .93 for SESRL, .96 for MSSE, and ranging from .79 to .92 for each dimension of the Learning Strategies Section of MSLQ.

Expected Outcomes

Canonical correlation was performed to investigate the relationship between two sets of variables. The first set included mathematics skills self-efficacy and self-efficacy for self-regulated learning while the second set consisted of rehearsal, elaboration, critical thinking, organization, and metacognitive self-regulation strategies. According to the results, the first solution was considered for interpretation since the first canonical pair (Rc = .78) was above .30 and accounts for more than 10% overlapping variance (Sherry & Henson, 2005; Tabachnick & Fidell, 2013). Accordingly, mathematics skills self-efficacy and self-efficacy for self-regulated learning variables in the first set and cognitive and metacognitive strategy use variables in the second set were positively correlated with the first canonical variate. In other words, higher levels of mathematics skills self-efficacy and self-efficacy for self-regulated learning are associated with greater use of rehearsal, elaboration, critical thinking, organization and metacognitive strategy use variables. Furthermore, 85% of variance was explained by mathematics self-efficacy variable set while 83% of variance was accounted by self-regulated learning strategies set. Similar findings were obtained when canonical correlation analyses were performed with respect to grade levels. Producing one significant canonical solution, again all variables were meaningful and positively related for sixth, seventh, and eighth grade students (with the cut of value of .30, Tabachnick & Fidell, 2013). Namely, those with higher levels of math skills self-efficacy and self-efficacy for self-regulated learning were correlated with greater use of self-regulated learning strategies. Moreover, 86%, 86%, and 83% of variances were explained by math self-efficacy; while 84%, 81% and 84% of variances were accounted by learning strategy variate for the sixth, seventh, and eighth grades, respectively.

References

SELECTED REFERENCES Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Gholomali Lavasani, M. , Mirhosseini, F. S., Hejazi, E. & Davoodi, M. (2011). The effect of self-regulation learning strategies training on academic motivation and self-efficacy. Procedia-Social and Behavioural Sciences, 29, 627-632. Hackett, G. & Betz, N. E. (1989). An exploration of mathematics self-efficacy mathematics performance. Journal of Research in Mathematics Education, 20(3),261-273. Pintrich, P. R. & De Groot, E. V. (1990). Motivational and self regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40. Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire(MSLQ).Ann Arbor, MI: National Centre for Research to Improve Postsecondary Teaching and Learning, The University of Michigan. Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications. Englewood Cliffs, NJ: Prentice Hall. Purdie, N., & Hattie, J. (1996). The relationship between study skills and learning outcomes: A meta-analysis. Australian Journal of Education, 43, 72-86. Sherry, A. & Henson, R. K. (2005). Conducting and interpreting canonical correlation analysis in personality research: a user-friendly primer. Journal of Personality Assessment, 84 (1), 37-48. Tulis, M. &Ainley, M. (2011). Interest, enjoyment and pride after failure experiences? Predictors of students’ state-emotions after success and failure during learning in mathematics. Educational Psychology: An International Journal of Experimental Psychology, 31(7), 779-807. Usher, E. L. (2007). Tracing the origins of confidence: A mixed methods exploration of the sources of self efficacy in mathematics. (Unpublished Dissertation). Emory University, US. Weinstein, C. E.& Mayer, R. E. (1983). The teaching of learning strategies. Innovation Abstracts, 5(32). Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13-40). San Diego, California: Academic Press.

Author Information

Başak Çalık (presenting / submitting)
Middle East Technical University, Turkey
Yeşim Çapa Aydın (presenting)
Middle East Technical University, Turkey

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