Linking Mathematics Learning Growth and students' motivation characteristics
Author(s):
Conference:
ECER 2014
Format:
Paper

Session Information

09 SES 11 C, Developmental Trajectories of Attitudes and Competencies in the Course of Lower Secondary Education

Paper Session

Time:
2014-09-04
17:15-18:45
Room:
B009 Anfiteatro
Chair:
Tobias C. Stubbe

Contribution

Theoretical Background

Among the several factors associated to students’ achievement at school, the individual characteristics are considered as critical ones. Their source can be home, family, culture and community and they can be categorized in attitudes and dispositions, physical influences and attributes, preschool experiences and other background elements  (Hattie, 2009). The present work will focus on the association between learning growth and attitudes and dispositions, more specifically, academic self-efficacy, interest in mathematics, and perceived competence about mathematics.The academic self-efficacy is based on the general construct of self-efficacy, defined as “the belief in one’s capability to organize and execute courses of action required to produce desired attainments” (Bandura, 1986, p.391). Since the concept is sensitive to different contexts it must be specifically anchored to the domain or object of interest (Bandura, 1997), that is, in school contexts it needs to be focused to scholar tasks and be subject-specific as well.

The perceived ability or competence at school differs from self-efficacy, since it does not link the own perception with a potential success given certain abilities (Friedel, Cortina, Turner & Midgley, 2007). Interest refers to the importance, usefulness given to a school subject and it relation to positive emotions as well (Krapp, 1992).

There is evidence in support of the existence association between these students’ motivational variables and learning growth (e.g. Hattie, 2009; Greene et al, 1999; Pajares & Graham, 1999; Singh et al, 2002; Zimmerman, 1995). Nevertheless, there are some considerations that this work is intended to overcome. On one hand, the measures of achievement used have not been always standardized (e.g. Pajares & Graham, 1999) and on the other hand, covariables that impact achievement as well are not always available, such as teaching quality or socioeconomic status).

Research question

How are students' motivation characteristics associated with learning growth in mathematics in 7th graders when controlling for teaching quality and socioeconomic status?

Method

The data source of this paper are the participants of a broader study granted by: FONDECYT (Chilean Fund for development of science and technology) Nº 1120441, called “Validation of the Chilean national teacher evaluation system using student learning progress and in-depth examination of teaching practice,” 2012-2015. The sample is composed by 788 students’ and their teachers, belonging to 22 7th grade classes of public schools in Santiago de Chile, that participated in the study along the school year 2013 (between march and December). The students answered 2 questionnaires and 3 mathematics tests throughout the year. The student questionnaires included 3 scales measuring self-efficacy (7 items), perceived competencies (7 items) and interest (8) in mathematics. The internal consistency of the scales will be examined and items with a correlation item-scale below 0.25 will be excluded. The mathematics learning growth was measured with “SEPA” test, that is, a standardized mathematics curriculum-based instrument for 6th and 7th grade, that was applied at the beginning and at end of the school year. The quality of teaching was measured with the national teaching evaluation system scores, composed by 4 instruments, namely, a portfolio, peer interiview, self evaluation and principalo supervisor report. There are 4 variables related to socioeconomic status available in the students database, they will be tested in order to define which one best fits the model. Multilevel regressions will be performed using gender, socioeconomic status, motivational scales and prior achievement as predictors at student level. Since only one class participated representing each school, teaching quality will be used as predictor at classroom level. The dependent variable corresponds to the scores obtained by the students in the test at the end of the school year. The database will be clean in March 2014 and the analysis will be run at the end of the month.

Expected Outcomes

Expected findings According to the literature, students' motivation characteristics are expected to be related in a positive and significant way to learning growth. Nevertheless, since prior knowledge and socieconomic status are controlled, the effect is expected to be small. Since motivation variables are conceptually similar among each other, big differences between motivation scales are not expected. Regarding the other variables, according to the literatur, prior knowledge is expected to have the greatest impact on learning outcomes, followed by socieconomic status.

References

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Freeman. Friedel, J.M, Cortina, K.S, Turner J.C & Midgley, C. (2007). Achievemnt Goals, efficacy beliefs and coping strategies in mathematics: The role of perceived parent and teacher goal emphases. Contemporary Educational Psychology, 32, 434-458. Greene, B. A., DeBacker, T. K., Ravindran, B., & Krows, A. J. (1999). Goals, values, and beliefs as predictors of achievement and effort in high school mathematics classes. Sex Roles, 40(5),421–458. Hattie, J. (2009). Visible learning. A synthesis of over 800 meta-analyses relating to achievement. New York: Routledge. Krapp, A. (1992) Das Interessenkonstrukt: Bestimmungsmerkmale der Interessenhandlung und des individuelles Interesses aus der Sicht einer Person-Gegenstand-Konzeption. In A. Krapp & M. Prenzel (Eds). Interesse, Lernen, Leistung (pp. 297-329) Münster Aschendorff. Pajares, F., & Graham, L. (1999). Self-efficacy, motivation constructs, and mathematics performance of entering middle school students. Contemporary Educational Psychology, 24, 124–139. Schunk, D. H. (1996). Goal and self-evaluative influences during children’s cognitive skill learning. American Educational Research Journal, 33(2), 359–382. Singh, K., Granville, M., & Dika, S. (2002). Mathematics and science achievement: Effects of motivation, interest, and academic achievement. Journal of Educational Research,95(6),323–332. Skaalvik, E., & Skaalvik, S. (2008). Self-concept and self-efficacy in mathematics: Relation with mathematics motivation and achievement. In F.M. Olsson (Ed.), New developments in the psychology of motivation (pp. 105–128). Hauppauge, NY: Nova Science Publishers. Zimmerman, B.J. (1995). Self-efficacy and educational development. In A. Bandura (Ed.), Selfefficacy in changing societies (pp. 202–231). New York, NY: Cambridge University Press.

Author Information

Daniela Jiménez (presenting / submitting)
MIDE UC
Research Area
Santiago
MIDE UC y Facultad de Matemáticas, Universidad Católica de Chile

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