Session Information
09 SES 14 B, Exploring Factors Influencing Motivation, Engagement, and Attitudes in Education
Paper Session
Contribution
Mathematics is perceived by many students as a particularly difficult subject, and many tend to experience higher levels of anxiety in relation to mathematics compared to other subjects (Goetz et. al., 2007). At the same time, mathematical competencies are fundamental to several aspects of contemporary society (OECD, 2013). Fostering motivation is therefore important for supporting students who experience difficulties in mathematics, especially since motivation is a driving force for learning mathematics over time (Wigfield et al., 2016). A number of studies have shown a positive relationship between motivation and achievement in mathematics, regardless of theoretical approach (e.g., Kriegbaum et. al., 2018; Prast et. al., 2018). Students who are motivated also tend to engage more in mathematical activities because they find them enjoyable and interesting (Eccles & Wigfield, 2004), and the development of motivation for mathematics during elementary school is related to the choice of mathematics-intensive careers (Musu-Gillette et. al., 2015).
One of the most important theories of motivation for mathematics is the Expectancy Value Theory of Motivation (EVM) proposed by Eccles, Wigfield, and colleagues. According to EVM, motivation is a function of a person's expectancy of success and the value they place on the task. Expectancy of success refers to a person's belief in his/her own ability to to successfully complete a task, and value refers to the importance or relevance of the task to the person's goals or interests. Students with a higher expectancy of success and a higher value placed on mathematics tend to have higher motivation and achievement in mathematics (Wigfield et. al., 2016).
Another theory relevant to motivation is Dweck's (1995) theory of implicit intelligence. The theory states that individuals can have implicit beliefs about the nature of intelligence that can be either fixed or malleable. People with a fixed mindset believe that intelligence is not changeable, whereas people with a growth mindset believe that intelligence can be developed through effort and learning. Students' implicit beliefs about intelligence are related to both academic achievement and motivation (e.g., Song et al., 2022), implying that students with a growth mindset tend to develop several adaptive academic behaviors, such as higher motivation and achievement, than those with a fixed mindset (Yeager and Dweck, 2012).
Wigfield et al. (2004) hypothesized that Dweck's theory of implicit intelligence is related to EVM in that individuals who believe their abilities cannot be improved through effort will not engage in activities they believe they are not very good at. However, few studies have examined how such motivational beliefs are formed in children. Eccles and Wigfield (2020) proposed in their situated expectancy-value theory (SEVM) that beliefs and values are also shaped by social context, such as family, peers, and culture. In a study of how parental beliefs about fixedness of ability affect interactions with their children, Muenks et al. (2015) found that parents with fixed mindsets engaged in more controlling and achievement-oriented behaviors and were less likely to engage in math-related activities with their children. Although few studies have examined how parents' mindset affects their children's motivation, a study by Song et al. (2022) showed that children reported having greater self-reported persistence when their parents had more growth mindset. Xie et al. (2022) also found that parents' mindset indirectly predicted math anxiety through their failure beliefs.
Thus, the present study aims to investigate the role of parents' beliefs about mathematical ability, i.e., their fixed or growth mindset, in fostering student motivation. Specifically, we focus on parents' beliefs of mathematical ability as innate or malleable, and whether and how parents' mindsets affect students' self-concepts about their ability, value, and achievement of mathematics.
Method
Participants Participants were about 600 elementary school students in grade 3 and 4 and their parents. Both children and parents participated in a larger study examining the development of motivation for mathematics in the elementary school classrooms. Parental informed consent was obtained for each student participating in the study. Instrument and procedures Motivation was assessed using an instrument based on the Expectancy-Value Motivation Scale (EVMS), which included a total of 34 items in five dimensions: Competence Self-beliefs (6 items, e.g., Math is easy for me), Intrinsic Value (8 items, e.g., I like doing math), Achievement Value (7 items, e.g., Being good at math is very important to me personally), Utility Value (7 items, e.g., What I learn in math I can use in my daily life), and Cost (6 items, e.g., Doing math problems keeps me from doing other things I like). All items were answered on a 4-point scale ranging from 'a lot of times' to 'never." In a validation study, the scale was found to be appropriate for early elementary grades and to have a good model fit consistent with expectancy- value theory. The different EVS dimensions also showed good reliability (Peixto et al., 2022). Parents' mindset was measured by eight items on their beliefs about mathematical ability as innate or malleable. 4 items were used to measure fixed mindset (e.g. Math ability is innate) and 4 items were used to measure growth mindset (e.g., a Child's ability in math can be improved with practise). Responses were given on a 4-point scale ranging from 'disagree' to 'agree." Socioeconomic background was measured by parental education level. The instruments were developed in English and translated into Swedish. Translation and back-translation procedures were used, and no discrepancies were found. The EVMS instrument was distributed in grades 3 and 4 in Sweden in spring 2022 as part of a larger study. Administration was done at school by trained research assistants using pen and paper questionnaires. Parents received a QR code and answered a digital questionnaire. Analytic Method Structural equation modelling (SEM) will be used to examine the relationship between parents' mindset and children's self-concept of ability, values, and achievement in mathematics. A path model will be estimated to examine the mechanisms between parents' fixed or growth mindset and children's self-concept of ability, value of mathematics, and achievement in mathematics according to the SEVM model of Wigfield and Eccles (2020).
Expected Outcomes
It is expected that parents’ fixed intelligence beliefs will negatively affect their children’s competence self-beliefs, which in turn will affect both attainment value, intrinsic value, and achievement. However, it is also possible that parents’ mindset directly affects achievement. Based on the findings of Song et al. (2022), it is also expected that the effect of parents' mindset is partially mediated by their socioeconomic background, implying that parents with lower socioeconomic backgrounds are more likely to have fixed mindset.
References
Dweck, C. S., Chiu, C.-y., & Hong, Y.-y. (1995). Implicit theories and their role in judgments and reactions: A world from two perspectives. Psychological Inquiry, 6(4), 267–285. https://doi.org/10.1207/s15327965pli0604_1 Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A developmental, social cognitive, and sociocultural perspective on motivation, Contemporary Educational Psychology, 61. https://doi.org/10.1016/j.cedpsych.2020.101859. Goetz, T., Frenzel, A. C., Pekrun, R., Hall, N. C., & Lüdtke, O. (2007). Between- and within-domain relations of students' academic emotions. Journal of Educational Psychology, 99(4), 715–733. https://doi.org/10.1037/0022-0663.99.4.715 Kriegbaum, K., Becker, N., & Spinath, B. (2018). The relative importance of intelligence and motivation as predictors of school achievement: A meta-analysis. Educational Research Review, 25, 120-148. Musu-Gillette, L.E., Wigfield, A., Harring, J.R., & Eccles, J.S. (2015). Trajectories of change in students’ self-concepts of ability and values in math and college major choice. Educational Research and Evaluation, 21(4), 343-370. https://doi.org/10.1080/13803611.2015.1057161 OECD (2013). PISA 2012 Assessment and Analytical Framework: Mathematics, Reading, Science, Problem Solving and Financial Literacy, Paris: OECD Publishing. Peixoto, F., Radišić, J., Krstić, K., Hansen, K. Y., Laine, A., Baucal, A., Sõrmus, M., & Mata, L. (2022). Contribution to the Validation of the Expectancy-Value Scale for Primary School Students. Journal of Psychoeducational Assessment, 0(0). https://doi.org/10.1177/07342829221144868 Prast, E., Van de Weijer-Bergsma, E., Miočević, M., Kroesbergen, E., & Van Luit, J. (2018). Relations between mathematics achievement and motivation in students of diverse achievement levels. Contemporary Educational Psychology, 55, 84-96. Song, Y., Barger, M. M., & Bub, K. L. (2022). The Association Between Parents’ Growth Mindset and Children’s Persistence and Academic Skills. Front. Educ, 6. https://doi.org/10.3389/feduc.2021.791652 Wigfield, A., Tonk, S., & Eccles, J. S. (2004). Expectancy value theory in cross-cultural perspective. In D. M. McInerney & S. Van Etten (Eds.), Big theories revisited (pp. 165-198). Greenwich, CO: Information Age Publishing. Wigfield, A., Tonks, S., & Klauda, S. L. (2016). Expectancy-value theory. In K. R. Wentzel & A. Wigfield (Eds.), Handbook on motivation in school (2nd ed., pp. 55–76). New York: Routledge. Xie, F., Duan, X.F., Ni, X.L., Li, L.N., & Zhang, L.B. (2022). The Impact of Parents’ Intelligence Mindset on Math Anxiety of Boys and Girls and the Role of Parents’ Failure Beliefs and Evaluation of Child’s Math Performance as Mediators. Front. Psychol, 13. https://doi.org/10.3389/fpsyg.2022.687136 Yeager, D. S., & Dweck, C. S. (2012) Mindsets That Promote Resilience: When Students Believe That Personal Characteristics Can Be Developed, Educational Psychologist, 47(4), 302-314. https://doi.org/10.1080/00461520.2012.722805
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