Session Information
24 SES 04, Patterns of Goal Orientations and Anxiety
Paper Session
Contribution
Math anxiety, one of the major affective factors affecting mathematics learning and teaching, (McLeod, 1992) may prevent individuals from learning mathematics (Bai, Wang, Pan, & Fray, 2009; Bai, 2011; Cates & Rhymer, 2003). Therefore, it is necessary to understand math anxiety for controling its effects on mathematics learning process. Since mathematics anxiety affects academic achievement of the students in a short term, and also it causes students to avoid mathematics learning in a long term (Richardson & Suinn, 1972). Researchers examined students' math anxiety in terms of different variables (e.g. gender, level of schooling parents’ effects, learning environment) (Dowker, Sarkar, & Looi, 2016; Hill, et al., 2016; Ng, 2012). Besides, researches have examined the relationship between learning styles and math anxiety (Banaga, 2018). However, there is no study investigating the relationship between mathematical thinking styles and anxiety. However, one of the factors influencing students' learning mathematics is their mathematical thinking styles. Akçakın and Kaya (2018) found that students' mathematical achievements differ according to their mathematical thinking styles. Borromeo-Ferri (2010) states that students show different approaches in mathematical thinking process; in other words, each student has a unique mathematical thinking style. Borromeo-Ferri (2015), in her study, found that students in Germany, Japon, and South Korea prefer predominantly different mathematical thinking styles. This result shows that thinking styles can be affected by culture. Borromeo-Ferri (2010) divides students' mathematical thinking styles into three categories as visual, analytical and integrated and she explains these thinking styles as follows:
Visual thinking style: Visual thinkers show preferences for distinctive internal pictorial imaginations and externalized pictorial representations as well as preferences for the understanding of mathematical facts and connections through holistic representations. The internal imaginations are mainly affected by strong associations with experienced situations. Analytical thinking style: Analytic thinkers show preferences for internal formal imaginations and for externalized formal representations. They are able to comprehend mathematical facts preferably through existing symbolic or verbal representations and prefer to proceed rather in a sequence of steps. Integrated thinking style: These persons combine visual and analytic ways of thinking and are able to switch flexibly between different representations or ways of proceeding (p.105).
In this context, the answer to the following research problem has been sought: Do mathematics anxiety of secondary school students differ significantly based on their mathematical thinking styles?
Method
The study is a causal comparison study. In causal comparative research, researchers seek to identify the causes or consequences of differences between individual groups (Fraenkel, Wallen, & Hyun, 2012). Students' math anxieties were measured by bidimensional mathematics anxiety scale which was developed by Bai et al. (2009). The adaptation of the scale to Turkish was done by Akçakın, Cebesoy and İnel (2015). In this study, students’ mathematical thinking were collected by the mathematical thinking style scale developed by Borromeo-Ferri (2015). The mathematical thinking style scale was adapted by Akçakın and Kaya (2018). The high score obtained from the bidimensional mathematics anxiety scale shows that the students have high anxiety. The mathematical thinking styles of the students were determined by latent class analysis. The participants of this study were 220 high school students who continue their education in Ankara province and participate voluntarily in the study.
Expected Outcomes
Latent class analysis was conducted to determine the secondary school students’ mathematical thinking style (see Magidson and Vermunt, 2004; Oberski, 2016). According to latent class analysis, it was determined that 115 of the students were in analytical thinking style, 91 were in integrated thinking style and 14 were in visual thinking style. Due to the variance between groups is homogeneous (F(2,84) = 0.251, p>.01), and data show normal distribution (analytical, W(115)=0.984, p>.05; integrated, W(91)=0.988, p>.05; visual, W(14)=0.954, p>.05), ANOVA test was used to determine whether groups' math anxiety differed according to mathematical thinking styles. As a result, it was seen that mathematics anxiety of students did not differ statistically according to their mathematical thinking styles.(F(2,217)=1.173, p>.05). Considering that mathematical thinking style can differ according to different cultures, further research should be carried out in other cultures.
References
Akçakın, V. Cebesoy, Ü.B., & İnel, Y. (2015). Validity and reliability study of Turkish version of bidimensional mathematics anxiety scale. Gazi University Journal of Gazi Educational Faculty, 35(2).283-301 Akçakın, V., & Kaya, G. (2018). Öğrencilerin matematik başarılarının matematiksel düşünme stillerine göre incelenmesi. Project Report, Unpublished manuscript, Uşak, Turkey Bai, H. (2011). Cross-validating a bidimensional mathematics anxiety scale. Assessment. 1, 178-182. Bai, H., Wang, L., Pan, W., & Frey, M. (2009). Measuring mathematics anxiety: Psychometric analysis of a bidimensional affective scale. Journal of Instructional Psychology, 36, 185-193. Banaga, A., (2018). Learning Style and Mathematics Anxiety of Calawis National High School Students. Master Thesis. Roosevelt College, Inc., Cainta. Borromeo Ferri, R. (2010). On the influence of mathematical thinking styles on learners’ modeling behavior. Journal für Mathematik-Didaktik, 31(1), 99-118. Borromeo Ferri, R. (2015). Mathematical Thinking Styles in School and Across Cultures. In Selected Regular Lectures from the 12th International Congress on Mathematical Education (pp. 153-173). Springer International Publishing. Cates, G. L., & Rhymer, K. N. (2003). Examining the relationship between mathematics anxiety and mathematics performance: An instructional hierarchy perspective. Journal of Behavioral Education, 12, 23-34. Dowker, A., Sarkar, A., & Looi, C. Y. (2016). Mathematics anxiety: what have we learned in 60 years?. Frontiers in psychology, 7, 508. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H.(2012). How to design and evaluate research in education. New York: McGraw-Hill Hill, F., Mammarella, I. C., Devine, A., Caviola, S., Passolunghi, M. C., & Szűcs, D. (2016). Maths anxiety in primary and secondary school students: Gender differences, developmental changes and anxiety specificity. Learning and Individual Differences, 48, 45-53. Magidson, J. & Vermunt, J. (2004) Latent class models, in the SAGE Handbook of Quantitative Methodology for the Social Sciences (Ed. D. Kaplan), Sage Publications, Thousand Oaks, CA, pp. 345–368. McLeod, D. B. (1992). Research on affect in mathematics education: A reconceptualization. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 575-596). New York: Macmillan. Ng, L. K. (2012). Mathematics Anxiety in Secondary School Students. Mathematics Education Research Group of Australasia. Oberski D. (2016) Mixture Models: Latent Profile and Latent Class Analysis. In: Robertson J., Kaptein M. (Eds) Modern Statistical Methods for HCI. Human–Computer Interaction Series (pp. 275-287). Springer, Cham. Richardson, F. C., & Suinn, R. M. (1972). The mathematics anxiety rating scale: Psychometric data. Journal of Counseling Psychology, 19, 551-554.
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