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- Mathematical modellers’ opinions on mathematical modelling in upper secondary education.
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In this volume cultural, social and cognitive influences on the research and teaching of mathematical modelling are explored from a variety of theoretical and practical perspectives. The authors of the current volume are all members of the International Community of Teachers of Mathematical Modelling and Applications, the peak research body in this field. A distinctive feature of this volume is the high number of authors from South American countries. These authors bring quite a different perspective to modelling than has been showcased in previous books in this series, in particular from a cultural point of view.
As well as recent international research, there is a strong emphasis on pedagogical issues including those associated with technology and assessment, in the teaching and learning of modelling. Applications at various levels of education are exemplified. The contributions reflect common issues shared globally and represent emergent or on-going challenges.
Help Centre. My Wishlist Sign In Join. Be the first to write a review. Add to Wishlist. Ships in 15 business days. Link Either by signing into your account or linking your membership details before your order is placed. Description Table of Contents Product Details Click on the cover image above to read some pages of this book! Brown and Vince Geiger. Jacob Perrenet and Bert Zwaneveld. Villarreal, Cristina B. Esteley and Silvina Smith. The Relationships between achievement goal and mathematical modeling competency will not be mediated by awareness, planning, cognitive strategy and self-checking.
Measures The translation preciseness of the original questionnaire was confirmed using back translation. Mathematical modeling competency test. Metacognitive inventory questionnaire. Data analysis Prior to further analysis, several issues related to data screening, such as handling missing data, multicollinearity and identification of outliers and normality, were considered using Statistical Package for the Social Sciences Mediator analysis A mediator intervening variable distributes the effect of an independent variable to a dependent variable [ ].
Download: PPT. Table 1. Means, standard deviations, and Pearson correlations between mathematical modeling competency, achievement Goals and sub-construct of metacognition. Testing the measurement models CFA procedures were conducted to verify the factorial validity of the four sub-constructs of metacognition and the six sub-constructs of achievement goals. Fig 1. Confirmatory factor analysis path diagram for achievement goals. Fig 2. Confirmatory factor analysis path diagram for metacognition. Fig 3. Confirmatory factor analysis path diagram for mathematical modeling.
Relationships between achievement goals and mathematical modeling competency We assumed that achievement goals will positively affect mathematical modeling competency. Relationships among four metacognition sub-constructs awareness, planning, cognitive strategy and self-checking and mathematical modeling competency We hypothesised that four metacognition sub-constructs, namely, awareness, planning, cognitive strategy and self-checking, positively affect mathematical modeling competency.
Mediating effects of the four metacognition sub-constructs on the relationships between achievement goals and mathematical modeling competency We expected a mediating effect of awareness, planning, cognitive strategy and self-checking on the relationships between achievement goals and mathematical modeling competency. Discussion This study examined the relationship between metacognition and achievement goals which might influence mathematical modeling competency in students of mathematics education programs.
Effects of achievement goals on mathematical modeling competency The significant direct relationship between achievement goals and mathematical modeling competency was confirmed in our study regardless whether due to task-approach goal, task-avoidance goal, self-approach goal, self-avoidance goal, other-approach goal or other-avoidance goal. Effects of the four metacognition dimensions awareness, planning, cognitive strategy and self-checking on mathematical modeling competency We found that metacognition positively affected mathematical modeling competency. Effects of achievement goals on mathematical modeling competency via awareness, planning, cognitive strategy and self-checking The present study indicates that the four metacognition dimensions including awareness, planning, cognitive strategy and self-checking are positive partial mediators because they improve the association between achievement goals and mathematical modeling competency.
Conclusions and suggestions The results of this research provide further evidence that achievement goals and metacognition positively influence mathematical modeling competency. Supporting information. S1 File. Letter of permission from the educational planning and research division. S2 File. Data availiability. Acknowledgments We would like to thank Mrs Aulia Stephani for her helps in data collate. References 1. English, L. Mathematical modeling: Linking mathematics, science and arts in the primary curriculum. Gainsburg J. The mathematical modeling of structural engineers.
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Erbas AK, Bas S. The contribution of personality traits, motivation, academic risk-taking and metacognition to the creative ability in mathematics. Creativity Research Journal. The relationship between mathematical problem-solving skills and self-regulated learning through homework behaviours, motivation, and metacognition. Tzohar-Rozen M, Kramarski B. Metacognition, motivation and emotions: Contribution of self-regulated learning to solving mathematical problems. Global Education Review. Yusnaeni A. Transitions between cognitive and metacognitive activities in mathematical modelling process within a technology enhanced environment.
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Problem solving ability and metacognition based goal orientation on problem based learning.
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The role of goal orientations and goal structures in explaining classroom social and affective characteristics. Learning and Individual Differences. Senko C, Harackiewicz JM. Achievement goals, task performance, and interest: Why perceived goal difficulty matters. Social Psychology of Education. Hagstrom F, White M. Talk and task mastery: The importance of socially shared talk during computer-based problem solving. Ferri RB, Lesh R. Should interpretation systems be considered to be models if they only function implicitly? Challenges in modelling challenges: Intents and Purposes. Mastery-approach goals and knowledge transfer: An investigation into the effects of task structure and framing instructions.
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Related Mathematical Modelling in Education Research and Practice: Cultural, Social and Cognitive Influences
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