Dynamic Mathematics Software as a Necessary Component of Modern-Math-Teacher Preparation in Ukraine

The article discusses the relevance of the study of dynamic Mathematics software by future math teachers in Ukraine. The focus is on the requirement, not only to know about specialized dynamic software, but also to be able to organize an effective learning process with its usage. The arguments for the organization of special courses in the study of dynamic Mathematics software are based on the need to demonstrate the skills of usage of modern Mathematics software. The authors describe their own experience of teaching the course at A. S. Makarenko Sumy State Pedagogical University (Ukraine), which is included in the curricula as variable course of math-teacher preparation, in particular, the successive changes of the content of the course, due to constant and rapid development of Information Technology, during all periods of learning

Methodology of formation of modeling skills based on a constructive approach (on the example of GeoGebra)

Author’s methodology of forming modeling skills involves 4 steps: Step 1 – the teacher step by step constructs the curve by means of cloud based service GeoGebra; Step 2 – the teacher offers a description-definition of the curve and provides a ready-made algorithm by which students model the curve independently in GeoGebra; Step 3 – the teacher offers an algorithm for constructing a curve model, and students need to characterize the properties of the curve or give its definition based on the results, Step 4 – students are offered definitions of curves that they have to model in GeoGebra). An example of realization of the author’s methodology is given, the pedagogical experiment on proof of its effectiveness is described

Data from an international multi-centre study of statistics and mathematics anxieties and related variables in university students (the SMARVUS dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments\’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website (https://osf.io/mhg94/)

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]