Statistical thinking has a broad definition but focuses on the context of regression modelling in the present study. To foster students' statistical thinking within the context, teaching should no longer be seen as transfer of knowledge from teacher to students but as a process of engaging with learning activities in which they develop ownership of knowledge. This study aims at collaborative learning contexts; students were divided into small groups in order to increase opportunities for peer collaboration. Each group of students was asked to do a regression project after class. Through doing the project, they learnt to organize and connect previously accrued piecemeal statistical knowledge in an integrated manner. They could also clarify misunderstandings and solve problems through verbal exchanges among themselves. They gave a clear and lucid account of the model they had built and showed collaborative interactions when presenting their projects in front of class. A survey was conducted to solicit their feedback on how peer collaboration would facilitate learning of statistics. Almost all students found their interaction with their peers productive; they focused on the development of statistical thinking with concerted effort.

Mathematics is a science of pattern. Mathematics is a subject of inquiring which aims at discovering the models hidden behind the world. Pattern is abstraction and generalization of the model. Mathematical pattern is a higher level of mathematical model. Mathematics patterns are often hidden in pattern similarity. Creation of mathematics lies largely in discovering the pattern similarity among the various components of mathematics. Inquiring is the core and soul of mathematics teaching. It is very important for students to study mathematics like mathematicians' exploring and discovering mathematics based on pattern similarity. The author describes an example about how to guide students to carry out mathematics inquiring based on pattern similarity in classroom.

A central problem of mathematics teaching worldwide is probably the insufficient adaptive handling of tasks-especially in computational practice phases and modeling tasks. All students in a classroom must often work on the same tasks. In the process, the high-achieving students are often underchallenged, and the low-achieving ones are overchallenged. This publication uses different modeling of the tennis serve as an example to show a possible solution to the problem and develops and discusses one adaptive task each for middle school, high school, and college using three mathematical models of the tennis serve each time. From model to model within the task, the complexity of the modeling increases, the mathematical or physical demands on the students increase, and the new modeling leads to more realistic results. The proposed models offer the possibility to address heterogeneous learning groups by their arrangement in the surface structure of the so-called parallel adaptive task and to stimulate adaptive mathematics teaching on the instructional topic of mathematical modeling. Models A through C are suitable for middle school instruction, models C through E for high school, and models E through G for college. The models are classified in the specific modeling cycle and its extension by a digital tool model, and individual modeling steps are explained. The advantages of the presented models regarding teaching and learning mathematical modeling are elaborated. In addition, we report our first teaching experiences with the developed parallel adaptive tasks.

Recent international reform movements call for attention on modeling in mathematics classrooms. However, definitions and enactment principles are unclear in policy documents. In this case study, we investigated United States high-school mathematics teachers' experiences in a professional development program focused on modeling and its enactment in schools. Our findings share teachers' experiences around their discovery of different conceptualizations, appreciations, and conflicts as they envisioned incorporating modeling into classrooms. These experiences show how professional development can be designed to engage teachers with forms of modeling, and that those experiences can inspire them to consider modeling as an imperative feature of a mathematics program.

We investigated the classification of learner groups for students' mathematical modeling competency and analyzed the characteristics in each profile group for each country and variable using PISA 2012 data from six countries. With a perspective on measuring sub-competency, we applied the latent profile analysis method to student achievement for mathematical modeling variables - Formulate, Employ, Interpret. The findings showed the presence of 4-6 profile groups, with the variables exhibiting high and low achievement within each profile group varying by country, and a hierarchical structure was observed in the profile group distribution in all countries, interestingly, the Formulate variable showed the largest difference between high-achieving and low-achieving profile groups. These results have significant implications. Comparison by country, variable, and profile group can provide valuable insights into understanding the various characteristics of students' mathematical modeling competency. The Formulate variable could serve as the most suitable predictor of a student's profile group and the score range of other variables. We suggest further studies to gain more detailed insights into mathematical modeling competency with different cultural contexts.

This study aims to investigate the extent to which Korean high school textbooks incorporate opportunities for students to engage in the mathematical modeling process through tasks related to exponential and logarithmic functions. The tasks in three textbooks were analyzed based on the actions required for each stage in the mathematical modeling process, which includes identifying essential variables, formulating models, performing operations, interpreting results, and validating the outcomes. The study identified 324 units across the three textbooks, and the reliability coefficient was 0.869, indicating a high level of agreement in the coding process. The analysis revealed that the distribution of tasks requiring engagement in each of the five stages was similar in all three textbooks, reflecting the 2015 revised curriculum and national curriculum system. Among the 324 analyzed tasks, the highest proportion of the units required performing operations found in the mathematical modeling process. The findings suggest a need to include high-quality tasks that allow students to experience the entire process of mathematical modeling and to acknowledge the limitations of textbooks in providing appropriate opportunities for mathematical modeling with a heavy emphasis on performing operations. These results provide implications for the development of mathematical modeling activities and the reconstruction of textbook tasks in school mathematics, emphasizing the need to enhance opportunities for students to engage in mathematical modeling tasks and for teachers to provide support for students in the tasks.