National standards and frameworks for mathematics, computer science, and technology emphasize the importance of teaching all children computational thinking (CT) skills. These skills are important for preparing citizens that are literate in science, technology, engineering, and mathematics and for participation in a society that is rapidly changing with emerging technologies. This paper describes a 72-hour summer institute for grades 6-8 middle school mathematics teachers (n = 22) with a comprehensive approach to professional development, including training in computer programming with Bootstrap Algebra and Lego® Mindstorms® robotics, mathematics content sessions, and mathematics pedagogy sessions. Results of an assessment used to measure content knowledge and CT skills as well as the Technological Pedagogical Content Knowledge survey yielded statistically significant increases. Participant reflections revealed they valued opportunities for collaboration within grade-level professional learning communities and integration of CT strategies through both programming and robotics. Based upon participant feedback we recommend choosing either the use of Bootstrap Algebra or Lego Mindstorms within shorter timeframes to better prepare teachers for classroom implementation. These middle school teachers were receptive to mathematics-specific content sessions focused on developing conceptual understanding of mathematics they teach as well as grade-level appropriate manipulatives.
This study examined the characteristics of technology-enhanced statistical tasks written by 75 preservice mathematics teachers who used the ESTEEM project’s curriculum materials. In particular, it investigated the extent to which the tasks incorporated three key aspects related to best practices for teaching statistics: (a) analysis of large, multivariate, real datasets; (b) continual connection to context; and (c) engagement in the statistical investigation cycle. Regarding Key Aspect 1, the results showed that the tasks involved analysis of large (usually between 30 and 200 cases) datasets, with an average of 15 attributes provided per case. The vast majority of the datasets were also real, either from outside sources or collected by the students when the task would be implemented. Concerning Key Aspect 2, most tasks called for students to connect their work to the context from which the data was generated numerous times including during their orientation to the task, their reading of graphs made to display the data, and their interpretation of their analysis. Engagement in multiple phases of the statistical investigation cycle (Key Aspect 3) was asked for in the tasks as well. Hence, the ESTEEM project’s curriculum materials hold promise for supporting new teachers to plan meaningful technology-enhanced statistical tasks.
Although teachers are expected to teach with technology, they often are not prepared or supported to do so (Albion, Tondeur, Forkosh-Baruch, & Peeraer, 2015), a critical issue in mathematics education (Wilson, 2008). The study described in this article investigated why and how secondary mathematics teachers implemented virtual manipulative (VM) tasks during and after participating in a professional development (PD) opportunity aimed at teaching with VMs. Findings indicate that teachers used VM tasks due to instructional benefits, for example, supporting students’ developing understanding and differentiation. Additionally, they used VMs and tasks due to the support they received from tools introduced during the PD. In this study, teachers primarily used VM tasks to support students’ developing understanding, to provide in-the-moment feedback, and as a reteaching tool. Mediating factors, such as student needs, curriculum, time, tool limitations, and so forth, influenced why and how teachers chose to use a particular VM.
The question of how elementary teachers choose tasks has been widely discussed in the field of education. However, these studies have not adequately addressed the increasing use of online resources by elementary mathematics teachers. The authors of this study surveyed 601 elementary mathematics teachers in the United States to examine the trends in the teacher selection of elementary math tasks from online resources. They discuss the relationship between different websites, various selection criteria used to find mathematics activities, and teachers’ years of experience. They found a significant relationship between number of years teaching and the use of paid resources and the appeal of visual components of an activity, yet they did not find a significant relationship between years of experience and time spent searching online for an elementary math activity. In sum, this project, by closely examining the trends in teacher selection and use of elementary math tasks, sheds new light on the thinly acknowledged issue of the use of websites and tasks by teachers of elementary mathematics.