Educational Technology

The COVID-19 induced school shutdown dramatically decreased students’ hands-on STEM learning opportunities. An NSF-funded program partnering preservice teachers and undergraduate engineering students to teach robotics to fifth graders was adapted to a virtual format via Zoom. A case study intimately explored one team’s experience as they engineered bio-inspired robots over five weekly sessions. Zoom recordings, written reflections, and lesson slides were analyzed to describe how the virtual context shaped the lesson and influenced the preservice teacher’s experience.

The use of video is commonplace for professional preparation in education and other fields. Research has provided evidence that the use of video in these contexts can lead to increased noticing and reflection. However, educators now have access to evolving forms of video such as 360 video. The purpose of this study was to adapt and validate an instrument for assessing immersive 360 video use in an undergraduate preservice teacher university training program.

Research has provided evidence of the value of producing multiple representationsof content for learners (e.g., verbal, visual, etc.). However, much of the research has acknowledged changes in visual technologies while not recognizing or utilizing related audio innovations. For instance, teacher education students who were once taught through two-dimensional video are now being presented with interactive, three-dimensional content (e.g., simulations or 360 video). Users in old and new formats, however, still typically receive monophonic sound.

The lack of a definition of the T in STEM (science, technology, engineering, and mathematics) acronym is pervasive, and it is often the teachers of STEM disciplines who inherit the task of defining the role of technology within their K-12 classrooms. These definitions often vary significantly, and they have profound implications for curricular and instructional goals within science and STEM classrooms.

The lack of a definition of the T in STEM (science, technology, engineering, and mathematics) acronym is pervasive, and it is often the teachers of STEM disciplines who inherit the task of defining the role of technology within their K-12 classrooms. These definitions often vary significantly, and they have profound implications for curricular and instructional goals within science and STEM classrooms.

The lack of a definition of the T in STEM (science, technology, engineering, and mathematics) acronym is pervasive, and it is often the teachers of STEM disciplines who inherit the task of defining the role of technology within their K-12 classrooms. These definitions often vary significantly, and they have profound implications for curricular and instructional goals within science and STEM classrooms.

This article focuses on discussion and preliminary findings from classroom testing of the prototype learning module: Investigating Income Inequality in the U.S. In this module, students examine patterns of income inequality using person-level microdata from the American Community Survey (ACS) and the U.S. decennial census.

A design study was conducted to test a machine learning (ML)-enabled automated feedback system developed to support students’ revision of scientific arguments using data from published sources and simulations. This paper focuses on three simulation-based scientific argumentation tasks called Trap, Aquifer, and Supply. These tasks were part of an online science curriculum module addressing groundwater systems for secondary school students.

A design study was conducted to test a machine learning (ML)-enabled automated feedback system developed to support students’ revision of scientific arguments using data from published sources and simulations. This paper focuses on three simulation-based scientific argumentation tasks called Trap, Aquifer, and Supply. These tasks were part of an online science curriculum module addressing groundwater systems for secondary school students.

Well-designed mathematics instruction focused on concepts and problem-solving skills associated with measurement and data analysis can build a foundational understanding for more advanced mathematics. This study investigated the efficacy of the Precision Mathematics Level 1 (PM-L1) intervention, a Tier 2 print- and technology-based mathematics intervention designed to increase first-grade students’ conceptual understanding and problem-solving skills around the areas of measurement and data analysis.