Gould, R. R., S. Sunbury, & Dussault, M. (2014). In praise of messy data: Lessons from the search for alien worlds. The Science Teacher, 31.
Lessons from the search for alien worlds.
The search for habitable planets offers excellent opportunities to advance students’ understanding of core ideas in physics, including gravity and the laws of motion, the interaction of light and matter, and especially the nature of scientific inquiry. Thanks to the development of online telescopes, students can detect more than a dozen of the known exoplanets from the classroom, using data they gather, assess, and interpret for themselves. We present a suite of activities in which students apply basic physics concepts to their investigations of exoplanets.
Authors present a suite of activities in which students apply basic physics concepts to their investigations of exoplanets. The activities were developed and successfully tested with physics and earth science teachers in secondary schools in 14 states.
Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria.
This paper explores the CAT Capability Flow, which begins to describe the processes and sub-skills and capabilities involve in computational algorithmic thinking (CAT). To do this, authors engage in an approach which results in an initial flowchart that depicts the processes students are engaging in as an iteratively-refined articulation of the steps involved in computational algorithmic thinking.
Paper from the 2016 Advancing Social Justice from Classroom to Community Conference.
Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. Supporting Computational Algorithmic Thinking (SCAT) is a longitudinal project that explores the development of CAT capabilities by guiding African American middle-school girls through the iterative game design cycle, resulting in a set of complex games around broad themes.
This paper explores African American middle-school girls' perspectives of their experience with the Supporting Computational Algorithmic Thinking (SCAT) project and perceptions of themselves as game designers.
Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria.
This article explores middle school girls' reflections about the difficulties they faced while using computational algorithmic thinking capabilities as they engaged in collaborative game design for social change. Authors focus on how these difficulties changed over the course of three years as well as new difficulties that emerged from year to year as girls become more expert game designers and computational algorithmic thinkers.
Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that it solves the problem, and evaluating the solution based on some set of criteria. CAT has roots in Mathematics, through problem solving and algorithmic thinking. CAT lies at the heart of Computer Science, which is defined as the study of algorithms.
This article introduces CAT as explored through the Supporting Computational Algorithmic Thinking (SCAT) project, an ongoing longitudinal between-subjects research project and enrichment program that guides African-American middle school girls (SCAT Scholars) through the iterative game design cycle resulting in a set of complex games around broad themes.
Discover how digital games can inform classroom teaching using data from innovative formative assessments from three different game-based projects.
This session aims to open up a conversation about of how games can be used for formative assessment and how data from digital games can inform classroom teaching.
Join a facilitated discussion about the application of data science to education, drawing on a recent NSF-sponsored report. Participants share insights from DR K–12 projects.
The Computing Research Association’s report from an NSF-sponsored workshop describes seven next steps for data-intensive research in education:
From the perspectives of Graduate Research Assistants (GRAs), this study examines the design and implementation of a simulated teaching environment in Second Life (SL) for prospective teachers to teach algebra for diverse learners. Drawing upon the Learning-for-Use framework, the analyses provide evidence on the development of student avatars in construction and role-playing activities. The study reveals challenges, procedures, and suggestions for future simulations. This study also calls for research efforts toward preparing mathematics teachers for cultural diversity.
This study examines the design and implementation of a simulated teaching environment in Second Life for prospective teachers.
