Computer Science

Background and Context
Students’ self-efficacy toward computing affect their participation in related tasks and courses. Self-efficacy is likely influenced by students’ initial experiences and exposure to computer science (CS) activities. Moreover, student interest in a subject likely informs their ability to effectively regulate their learning in that domain. One way to enhance interest in CS is through using collaborative pair programming.

The COVID-19 pandemic shifted many U.S. schools from in-person to remote instruction. While collaborative CS activities had become increasingly common in classrooms prior to the pandemic, the sudden shift to remote learning presented challenges for both teachers and students in implementing and supporting collaborative learning. Though some research on remote collaborative CS learning has been conducted with adult learners, less has been done with younger learners such as elementary school students.

The COVID-19 pandemic shifted many U.S. schools from in-person to remote instruction. While collaborative CS activities had become increasingly common in classrooms prior to the pandemic, the sudden shift to remote learning presented challenges for both teachers and students in implementing and supporting collaborative learning. Though some research on remote collaborative CS learning has been conducted with adult learners, less has been done with younger learners such as elementary school students.

The rapid expansion of K-12 CS education has made it critical to support CS teachers, many of whom are new to teaching CS, with the necessary resources and training to strengthen their understanding of CS concepts and how to effectively teach CS. CS teachers are often tasked with teaching different curricula using different programming languages in different grades or during different school years, and tend to receive different professional development (PD) for each curriculum they are required to teach.

The CS-STEM Network offers research-based curricula created by Carnegie Mellon Robotics Academy that focus on teaching big ideas with robotics. Over 20 curriculum options provide support for LEGO, VEX, Arduino, and Virtual robot platforms in this Learning Management System.

The CS-STEM Network offers research-based curricula created by Carnegie Mellon Robotics Academy that focus on teaching big ideas with robotics. Over 20 curriculum options provide support for LEGO, VEX, Arduino, and Virtual robot platforms in this Learning Management System.

EarSketch helps you learn core topics in computer science, music, and music technology in a fun, engaging environment. You learn to code in Python or JavaScript, two of the most popular programming languages in the world, while manipulating loops, composing beats, and applying effects to a multi-track digital audio workstation. To start learning to write code and make music, click the Start Coding button and use the integrated online curriculum.

The SchoolWide Lab middle school curriculum units are anchored in phenomena, aligned to the Next Generation Science Standards(NGSS) and purposefully integrate Computational Thinking (CT). To date, four units have been developed by a team of researchers from the University of Colorado Boulder in collaboration with middle school teachers from Denver Public Schools.

Getting Unstuck is a 10-module intermediate Scratch curriculum to help your students develop greater creative and conceptual fluency with code. The curriculum reimagines the classroom as a design studio: a culture of learning in which students explore, create, share, and reflect. Get started with the curriculum by reading the orientation, then explore the modules.