RCA1611 – Teaching with Physical Computing: Introduction to Project-Based Learning

COURSE DESCRIPTION

This course introduces the fundamental concepts underpinning Project-Based Learning, and how you can apply it with programmable devices to bring STEM & Computing to life in the classroom.

Arm’s first professional development course introduces you to the core elements of physical computing. This includes common Arm-based hardware platforms such as Arduino, Raspberry Pi and micro:bit, as well as the learning theories and concepts that underpin a Project-Based Learning pedagogy. The course helps you transform your approach to teaching Computer Science in the classroom, sharing best practice and practical guides to give all learners the opportunity to develop and practice a broad range of STEM skills.

The course explores how physical computing devices can enable educators to apply a constructionist approach to computing in the classroom, using real-world contexts to engage and inspire learners to be creative with technology.

LEARNING OUTCOMES

• A comprehensive introduction to Project-Based Learning and Physical Computing
• An understanding of the ‘big picture’ of Physical Computing, and why it’s essential to STEM & Computing education
• An introduction to how the Arm School Program structures its PBL teaching and learning resources
• A deeper sense of the practices which underline Project-Based Learning, from teaching approach to learning theory
• Resources that help you to deliver an engaging, practical and inclusive class for your students
• Finish the course with a classroom investigation, which helps you put your learning into practice

Syllabus

Module 1 Introduction

Module 2 Required hardware and software (micro:bit, Arduino, Raspberry Pi)

Module 3 The big picture of physical computing

Module 4 Brief description of the orthodoxies

Module 5 The big picture of learning

Module 6 The ASP approach

Module 7 Comprehensive reflection on many learning theories

Module 8 Comprehensive reflection on many teaching approaches

Module 9 Computational thinking

Module 10 Classroom investigation