Cloud Computing Workshop for Teachers (CCWT) at NJIT

In 2012, New Jersey Institute of Technology (NJIT) hosted the Cloud Computing Workshop for Teachers (CCWT), a professional development workshop for high-school teachers. The workshop was organized by Prof. Reza Curtmola (Department of Computer Science, NJIT) in collaboration with the Center for Pre-College Programs (CPCP) at NJIT. The workshop was supported by the United States National Science Foundation.

The goal of the workshop was twofold. First, it exposed high school teachers to the concept of Cloud Computing and the technologies associated with it. Second, it sought to develop curriculum units based on cloud-based technologies that can be integrated into high-school instruction.

The workshop was structured in two sessions. The first session, held in July 2012, consisted of three days of hands-on instruction.  The 3-day summer session focused on several instructional topics. Each topic consisted of a presentation given by the workshop organizers, followed by hands-on exercises to illustrate the concepts that were presented. The following topics were addressed:

  • Overview of Cloud Services
  • Storing and Sharing Data in the Cloud
  • Clouds in Education and Collaboration in and out of the Classroom
  • Cloud-based Tools for Real-time Collaboration
  • Course Management using Piazza
  • Standards-based Lesson Planning and Post-workshop Assignment
  • Creating a Lesson Plan
  • Using Public Data Sets Available in Amazon’s Cloud

At the end of the three-day program, participants were given an assignment which asked them to identify a lesson taught in their classroom, which would use the cloud as an educational technology tool, and then to write a revised lesson plan based on cloud computing integration and standards-based lesson planning. The assignment also required participants to submit the revised and original lesson plan plus samples of student work. Their completed assignments were presented at a 1-day meeting in December 2012.

This material is based on work supported by the National Science Foundation under Grant No. 1054754.  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.