The Connected Spaces Framework (CSF) is a lightweight, customizable framework for connecting multiple distributed makerspaces together. For instance, CSF can log an individual participant’s presence (using either RFID or Bluetooth) in a makerspace within a network of makerspaces and track their current activity, as well as the growth of their personal learning trajectories and “skill” acquisition.
In each space, a large ambient dashboard shows the nicknames of all the makers currently present, their current activities, and any skills in which they have gained “proficiency.” The dashboard also shows all other currently connected and active makerspaces and their participants’ names/nicknames, activities, and proficiencies. By providing this information, CSF attempts to answer the two main challenges in distributed learning spaces: 1) How do we give participants insight into the skills of their peers to help know who to reach out to when they need help with a specific maker-skill related problem (e.g., 3D Printing)?; and 2) How do we give learners a sense of the distributed knowledge community they are a part of?
CSF also works to support distributed engagement and collaboration across makerspaces by embedding a lightweight video chat portal in each dashboard, which can be turned on to connect makerspaces together for real-time collaboration (see Figure 1). We are currently developing a series of RFID enabled blocks that can be placed on sensors near the dashboard that will allow one space to reach out and “poke” another space to initiate a chat session. The blocks will be able to specify which space a group wants to talk to, and what they want to talk about (e.g., A question about 3D printing, Coding, or just to say hi). Our goal is to make this customizable by each network of spaces, to allow them to determine which spaces they want to connect to and the topics they would want to connect on.
Each student in the CSF is provided with a low cost NFC card/sticker which they can use to log into the makerspace (or a specific computer/station), using a simple tap system (see figures 2 & 3 below). Once a student logs into the system all the relevant information is are logged in the CSF database (e.g., student ID, login location, time logged in). The collective student data can then be easily exported for further analysis (e.g., looking at collaboration patterns, time spent on tasks). In conjunction with other analytic approaches, this data can also be used to help determine student skill progress and learning trajectories, which can be shown to both students and teachers.