The Connected Learning Analytics (CLA) Toolkit
The CLA toolkit helps students and teachers to harvest data about their activities in standard social media environments, and then provide immediate feedback and reports. It is currently in development, but the basic design is sketched out below:
The release of the Experience API (xAPI) makes it possible to capture student behaviour in a highly flexible manner and send it to a Learning Record Store (LRS) for immediate or later analysis. We currently have tools in development that will interface with the API's of
- Google Docs
More details can be found in this paper:
And if you want to go and check out the source code, then it is available on GitHub
This project has now been funded by the Australian Government's Office for Learning and Teaching (OLT). The Proposal that we submitted can be found here if you would like more details. Feel free to contact me about it!
YouTube Pilot Project
One example scenario of using the CLA toolkit could revolve around specific activities using YouTube.
For example, if you wanted to use YouTube in a teaching exercise, then you could:
- Get each of your students to upload a YouTube video that they had created.
- Comment on a minimum set of other students' videos
- Then send you the YouTube identifier (i.e. URL) and their username.
- If you could somehow access YouTube data, then:
- You could upload all relevant data to your LRS
- Then you could perform analysis of that data, e.g. you show everyone a network map of their place in the class community (in terms of comments on other students' videos)
We have a tool that allows you to access YouTube data, and enter it into an xAPI LRS. If you enter a specific YouTube URL, then the tool will extract all of the textual data from that webpage and send it to a LRS (as long as the people who posted comments have an account on the system, and have registered their YouTube username with the system). We will be making this tool available via GitHub when we launch a prototype of the CLA toolkit (hopefully before the end of 2014 so keep an eye out). For now, you can check out a simple demo by following this link
Student Teams and Projects
Students who have helped in developing CLA tools and prototypes so far (not all of these prototypes are available here, but I can provide more details as to the team contribution upon request):
- Team 42: 2014, S1. Eliza Williams, Natakorn Lekavatanachai, Sebastian Cross, Steven Kelly, Zak Waters
- Team G-generation: 2014, S1. Daniel Young, Yanqiu Yan, Ziyao Tang, Liang Wu, Si Chen
- Learning Analytics Team: 2014, S2. Jarrah Madill, Brian Fernandez, Clinton Redhouse, Nathan Osborne, James Pilkington, Ihsan Mujdeci
A big shout-out goes especially to Sebastian Cross, who has been working on the CLA toolkit as an individual project for one semester now... and is now on his second semester! Similarly to Clinton Redhouse who appears to be following in his footsteps...