Learning Record Stores with Tim Martin #ASTDTK14

 These are my live blogged notes from Tim Martin's session at ASTD Tech Knowledge, wrapping up today in Las Vegas.

Tin Can 101: It’s a shared system for two systems to talk about the things that a person does. Unlike SCORM which was about content in a browser.  (There’s much more here: http://tincanapi.com/overview/)

TinCan allows simulators, servers, mobile devices, etc to communicate.

Tin Can is driven by a web service based solution. It uses a RESTful web Server (and yes, I had to ask what this is: a more commonly adopted web service architecture. Developers, apparently, will like this. http://en.wikipedia.org/wiki/Representational_state_transfer)

Two parties in xAPI/Tin Can: Activity Provider and the Learning Record Store

How might you use Tin Can today? Start small. Success comes from starting small, understanding something narrow and then expanding. Instead of trying to measure everything in your organization, think about designing experiments.  

This echoes something @reubentozman said in his session yesterday on Designing for Data (sorry – I didn’t blog it, but I did Tweet a lot for Reuben’s session): 

"Think about design as an experiment. Design your experiments to capture data you want/need."

Tin Can has a noun (the person, email address, ee identifier, etc), verb, object structure. “Cammy read a book.” “Cammy ran a marathon.” “Cammy presented at a conference.”

Learning Record Store = collects statements from Tin Can (A much better definition can be found here: http://tincanapi.com/learning-record-store/)

Organizations might use multiple LRS’s in their organizations – each one looking at the same set of data and presenting them in different ways for different parts of the organization. Use the data in the LRS from an interesting analytics view.

This page gives a really nice introduction to how you an approach the design process as an experiment.  http://watershedlrs.com/site/watershedmethod.html

So the analytics could help you identify completion rates if a course is designed with higher fidelity vs. lower fidelity (helping you test your hypothesis that the production value of yourx` course does matter).

Or “People who do that and this are more successful than people who do that and not that…” Follow the learning path and watch who succeeds based on the paths.

Experiment Design:

• The company was looking to look at cultural adoption of the code of conduct. They wanted people to do the right thing because they believed it, not because they were forced to. So they wanted to see the # of calls going up to report ethics violations and help desk.
• They had a piece of content from a rapid learning tool. The experiment compares high fidelity content (with video and simulations) to the actual text of the code of content. So completion statements for each modality.  “Tim completed this.” – can see the depth to which Tim explored the simulation. The sim sends statements.
• For the text version can just know if they got through all the pages of the document. So text doc sends statement.
• Quizzes to test comprehension.
• Pre and Post surveys to self-assess afterwards. Comes in from a survey tool. These make statements.
• Calls to the help desk can send statements. (“Tim called hotline.” Or “Tim reported violation.”)

So it's a fixed set of statements about a fixed population.

Gave one part of the company the high fidelity content and the other part the text. We think (the hypothesis) that high fidelity content is going to help people get it better.

The high fidelity group follows through on the path and completes different tasks, surveys etc. And if the data proves that high fidelity content creates better outcomes (e.g., more calls to help desk) then the business can make different decisions.

The first meetings are asking questions like “so where do you think you can make a difference in the organization.”

Some designers just think of themselves as designing content in a tool. Instead, let’s think about designing experiments.