How to Do SMS Learning Using the Experience API

| Comments

The Experience API enables new ways to deliver and capture mobile learning experiences, like SMS learning. There are great tools for mobile delivery like HTML5 & native apps but they require a lot of time and resources. In this article, we’ll cover how to setup an SMS learning application and have the results reported to an LRS, then we’ll show you how to deploy your own application.

xapi-sms-learning-application

The Problem

We need a cost-effective way to provide a short burst of learning on a mobile device. Results of the learning experiences need to be captured and it should work on different types of mobile devices.

The Solution

One possibility is using Twilio + Experience API + Google App Engine + Wax LRS. We’ve designed an example web application hosted on Google App Engine (a place to host web applications) that provides step-by-step instructions via text message for folding a dollar bill into a t-shirt. Twilio is the mechanism our application uses for sending and receiving SMS and the app reports progress to Wax LRS using the Experience API upon completion of each step.

We’ve created a detailed 4-step guide or you can see the following video for a quick overview:

Deploy your own SMS learning application

If creating t-shirts from a dollar bill isn’t what you need, try this:

  1. Download & modify the code. We’ve open sourced the code on GitHub, so you can download and modify it for your specific needs.
  2. Upload your app to Google App Engine. Here’s an introduction for uploading and registering your custom application to Google App Engine.
  3. Other resources: Twilio Quickstart Guide, Google App Engine SDKs.
  4. You can always reach out to us for any help, we’d be glad to answer any questions.

Do you want to use SMS for mobile learning delivery? How would you use this? Let us know what you think in the comments below.

Neil Lasher (Phone2Know) and Russell Duhon (CTO, Saltbox) collaborated on the ideation, design, and development of this application and it was presented at mLearnCon 2013.

Comments