After getting my hands dirty with SCORM implementation for mobile devices I think there are some key points to consider before implementing SCORM for mobile devices in any form.

Since my post on SCORM Implementation for Mobile Devices, I have wanted to write a specific post on offline SCORM implementation for Blackberry, which is still the most widely used mobile device in enterprise and business domains.

Again, as in implementation of SCORM for mobile devices, we encountered some interesting issues in its implementation for Blackberry.

Find our experience on the same.

Recently we’ve made the UpsideLMS compatible to mobile devices and also launched a new version – UpsideLMS Version 4.0. While ensuring compliance, we encountered some interesting issues in the implementation of SCORM and found very little help online about implementing SCORM for mobile devices. So we thought sharing that experience might help.

Mobile devices have limitations:

- Screen size
- Availability of required technology/software like J2ME, a compatible browser
- Availability of consistent internet connection

1. Alternatives to Second Life
Karl Kapp puts some alternatives to Second Life on his blog. Interesting products, although some will cease to exist starting next year.

2. Windows Mobile for Gaming
Microsoft to make Windows Mobile a gaming platform. While other mobile OS developers are jockeying for position to become the game platform of choice for mobile devices, Windows mobile lagged behind.

The Big Question posed on Learning Circuits this time,as always, is thought provoking –

What did you learn about Learning in 2009?

I think my learning for 2009 was focused around three primary areas; this obviously derives from my focus on innovation in elearning and is biased, but here goes.

1. Meaning Tool: Training Semantic Search With Feeds
Meaning Tool is a semantic engine that offers users a chance to extract concepts from text using specific semantic trees. You define your categories of interest by creating search parameters and training them with related websites or RSS feeds. A great tool to see how semantic trees can help search.

1. Device tag support in HTML 5
   Yesterday World Wide Web Consortium has reported that HTML 5 will support external devices, directly from your browser. Now your browser will access your webcam, microphone and other USB devices directly, no other software/plug-ins required.

With increasing bandwidths and better compression techniques available, use of videos in Flash platform based eLearning courses is on the rise. However, often we find videos not being used optimally. This could leave your learners with a bad experience. Here are a few technical aspects to keep in mind when working with videos. Please do share any others that you may know in comments area.

I came across this really interesting interview with Greg Kroah-Hartman – Linux Kernel Dev/Maintainer. In this interview, Greg talks about how the Linux project has accommodated the accelerating rate of change for the kernel. It was very interesting to draw parallels between some of what he says and learning.

1. Google Dumps Gears for HTML5
   Google will end Gears, an open-source plug-in project it launched two years ago to allow Web applications to function even when a computer isn’t connected to the Internet. Applications that used Gears include Google’s Docs and Reader.
   However, new incompatibilities with Gears have cropped up. Although it works with Microsoft’s Windows, Linux and some Apple Mac OS X versions, it doesn’t work with Mac OS X 10.6, also known as Snow Leopard. Also As much of the technology in Gears, including offline support and geo-location APIs, are being incorporated into the HTML5 spec as an open standard supported across browsers, it is natural for Google to Drop Gears in favor of HTML5. However Gears will continue to be supported for sites that already use it.

Yesterday Google released a visual search engine called Google Goggles. It is available right now as an application for Android 1.6+ (i.e. Donut or Eclair) based mobile devices. It uses several sophisticated image recognition techniques like object recognition, OCR, face matching, etc.

Over the last couple of weeks I’ve met some prospective customers from the Telecom domain here in India. While they’re all keyed about mobile learning, they have serious reservations about how they (as telecom service providers) can leverage their own networks. I often point to some simple facts. Each of their employees carries a cell phone and is connected to the network 24 hours a day. These employees are scattered all over the Indian geography. This presents a unique challenge and opportunity.