Fall 2000

 

Read some related materials:

The Invisible Computer. D. Norman, MIT Press (1998)

Learning Objects and Instruction Components C. Quinn. Educational Technology & Society 3(2) 2000

Technology and Learning C.Quinn. Teaching and Learning Online, The Journal. 1997

Some other material Clark wants to show off:

Engaging Learning. C. Quinn. An ITFORUM paper on adding engagement to educational technology. 1997

The Quest for Independence. A game to assist kids in learning to live independently. C. Quinn. 1994; 1997

Designing Cognitive Technology Design A conference paper on practicing what we preach. 1995

UIDGS An aid for interface design (student project) 1998

Visit Quinn's biography.

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Just what is mobile elearning (mLearning)? It's elearning through mobile computational devices: Palms, Windows CE machines, even your digital cell phone. Let's call them information appliances (IAs), and ask what's cool about this? Imagine…

…You're building a requirements doc (using a template in your IA) with your customer when you remember a new feature your company has released. You access the sales training info, and your customer is floored. You update your template and nail the sale at the same time…

…on location, you notice a problem. Through your IA you contact an expert, and use the advice to plug a sensor in and take a reading. Collaborating, you determine another reading to take, and, bingo, you've tracked it back to your supplier. You log the story back into your company knowledge base…

…you settle into your seat and open your IA, dropping back into that simulation. You zip through, and receive feedback not only on your outcomes, but on your approach to the problem. You're now certified, and qualified for the next course as well (one you're determined will lead to a more challenging position). You dive in, hoping to finish on the return trip…

The vision of mobile computing is that of portable (even wearable) computation: rich interactivity, total connectivity, and powerful processing. A small device that is always networked, allowing easy input through pens and/or speech or even a keyboard when necessary (though it may be something completely different like a chord keyboard), and the ability to see high resolution images and hear quality sound. It may be that the image is overlaid on the world through glasses that act like a Heads Up Display.

Donald Norman paints the picture, in his The Invisible Computer of small specialized information appliances. I don't quite agree; I think we want a variety of different general devices capable of customization for our purposes (a subtle but important distinction). As people acquire expertise in digital information processing, they are willing to invest the effort to learn the tools that they uniquely require. For example, people typically have slightly different combinations of programs on their Palm handheld.

The average mobile device will be a small handheld computer with a personally chosen suite of applications. My preference would be something with about an 800 x 600 color screen, a pen, a foldout keyboard (when necessary), fully networked, with a microphone and a speaker. It might be 3 x 5 inches when the keyboard is not extended, and would have a slot to plug in additional capability (for example, a camera). It would either have an advanced browser or a dedicated learning application as one of the software packages installed.

The vision is clear. mLearning is the intersection of mobile computing and elearning: accessible resources wherever you are, strong search capabilities, rich interaction, powerful support for effective learning, and performance-based assessment. elearning independent of location in time or space. What is less clear is where we are now and how we will deliver on this vision.

Where are we now?

So, what is the current state of mLearning? We're just on the cusp of achieving the potential. IAs are becoming commonplace and the quality and capability is increasing while costs continue to drop. My working definition of mLearning is using a Palm as a learning device. There are still some limitations, however, on the vision. Currently, few of these devices are ubiquitously connected, but instead have a 'dialup' capability meaning intermittent connection. The screens are small, the processing is slow, and the storage capacities are limited.

I'll state that elearning properly includes some content material, which could include text, graphics, animation, and covers both the conceptual material as well as some examples. It will also include some interactive practice activities that allow the learner to practice and to provide some personalized feedback. The local learning application or interface will need to ensure that it can talk to a Learning Management System to track performance and update records as well as enable certification.

Two major issues confront us. The first is the problem of having managed learning through the intermittent connection. While we prefer individuals to take responsibility for their own learning, many constraints suggest that there are benefits from having systems track and manage learning. The second issue is cross-platform solutions, meaning all learners have access to all materials independent of particular system preferences.

When tracking learning, the outcomes must be stored and reported back. This is beneficial to know what next to provide the learner, to be able to reward outcomes, and to manage corporate knowledge. As soon as action happens, the learner platform can communicate the outcome back to the management system. However, this solution does not work with intermittent connectivity. Those same mechanisms do not possess the ability to save or maintain outcomes until connectivity is restored. Two alternatives then arise: adding to the web mechanisms with plug-ins or applets, or standalone learning applications.

Both of these alternatives raise a related problem of proprietary solutions. Plug-ins or applets have had trouble working seamlessly across different versions of browsers and platforms. They also require configuring systems to a unique standard, which adds to system maintenance headaches. Standalone learning applications currently use proprietary mechanisms, and it is difficult to find a solution providing sufficient breadth of content (as well as limiting flexibility).

Currently, there are platform-specific solutions. Avantgo has a Palm-deliverable content solution, and includes learning content. Note that there is no Learning Management System associated with the system. I understand others have or will soon have proprietary solutions for general purpose PCs as well, though they cannot be platform nor content vendor independent.

Some more general solutions are coming. Efforts to standardize learning technology are leading to a proposal for learning objects and interoperable systems to manage learning with these objects. Learning objects, as defined by the International Electronic Electrical Engineer's Learning Technology Standards Committee, are “any entity, digital or non-digital, which can be used, re-used or referenced during technology supported learning.” Several efforts are underway to define learning objects as a medium for content and system delivery, notably the Advanced Distributed Learning initiative's Standard Courseware Object Reference Model (SCORM). The goal is to be able to run any compliant content on any compliant system. Thus, proprietary solutions can use any available content, and report back results to any necessary systems.

And ongoing efforts to both improve the capabilities of standard web mechanisms, as well as constant improvement in mobile device connectivity and capability, are coming.

The second issue is device-independent delivery. As people choose idiosyncratic IA solutions, what is not desired is a solution that works for only one set of devices. Yet, the broad range of devices precludes specific solutions. This issue is already being solved through efforts to broaden the capabilities and flexibility of web mechanisms. People are working on more advanced information representations that separate out the content from the format. One example is eXtensible Markup Language, which holds the promise of allowing you to specify the content, and specify how it appears on each different type of device. It will require some revisions to the content development process, and associated tools before we reach the full promise, though companies are working on this currently.

Soon there will be essentially no distinction between mLearning and elearning. When we have seamless wireless networking, the power of a present-day supercomputer in our IA, high resolution full color screens at any size we prefer (or integrated into our visual field through special glasses), and flexible input from pen to keyboard, the distinction between desktop and mobile will disappear. And that day is not far off, so this is a relatively short-lived distinction!

What's the path forward?

With these issues and challenges, what might we expect in the months and years ahead? I’ll go out on a limb to suggest templates and tools that populate learning object models will become prevalent and, in doing so, will address device-independent learning. I also think that the major elearning vendors will come up with proprietary solutions to mLearning, largely through downloaded helper-applications that manage what you’ve done while offline. Eventually a consortium or an independent group will develop an open solution that will drive adoption.

In the longer term, as we realize that learning should move from an organizational function to an individual necessity, mLearning will likely move from a hosted service to device-resident applications we can carry with us wherever we go. Eventually, the learner will not know, nor care, where the learner model is kept, where the content resides, nor how the communication is handled. This will happen as cost drops, product power improves, and design takes into account a wider range of learning styles and lifestyle needs. And that will be true mobile learning.

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Clark N. Quinn Ph.D., has been innovating for business, education, government, and the not-for-profit sectors for over 20 years. He has been responsible for the design of award-winning online content, educational computer games, and websites, as well as intelligent learning, mobile, and performance support systems. Currently working through OtterSurf Labs, he previously headed research and development efforts for Knowledge Universe Interactive Studio and has held positions at the University of New South Wales, the University of Pittsburgh's Learning Research and Development Center, and San Diego State University's Center for Research in Mathematics and Science Education. Clark is writing a book about how to use games to teach which will  be out in 2005. To learn more, email him at clark@ottersurf.com.

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