On-the-Spot Learning: Coming Soon to Your Location?

Positional technology

With regard to location-based learning, two systems determine the scope of services that you can offer. On the one hand, there are the positional systems that determine the location of the user, and on the other are the user interfaces that allow interaction with data at the learner’s location.

Let’s continue with a very brief exploration of some current positioning techniques.   

Systems that find the learner

In North America, 911 is the emergency telephone number that connects citizens to dispatchers for local fire, police, and emergency medical services. While it is a fairly straightforward process to determine the location of a caller who uses a landline phone, it is much more difficult to know a mobile phone caller’s location. Wireless Enhanced 911 service solves this problem by using radiolocation from the cellular network, or by using GPS data from the mobile phone if it is so equipped.

If GPS data is not available, there are many different techniques for locating a mobile phone. All of these rely on some combination of triangulation and signal timing analysis. With a single tower this narrows the location to within about a thousand meters. With information from additional towers, the location becomes more precise, and with three points from which to triangulate it’s possible to determine the position of the mobile device with a fair degree of accuracy.

But the accuracy of cell tower triangulation doesn’t come close to that of the Global Positioning System. GPS can provide a location that is accurate to within a few meters, and it can provide this accuracy anywhere on earth, because the signals originate from satellites in low Earth orbit rather than from terrestrial towers. However, achieving this accuracy takes time. From a cold start it can take between two and twelve minutes for a GPS device to acquire the signals from satellites and determine its own location.

The solution to this problem has been the development of Assisted GPS (AGPS). AGPS uses the cellular network, in concert with GPS, to reduce the time it takes to determine location, and in some cases to improve the accuracy of the measurement. The wireless carriers maintain powerful GPS units linked into their networks that continually update a database of satellite locations and other pertinent information. When a mobile device makes a location request, data referenced by cell site is forwarded to the phone, allowing it to acquire its position much more quickly.

With respect to mobile learning, it’s not necessary to go further into the specifics of these positioning technologies except to recognize that the fundamental relationship is one between accuracy and latency. The technology exists to determine location very precisely, but the more precision that is required, the longer it will take to provide it. (See Figure 3.)

Figure 3 Latency: Time vs. location accuracy for GPS, Assisted GPS, and Cellular ID

Using 2D tags to retrieve information for the current  location

Another approach can provide information tied to the learner’s location, with very low latency, and it may hold the most promise for location-based mobile learning. Rather than rely on signals from towers or satellites, applications are in development that rely on image processing to recognize contextual cues from the environment. Similar to how a person is able to determine location by recognizing landscape features, familiar places, and buildings, mobile devices can “recognize” specially designed signs and symbols – the 2D barcode tags discussed earlier.

The most basic way to use 2D tags might be to encode links to a map or diagram, providing a kind of “You Are Here” waypoint. This could be useful for new employees learning their way around inside a building, where GPS is of no use or unavailable. However, there may be better ways to support more meaningful learning by using 2D tags.

Semapedia.org (http://www.semapedia.org) is a non-profit, community-driven project that has the goal of “connecting the virtual and physical world by bringing the right information from the Internet to the relevant place in physical space.” The project does this by helping individuals create and distribute Semapedia Tags. These are simply QR code tags that contain a URL. Specifically, each Semapedia Tag provides a link to an article in Wikipedia, or one of its sister Wikiprojects (Wikibooks, Wikinews, Wiktionary, Wikiquote, Wikispecies, Wikipedia Commons, and Wikisource).

How does this facilitate location-based learning? Individuals have posted just over 31,000 Semapedia Tags in various places around the world so far. Whenever someone scans one of these tags, using the camera in their mobile phone and a QR code reader, they will obtain the URL of the Wikiproject page relating to that site. When they load that URL in their mobile phone, their browser will open that page and they will be able to read about the tagged place or item.

Any organization can set up a similar system, using URLs of pages on their own servers. The tags for such a private system could contain URLs, brief text (such as instructions), contact information, and so on. URLs could also open audio, still photo, or video files. The possibilities for this approach, for example in new employee orientation, are endless. The advantage to this approach to location-based learning, is that it enables mobile users to access very specific, contextually-relevant information, and do so indoors where precise radiolocation is more difficult.

Concierge vs. tracking services

Location-based services fall into two distinct categories, and the central issue differentiating these categories is the question of privacy. The ability to locate someone, anywhere and anytime, is tremendously useful, but potentially invasive. The idea that something may be tracking and recording your every movement is unacceptable to many users. A recently published study conducted in Europe used mobile tracking technology to measure the movements of 100,000 people, without their knowledge or consent. And while precautions were in place to preserve anonymity, this study has generated a lot of controversy. The similarity of the technology in this study, and that in a service such as Citysense, described earlier, is apparent.

One way to defuse the situation is to provide two distinct services; one with authorized persistent tracking, and another where only a specific request will result in disclosure of the user’s location. This allows you to make a distinction between personal and organizational productivity services. When the user is off the clock, they can freely access services while maintaining their locational privacy, but when on duty, the corporate office could ensure that employees are on track to accomplish a field assignment. These two service models are known as “concierge” and “tracking.”

A concierge service is one in which the user specifically makes a location-based request, and the system accesses the location data to route the relevant information. But a tracking service accesses location data continually. These two approaches have a significant impact on the range of learning applications that you can offer to the user. Within the concierge model, the user must actively make a request for information. The tracking model however, allows applications to push out data to the mobile device based on changes in location.

Geofencing is an example of what’s possible using location tracking. You can reference geographic boundaries, delineated in a database, to information delivered to a mobile device as it moves from one region to another. Multiple sources of geofencing data would allow users to choose from a whole range of applications. A local history overlay could guide users to areas of interest, and help smaller towns and cities create directed tours such as Boston’s Freedom Trail. Large college campuses could provide orientation services, and mobile professionals such as realtors could receive on-site zoning information and future land-use provisions. Rave Wireless (http://www.ravewireless.com) is one company that is already providing many of these services in a software package that tracks bus routes, and broadcasts location-specific security alerts to students on college campuses.

Augmented reality

Ernie Thor’s apt characterization of the relationship between instructional technology and the corresponding instructional techniques and strategies, prompts us to ask whether the technology has advanced sufficiently for location-based learning to compete as a viable alternative to more established methods. With regards to specific applications like geofencing, you can make a strong case. But speaking more broadly, the challenge to location-based learning is that it requires the user to synthesize two spaces at once. The user must simultaneously navigate physical and informational space. In a desktop environment you can accomplish this as simply as opening separate windows, or creating a “mash-up” of data types.

These juxtapositions can form the foundation for remarkably effective learning experiences. Henry Jenkins, director of the comparative media program at MIT, has been a strong advocate for the use of these innovative learning strategies that incorporate new media and gaming. And recent approaches like Jane McGonigal’s work with alternate reality games, and Marcelo Milrad’s AMULETS program (see the References at the end of this article), have found ways to cut the ties with the desktop, and take these learning experiences out into the world.

But when one of the data types incorporated into a mobile learning application is sense experience, it’s difficult for current user interfaces to harmonize data sources unobtrusively. The current generation of devices capable of accomplishing this synergy (other than in the cockpits of multi-million dollar fighter jets) is anything but elegant. If you wish to resemble a Cyborg from an 80’s science fiction film, a number of heads-up displays will fill the bill. Given the surprising adoption of the Bluetooth headset as a fashion accessory in certain quarters, perhaps enormous head-mounted displays will become increasingly common, although the authors remain skeptical.

Fashion considerations aside, there are safety issues to overcome before user interfaces that enable location-based learning achieve mainstream acceptance. A study conducted by the Virginia Tech Transportation Institute found that using mobile devices while driving could increase the risk of collision by 300%. User interactions such as dialing a number or text messaging accounted for the highest accident rate, whereas merely speaking on a mobile phone resulted in a smaller increase in accident probability.

The obvious conclusion is that interacting with mobile devices distracts the user from his surroundings. In a car, these moments of distraction can be catastrophic, and at other times they can be inconvenient or socially awkward. But the greatest potential for location-based learning will require the user to seamlessly integrate two sources of information simultaneously.

A typical mobile device requires the user to divide his attention between the user interface and the physical world. This is why the average user profile for such devices lasts only a few seconds. Heads-up displays address this difficulty by compositing information in the visual field, but we’ve already addressed the shortcomings of these interfaces. Another promising approach is to divide the senses, and provide audio data while leaving the visual field free of distraction.

Ambient, the creators of “Audeo” have taken a very exciting step in this direction. They have developed a collar that is capable of detecting neurological speech impulses transmitted through the skin to the throat. Much more than a microphone, this approach allows the system to detect speech without the user actually speaking. As the words form in the mind, the sensors are able to detect and translate them into synthesized speech or computer instructions. They are developing this technology initially as a speech aid for the disabled, but Ambient intends for it to have much broader application.

Audeo will enable users to interact with a mobile device without giving any indication that they are doing so. The unobtrusive collar can receive silent speech input directly from the central nervous system, and respond via a headset. This type of interface will allow the user to effectively integrate data and physical space, creating the most compelling form of location-based learning. People often refer to this capability, of melding physical space with a data overlay, as Augmented Reality.

Practical auditory augmented reality systems are already in development, and will see commercialization within five years. Visual systems are not far behind. DARPA has announced funding for “the creation of micro- and nano-scale display technologies for the purpose of creating displays that one can wear as transparent contact lenses." And a research team from the University of Washington already has already begun work on a contact lens display:

“The UW team uses a technique called self-assembly to manufacture the eyewear. Researchers dust a specially designed contact lens with micro-scale components that automatically bond to predetermined receptor sites. The shape of each component dictates where it attaches.”

Obviously, commercial applications are more than a decade away, but this research is illustrative of an important trend in mobile learning and performance support. Interface transparency will become increasingly important to mobile applications in the future, and the ability to deliver data without disrupting social interaction or situational awareness will be the distinguishing features of next-generation user interfaces.

Conclusion

What would you do with location information? How would you use it to improve the productivity of your workers? Could you elevate performance standards amongst average workers to match the high performers, improve logistics, and provide just-in-time knowledge transfer throughout the organization?

With fuel prices at record levels, some shipping companies have developed ways to dynamically update routes and coordinate their fleets with much greater efficiency. In light of energy costs, the return on investment for these services has never been higher. You could implement this form of dynamic performance support to improve the operations of any business with mobile employees.

Other organizations are looking at the potential for location-based information to coordinate sales reps, and provide them with geographically relevant information about existing and future clients, to help increase sales and customer satisfaction.

Location-based services provide a new range of options and opportunities to instructional designers and corporate learning officers. How can you harness these services to enhance your business?

References

Langendorf, Daniel. “Location-based services like Whrrl on iPhone to usher in Internet of people, places, and things” Last 100. May 27, 2008. http://www.last100.com/2008/05/27/location-based-services-like-whrrl-on-iphone-to-usher-in-internet-of-people-places-and-things/

Tech Gadgets “Mobile Phones help to analyze historical and real-time location data” Tech Gadgets 2008 http://www.techgadgets.in/mobile-phones/2008/11/mobile-phones-help-to-analyze-historical-and-real-time-location-data/

Yoffe, Amos. “BreadCrumbz” 2008. http://bcrumbz.com/

Bruner, J. (1973). Going Beyond the Information Given. New York: Norton.

Nicole, Kristen “Seero Live Streaming Widgets with GPS, Debut at Where 2.0” Mashable.com: May 10, 2008. http://mashable.com/2008/05/10/seero-gps-embeds/

Kawamoto, Dawn. “Study tracking people via cell phone raises privacy issues.” Cnet June 5, 2008. http://news.cnet.com/8301-10784_3-9960687-7.html

Carliner, Leah. “Wireless may soon be all the ‘rave’.” GW Hatchet, September 18, 2006.

Jenkins, Henry. “Confronting the Challenges of Particpatory Culture: Media Education for the 21^st Century.” MacArthur Foundation, 2006.

McGonigal, Jane. "The Puppet Master Problem: Design for Real-World, Mission-Based Gaming." Second Person. MIT Press, January 2007

Spikol, D., & Milrad, M. “Combining Physical Activities and Mobile Games for Designing Novel Ways of Learning.” Proceedings on the IEEE international conference on “Wireless, Mobile and Ubiquitous Technologies in Education (WMUTE 2008). Held in Beijing, China, March 23-26, 2008.

Neale, Vicki, et Al. “An Overview of the 100-Car Naturalistic Study and Findings” National Highway Traffic Safety Administration Paper Number 05-0400.

Simonite, Tom. “Nerve-tapping neckband used in ‘telepathic’ chat.” New Scientist, March 12, 2008.

Shachtman, Noah. “Pentagon: ‘Augment’ Reality with ‘Videogame’ Contact Lenses.” Wired, March 20, 2008.

Sofge, Erik. “Souped-Up Contact Lenses Promise On-Demand Bionic Eyesight.” Popular Mechanics, April 2008.

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