Learning Solutions Magazine
     [Forgot Password?]
Your Source for e-Learning
Technology, Strategy, and News
ARTICLES      
RSS feed RSS feed

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

Many mobile devices can now retrieve and deliver information, even based on the user's location, and on what the devices themselves can see. How can designers make use of location-based services (LBS) to better support learning and performance?

The old real estate adage “Location, Location, Location” is gaining new meaning with current developments in mobile- and location-based technology. Nowhere is this truer than for mobile devices when workers use them to support learning and performance away from their desks and their computers.

With the advent of location-based services and two-dimensional bar-coding, for the first time many mobile devices can retrieve and deliver information based on the geographic position of the user, and on what the devices themselves can see there.

At this intersection of information and location, we find an explosion of novel and creative applications. These include advanced social networking programs that allow users to find each other and coordinate activities, and location-specific data broadcasts that provide detailed information for mobile professionals. Mobile phones, especially, with their cameras and Global Positioning Systems (GPSs), are the key platforms carrying these applications.

But how can instructional designers harness location-based services (LBS) to support learning? A new wave of applications promises to provide a fresh range of delivery options. This first-generation software demonstrates the possibilities of LBS, and suggests that innovative learning strategies may be just around the corner.

In this article, we explore some of the emerging technologies. This is a very early look, and at this point there is more potential than there are practical examples of its use in e-learning. But even now, there is definite potential for use in performance support and just-in-time information delivery in learner populations already equipped with the right devices.

New applications

Most of the new applications related to location-based services do not directly support learning or performance as their primary purpose. At this time, the technology is very basic, and furthermore, not many learners actually own devices that support it. However, we would like to begin by reviewing what existed as of last week. Many readers will be aware of the release on Friday, July 11, of the iPhone 2.0, with incorporated GPS, accessible developer environment, and online application store. This is only the latest tip of the iceberg. There is much, much more, as you will see.

Hardware

Most location-based services get their power from global positioning services built into mobile devices. Until recently, GPS relied on independent devices that only provided location-related functions – latitude and longitude, height above sea level, direction of travel, and speed. With the advent of so-called smart phones, manufacturers began building GPS functions into mobile telephones.

The latest generation of many telephone models now includes GPS. Among these, in addition to the iPhone 2.0, are phones with even more powerful systems and software built in, such as the AT&T Tilt (also known as the HTC 8900 or TyTN, depending on the cellular provider), the Nokia N95, the latest Blackberry models, and many others. Other phones are able to link to separate GPS units with a cable or via Bluetooth radio, and these phones can run software that uses the GPS data.

Another hardware technology that is important to location-based services is the mobile phone camera, when used to read 2D barcodes. A 2D barcode is one in which the elements of the code appear as small black or colored squares within a larger square grid. (See Figures 1 and 2 for examples.) Thus, 2D stands for “two-dimensional,” to distinguish them from the older linear UPC bar codes so familiar from retail settings over the last thirty years.

 

 

Figure 1 A QR code, containing the URL for The eLearning Guild’s Web site. A mobile phone with a camera and QR scanner software can read this code and open the Web page.

 

 

 

 

 

 

 

Figure 2 An EZcode, containing the URL for The eLearning Guild’s Web site. A mobile phone with a camera and the EZcode scanner software can read this code and open the Web page.

 

 

 

 

With the appropriate software running on the parent device, a digital camera can scan the 2D code. (See Sidebar 1 for a discussion of 2D barcode systems.) Typically, these codes can contain information ranging from plain text to URLs (Web addresses), and from telephone numbers to computer instructions. The digital camera could be a Web cam attached to a desktop computer, but most often now it is a mobile phone camera.

 

Sidebar 1 The fast-growing (and confusing) world of 2D barcodes

There are a number of different approaches to encoding data in two-dimensional arrays for reading by cameras, but three particular systems are most significant world-wide (in terms of visibility and familiarity).


QR (Quick Response) is the most familiar 2D barcode scheme, especially in Japan and in China, where advertisers and retailers have used it for several years. It is so familiar that some people use “QR” as a generic term for all 2D codes, but QR is a specific type which the Japanese firm Denso-Wave created in 1994. These 2D barcodes appear on magazine covers, in newspapers, and on billboards, where consumers can easily use their mobile phones to read the information encrypted in them. QR codes contain all of the data within the barcode itself, and there are a number of related systems for generating the codes. Some systems (“Design QR”) can create a grid that incorporates an image, or that uses color. A QR code nominally can contain up to 7089 numeric characters, or 4296 alphanumerics, or 1817 kanji/kana characters, or 2953 bytes of 8-bit binary data, but variations on the code have different limits. The limit seems to be camera resolution. While Denso-Wave owns the patent on QR code technology, the company does not exercise its rights, which effectively makes QR code™ an open standard. (“QR Code” itself is a registered trademark of Denso-Wave Incorporated in Japan and elsewhere.)


Data Matrix code is more widely used in Europe, and increasingly by the U.S. Department of Defense, mostly for marking small items. Data Matrix codes can be very compact (2 or 3 mm on a side), and can contain up to 2335 alphanumeric characters in a matrix. The size of the matrix depends on the amount of information encoded. Data Matrix code may appear in square matrices or in rectangular arrangements. The data, as with QR, can be either text or raw data. There are several variations on the Data Matrix code, mainly intended to reduce errors when reading damaged codes. One company, Semacode, converts internet URLs into Data Matrix symbols to encode Web addresses. (Editor’s Note: Do not confuse Semacode with Semapedia.org, discussed later in this article. The two are not related.) Like QR, Data Matrix is a free standard, covered by an ISO standard. It is in the public domain, and is free of licensing and royalties. However, all documentation is only available for a fee. RVSI/Acuity CiMatrix (acquired by Siemens AG) created the Data Matrix system. There is some dispute about Data Matrix. Acacia Technologies claims that Data Matrix infringes on one of their U.S. patents. This claim is pending resolution in the courts. However, Acacia’s patent expired in 2007, so it only affects previous usage if the court finds for Acacia.


EZcode is a 2D code system coming into use in the United States. Invented by ETH Zurich, and licensed by Scanbuy, EZcode matrices contain a single “index” number that relates to content held on a central server, rather than containing the information itself. The EZcode system transmits the index code to the central server via a wireless connection. The server retrieves the content (alphanumeric textual information, telephone number, internet URL, or instructions to the mobile device that scanned the code), and transmits it back to the scanning device, where it is displayed or executed. The scanning device depends on having a wireless connection to the Internet to receive the information indexed by the code. Scanbuy offers scanner software that runs on any operating system and on popular mobile phones, including Windows Mobile phones, Blackberry, Nokia, and Palm Treo (among many others). As with Data Matrix, EZcode is the subject of patent infringement claims. Since 2004, NeoMedia and Scanbuy have been in court over NeoMedia’s claim that Scanbuy’s use of an indexing system infringes on NeoMedia’s patents. However, at this point, Scanbuy is moving forward with a campaign to persuade advertisers and publishers to use EZcode, and some examples have appeared in the last couple of years.

Scanner (reader) downloads:

QR code

http://reader.kaywa.com (Does not support Windows Mobile)
http://www.quickmark.com/tw/En/basic/download.asp (Covers many phone models, including Windows Mobile, requires registration)

Data Matrix

Both the QuickMark scanner and the Kaywa scanner can decode Data Matrix codes

EZcode

In the United States, text SCAN to 43588
Elsewhere in the world, direct your mobile phone browser to www.getscanlife.com.
Note: The EZcode scanner will decode only EZcode in the United States, Mexico, and Denmark. In Spain and France, it will decode EZcode and Data Matrix. In China, it will decode EZcode and QR code. It will decode EZcode anywhere in the world.

Creating 2D codes

To create QR codes, direct your browser to: http://qrcode.kaywa.com or http://www.quickmark.com.tw/En/diy/?qmLink (no login required) or just Google “qr code generate”
To create Data Matrix codes, see: datamatrix.kaywa.com or http://invx.com (also generates a QR code for the same content)
To create EZcodes, go to: www.scanlife.com (requires registration, limit three EZcodes for personal use)

 

Software

How do organizations use the location data and the bar-coded information that mobile devices can now acquire? Many of the applications are straightforward and obvious. By giving directions, GPS provides performance support for drivers, sales people, and others who must move efficiently from one location to another. 2D barcodes can provide information about products and inventory, links to company Web sites and sales notices, among other things. If that were all that these services provided, they would be little more than novelties.

What makes the difference? Software and the processing power built into mobile devices, and wireless communication between each individual device and servers, other devices, and the Web “cloud.” Here are some examples, and potential applications to e-Learning.

Location-based social networking

Applications like Loopt (http://www.loopt.com), Whrrl (http://www.whrrl.com) and nrme (http://www.nrme.com (Editor's Note: As of March 29, 2010, this website appears to be no longer active.) ) (for the iPhone only) allow the user to broadcast his or her location and receive updates on their friend’s movements (as long as the user and the friend use phones that can run the same software and have service from participating providers). Users can share recommendations on restaurants, and meet up for lunch spontaneously when they happen to be in the same area. All three of these applications rely on built-in GPS in mobile phones.

Admittedly, these specific applications may be trivial as far as learning is concerned, and there is the added drawback that GPS generally requires that one be in an area with an unobstructed view of the sky (i.e., no roof, no tall buildings blocking direct visual access to the GPS satellites). However, they do demonstrate a possibility at the intersection of social networking (you can only get the locations of friends who give you permission to know) and location data.

Sense Networks has developed an application for the iPhone and Blackberry, known as Citysense (http://www.citysense.com), that takes user location data a step further. Citysense has as its goal the creation of traffic maps that correspond to specific tastes and subcultures.(Editor’s Note: This is not the same application as CitySense at www.citysense.net.) In its current release, Citysense combines live anonymous data (GPS- and WiFi-derived locations of users in San Francisco) and past data (again, GPS- and WiFi-positioning data, but from previous months) and superimposes it on a city map. This allows users to visually identify “hot spots” and overall activity in the city. Users can click on a given “hot spot” and the system will bring up current information about bars and restaurants in that area. In the next release, by analyzing a user’s movements, and cross-referencing them with restaurants and nightspots, Citysense can build a user profile and recommend venues based on that profile. With the ability to learn the user’s preferences for food and entertainment, Citysense will function essentially like TiVo (digital video recording) for physical locations. This data could be incredibly useful for corporate users who want to learn about the traffic and use patterns of the cities in which they operate. This is still a little distant from the kind of learning that we usually deal with, but it is closer, and it demonstrates the ability of software to aggregate billions of data points into a picture that provides useful real-time information to a user.

Other applications may align more closely with the requirements of mobile learning.

Image navigation and geo-tagging

Breadcrumbz for the Android platform, and GPSed for Blackberry, Nokia N95, and Windows Mobile smartphones allow the user to navigate with images instead of relying on maps. (Editor’s Note: Android is the first complete, open, and free mobile platform, developed by The Open Handset Alliance, which is headed by Google. The main site is at http://code.google.com/android/.)  

Breadcrumbz (http://www.bcrumbz.com) supports navigating by pictures alone (or by pictures and map together). Users create routes with their smartphones, as the GPS in the phone records the route, and as the users take pictures of landmarks with the phone camera. When the user takes a picture, the software records the location, creating a geo-tag for the photo. The user can then store and share the recorded route. On playback in another smartphone, the phone’s GPS will visually guide the new user along the route, and will display the landmark photos at the correct locations, giving visual cues and reassurance. Breadcrumbz also supports voice instructions, and works in areas where GPS loses its signal. It does not require an Internet connection. You can supplement routes with rich content.

The developers refer to this as “user-created geo-content.” (Editor’s Note: Watch the video on the Breadcrumbz Web site, which involves a route through Jerusalem by car and on foot, and this makes much more sense.) This is performance support, at the least, for pedestrians and cyclists, supports digital “guided tours,” and could easily be a learning application for such jobs that involve getting around in areas where GPS maps do not exist or are of no use.

GPSed (http://www.gpsed.com) is similar to Breadcrumbz, and supports more mobile phone models. It offers a site where users can publicly post their tracks, as well as archive them privately. Users can display their tracks on Google Maps or Google Earth, and attach photos to GPS tracks from Picasa and Flickr. It does not support “playback” of a track on another mobile device. (Editor’s Note: Again, this makes more sense if you look at some of the featured tracks posted on the GPSed Web site.)

Since these programs focus on navigation, they use the geographic data composited with the images to prompt the user to turn, or to take notice of a specific entrance (in the case of Breadcrumbz), or to place the images in the right place on a map (in the case of GPSed). But the idea of accessing images of the user’s physical location laden with relevant data could find ready application in the context of mobile learning.

This technique could be adapted to quickly orient employees to a new workplace, or to provide mobile professionals with a convenient instructional tool. For example, property appraisers and building inspectors could create image-based Wiki’s of a given site. These Wikis would be an ideal way to store information about building features and code compliance, which they could also use to develop tutorials for students. Such tutorials would be an ideal implementation of Bruner’s Constructivist theories of learning (see http://tip.psychology.org/bruner.html). Almost like an interactive scavenger hunt, this form of instruction encourages the student to learn through self-directed experience.

Seero (http://www.seero.com/), a ”journalism” application (actually, “video-journaling” might be a better description), approaches location-based learning from a different perspective. Instead of focusing on providing information to the user based on their location, Seero enables users to become “geo-broadcasters.” It supports producing and sharing live and archived, geo-tagged video streams referenced to the user’s physical location. The program also seeks to provide the geo-broadcaster with a range of local information in order to provide them with context for their broadcasts. Viewers can then search for these broadcasts, and “tune in” to a specific geographic area or watch an archived video of a location. During playback, a separate window displays a moving map of the user’s location, synchronized to the video. (Editor’s Note: The featured videos on the site make this much clearer.) Seero has the potential to become a powerful tool for any learning application where geography is a relevant factor.

Interview with Ernie Thor

We had the opportunity to discuss the future of location-based learning with Ernie Thor, a member of The eLearning Guild, and a senior instructional Designer at AT&T. He has thirty years of experience in the field of instruction design; ten of those years focused on wireless training. He has worked for many companies, including Boeing and Bank of America. His expertise provided much of the foundational knowledge for this article.

Ernie described how the Bluetooth protocol, which originally provided users with information about local computer and printer settings, was a forerunner of location-based services. The limitation on Bluetooth is that it is highly localized, with an effective range of only a few meters. But providing location-based services over a mobile network allows for ubiquitous coverage.

Enthusiastic about the potential for these new services, Thor said, “[Location-based Learning] will provide the means to give an employee what they need, when they need it, wherever they need it, and it can be specific to their location. It’s another tool in the belt of just-in-time training.”

To explain the utility of this instructional method, he described how certain skills lend themselves more readily to one form of instruction than another. For example, a video is not the best way to learn to ride a bicycle, because you need to develop the motor skills necessary to maintain control. In the same way, there are skills sets and information that can derive tremendous benefit from an instructional method that incorporates location-specific information.

Ernie also discussed how the evolution of training technologies transforms the very nature of instructional content. When he began his career, 16mm educational films were the gold standard. The time and expense required to produce movies greatly restricted their potential applications. But with the introduction of affordable video cameras, and even more so with the proliferation of Web video, the cost of production dropped quickly. In this environment, training videos can be short, cheap, and very spontaneous. In the same way, mobile technology will facilitate the development of new modes of instruction.

 

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 21st 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.




(2)
I appreciate this article
 RSS feed

Comments

Login to comment

Be the first to comment.

Related Articles

Seven industry experts who will speak at mLearnCon in San Diego next week, answer three simple questions about mobile learning (mLearning): What are the obstacles to practical delivery of learning via mobile devices? What will it take to solve these problems? When do you think this will happen? If you create or manage online learning in your organization, you must read their replies.
Discussion of Mobile Learning (m-Learning) has been going on for almost ten years, and we only now seem to be approaching actual deployment. However, there are still some barriers. An industry expert presents a summary of what it will take to bring m-Learning to real life.
One of the most important things we in e-Learning today can do for the generations to come is to support effective use of technology in primary and secondary education. For the past several months, Anne Derryberry has written about her experiences as a volunteer in her local high school. Now Marc shows you eight more ways you can make a difference in your local schools.
Advertise Here

Advertise Here

Advertise Here

Advertise Here

You need to upgrade your Flash Player
This interactive requires Flash Player version 7 or higher.