If the key to survival in the knowledge era is to “learn a living” by integrating work and learning, then we must understand the relationship between education, work and technology.
Robert K. Logan, The Sixth Language: Learning a Living in the Internet Age
Corporate learning professionals have begun to achieve a better understanding of this relationship, and a new type of learning model is taking hold in the business world. The technology is new, but the learning theory has been around for some time. Organizational behavior specialists and learning theorists have been hammering out the dimensions of this type of learning model for more than 20 years. It is called experiential learning or experience-based learning.
Creating experience-based learning is now possible due to the availability of new tools and technologies. Contextual collaboration, simulation, business process modeling, workflow management and ambient intelligence (also known as smart technology) have all emerged as tools at the disposal of developers. They are used to create an increasingly seamless experience combining work and learning.
The worker’s experience is becoming highly automated through the use of virtual collaboration workplaces, real-time communication tools, business process management and business activity monitoring. The worker’s learning experience is being automated and layered over this virtual workplace through the use of expertise mining, social network analysis and smart ambient objects.
The individual’s work experience includes first-person experience, business conditions, productivity expectations, tools, time constraints, physical or virtual workplace conditions and other people. The interactions of these variables can create very complex and demanding working conditions. Legacy courseware models were never designed for this kind of flux, and a new kind of adaptive learning model has emerged. As each worker adapts to changes in the rapidly evolving business ecosystem, experience-based learning adapts to the evolving needs of the individual worker.
Tapping the Right Experience
Practitioners who develop content and services for the individual worker have a growing number of tools they can use. Tools are selected based on the type of applications used by particular people in specific contexts. Experience-based learning tools are often native front-ends to the actual applications used by the worker.
Many of these systems have native features that can capture a set of work tasks automatically as real workers perform daily work routines. The systems then allow developers, managers and workers to “run” the routines and optimize them for desired results.
One of the most interesting aspects of experience-based learning is the individual worker’s growing content development role. Many vendors now define the expert worker in the business unit, on the line and in the field as the combined subject-matter expert, content developer and end user of their products.
Expert workers use external tools outside of productivity applications to “record” themselves traversing multiple applications. Epiance, OnDemand (part of Global Knowledge) and RWD Info Pak are examples of this kind of tool. Instructional designers may not be required to create this kind of learning, but it is based on a solid learning model.
Putting Theory Into Practice
The theoretical underpinnings of experience-based learning in the business world derive in large part from the pioneering work of David Kolb, professor of organizational behavior at the Weatherhead School of Management at Case Western Reserve University. He since has commercialized the theory and now runs a company called Experience Based Learning Systems.
Kolb based his theory on the ideas of John Dewey, an early proponent of experience as an effective learning method. Dewey’s influence also can be seen in the work of other pioneers who have influenced the development of experience-based learning, such as Grace Coyle, Eduard Lindeman and Carl Rogers.
Related theories and practices include active learning, engaged learning, situational learning, work-based learning, contextual learning, problem-based learning and service-based learning. All of these models stress the importance of the learner’s experience within a real-world context as the primary condition required for learning.
Defining the Technology
So, what is it? Experience-based learning technologies are systems, applications and tools that merge learning with the real-time work experience of individual workers. Experience-based learning content corresponds as closely as possible to direct experience. Experience-based learning in the business world is learning that maps directly to everyday work life.
In educational environments, this is sometimes referred to as “situated learning.” Situated learning is very common in workforce retraining, rehabilitation and vocational training. It places a premium on the high-fidelity replication of not only the job’s tasks, but also the job’s environment.
Experience-based learning technology combines learning with the primary experience of workers as they perform tasks and interact with people in the real-time corporate ecosystem. The new technology is taking root in a fertile technical environment that includes real-time contextual collaboration, business process simulation, workflow management, social network analysis, expertise mining and smart wireless technology, also known as ambient intelligence.
Virtual Prairie-Dogging: Finding the Local Human Learning Object
Instant messaging is growing rapidly in corporate markets. It is becoming one of the most common experience-based learning technologies in the workplace (real and virtual). According to data released in August 2004 from a survey conducted by the Pew Internet & American Life Project, 40 percent of all adult Internet users in the United States are using instant messaging. AOL’s annual survey on instant messaging, also conducted in 2004, found that the use of instant messaging is growing annually by 71 percent in the corporate world.
Expertise mining is the most innovative collaboration technology on the market. This technology “mines” for human experts and puts workers and experts in contact with each other via instant messaging. This is closely related to the technology known as “skill-based routing,” invented in the call-center industry.
In both cases, the most highly valued learning object is the human expert who is best qualified to help a co-worker or customer accomplish a task. This is the high-tech equivalent of what is known as “prairie-dogging,” asking the local expert in the next cubicle for help. Creating this kind of learning requires the mapping of the expertise inside a corporation. IBM, AskMe and Tacit all offer tools that map human expertise.
A growing number of companies, such as Scion, Telispark, IBM, Microsoft and Oxford are now selling wireless products that allow workers to find and work with remote experts. Oxford Technologies sells a wireless product called Remote Technical Assistance Support System (RTASS). It was developed with the U.S. Navy’s Naval Undersea Warfare Center as a “telecollaboration” solution. It not only provides local real-time performance support, but also links remote experts with workers in the field. The solution provides what the company calls an over-the-shoulder presence of a remote supervisor via collaboration software, high-performance imaging and wireless broadband connectivity.
Wireless Peripheral’s SightLink provides visual communication “between an activity point and a consultation point.” According to the company, SightLink reduces or eliminates the need for specialized personnel to be physically present when tasks that require their expertise need to be performed. With SightLink, field personnel have immediate access to a remote expert for assistance. Because the product uses a high degree of two-way visualization software, the company calls this “working at the Speed-of-Sight.”
Bottling the Blue-Collar Experience
Experience-based learning technology is expanding rapidly into the so-called blue-collar workplaces. These workplaces include factories, shipyards, oil tankers, warehouses, auto repair shops, construction sites, mines, mills, power plants and even farms.
Forklift drivers at the Sears Warehouse in Columbus, Ohio, use touch-screen computers mounted on their forklifts. The devices provide decision support, inventory tracking and navigational advice, and even assess a worker’s performance in real time. The device (and the boss) can quickly identify productivity gaps.
Honda technicians use Nomad Expert Technician Systems from Microvision, a wireless, wearable computer system with a head-mounted display device that beams an image directly on the retinas of technicians. The system provides access to test data, mentors and repair information while service technicians work on cars. Workers see the information they need at the point of task, without having to turn away from the job at hand. The device is wirelessly linked to the Dealership Management System (DMS) populated with electronic repair manuals, work orders, vehicle histories and part inventories. The technicians can even access messaging and collaboration technology while they work.
Prescribing a Rich Clinical Experience
Health-care workers now carry handheld devices that contain decision support, patient histories and encyclopedias of medical information. Nurses use bar-code devices that read patient wristbands. The readout on the device prompts nurses to provide the exact dosage of the right medicine to the right patient at the right time. To their annoyance, it also asks the nurses to provide explanations if medications are not delivered on time. Vendors in this space include MercuryMD, PatientKeeper and ePocrates.
According to ePocrates, more than 350,000 physicians, pharmacists and other health-care professionals use its handheld drug reference application, called ePocrates Rx. The application features more than 3,000 conventional drug monographs and an alternative medicine database. It includes a drug interaction guide that has a built-in function that allows the user to simultaneously check up to 30 drugs for interactions across both “ethical and alternative medications.” The product includes an infectious disease guide, clinical tables and clinical guidelines. Also included is the proprietary MedMath calculator with more than 30 of the most commonly used medical equations.
Tablet PCs have experienced wide adoption in only two markets: academic and health care. Nurses have been ambivalent about the devices, but administrators and physicians have warmed up to the new technology. Interestingly, physicians often use the devices for real-time patient education. Complex procedures can be explained quickly by showing patients simulations and diagrams of the procedure. Doctors can show patients how medical technology products work.
Not surprisingly, there is a thriving niche industry of service firms that develop medical device training and patient education content.
Sensing Smart Ambient Objects
Workers in many industries are now using handheld scanning devices, such as radio-frequency identification (RFID) and smart-tag readers, which scan data in bar codes and chips that are embedded in machines, devices and objects. The readouts provide static data, as well as highly contextual decision support and procedural instructions. Some of these smart tags are proactive: Machines in the plant alert workers when they need attention. In this case, content stored on the devices is generated by both human developers as well as the machines themselves when their microelectromechanical system (MEMS) sensors indicate problems.
Questra sells remote-device-monitoring software that proactively alerts service personnel when things break or when maintenance is needed. Using a form of predictive maintenance, the machines are able to “self-diagnose” themselves and send detailed alerts to remote technicians. The technicians can often fix the problem from a remote location in a sort of collaboration with the diagnostic software.
Dallas Semiconductor’s iButtons are small metal cylinders with an embedded chip that allow maintenance technicians to enter information in 32 text fields on the chip. Mining and manufacturing companies use iButtons to tag machines and equipment. The iButtons contain inventory data as well as maintenance history and short bursts of task support, helping workers quickly fix problems encountered in the past by other technicians. Each time a worker “touches” a piece of equipment with an iButton, he updates the data.
SAT provides wireless workflow solutions to the energy sector. The company’s IntelaTrac “reads an RFID tag that a worker scans on a piece of equipment and then provides device-specific data about what to check for, how often to check for it and what steps to take in the event of an abnormal reading.”
The rapid proliferation of ambient technology like smart tags, RFID and handheld devices to communicate with them has begun to create a global environment of pervasive intelligent information. Wi-Fi “hot spots,” wireless broadband Internet access and satellite connectivity have extended the virtual work experience everywhere.
Desktop computing is now being replaced by pervasive, ambient technology that distributes experience-based learning everywhere, all the time.
Sam S. Adkins is an independent learning technology researcher and chief research officer at Ambient Insight. Sam specializes in learning and productivity technology research that spans several converging technologies including simulation, mobility, business process management, collaboration, workflow management and Web services. E-mail Sam at firstname.lastname@example.org.