Brent G. Wilson, University of Colorado at Denver www.cudenver.edu/~bwilson
Paper presented at the Provider Educators' Symposium '98: Improving the Health Care System through Provider Education, Boston, April 1998.
Web address: www.cudenver.edu/~bwilson/empower.html
I belong to a graduate academic program named Information and Learning Technologies, or ILT for short. I like that name, although I'm not aware of another program with this same title. Most programs like ours are called Instructional Technology or Instructional Systems Design.
I like our title because of its power and generality. The whole world knows what IT is--Information Technology. Businesses can't live without an IT department. Learning technologies put traditional technologies, including IT, to the service of learning and performance improvement. In this way, we as learning technologists complement IT, but we also appropriate various information, network, communications, and computing technologies as they focus on a core function of today's organization: learning.
Much is being said now about the "learning organization." A key insight, popularized by Peter Senge's seminal book The Fifth Discipline (1990), suggests that businesses, in order to survive in today's fast-changing competitive world, need to be life-long learners right along with their workers. Organizations can learn and adapt just as we do. A variety of tools support individuals and organizations in their learning goals. Examples of learning technologies include computers, networks, communication programs, groupware programs that support collaborative work, presentation programs, and knowledge-management systems that facilitate sharing information and connecting knowledge to practice.
In addition to these "hard" technologies, a number of "soft" technologies--models, strategies, methods, techniques--are available that give direction and focus to the learning enterprise. Soft technologies include systems planning models, models of collaborative work and collaborative learning, strategies for team problem solving and communication, and methods for presenting information effectively.
Together, hard and soft learning technologies constitute a powerful
repertory of tools available to support learning and performance
in work situations. But new technologies are constantly being
developed and promoted. Notable lately are networking and communication
technologies that facilitate learning and working from a distance.
With such a rapid pace of development, learners and workers can
easily become confused. Some may invest inordinate time and resources
chasing after the latest fad. Others may retreat back into a shell
of proven practices, but growing further out of touch and further
behind competitors. At occasional intervals, we benefit from taking
a broad view of where we've been, where we are now, and where
we're going. This short paper is intended to provide such a broad
view of learning technologies, and to highlight why some recent
developments are especially exciting as they open up new possibilities
for learning.
Over the past forty years, conceptual frameworks for learning
support have tried to keep up with constantly developing technologies
and theoretical advances in cognitive science and education. We
trace below three basic paradigms for thinking about support for
learning and performance on the job. Admittedly, these paradigms
underlie a variety of specific methods and models, and are not
cleanly articulated and defined in the literature. My purpose
in contrasting these three views is to highlight an overall trend
toward greater flexibility and empowerment, and to show how each
paradigm reflects the technologies available at the time of its
initial development. Figure 1 presents the three paradigms discussed
in this paper: instructional design, performance support, and
network systems.
| Instructional Design | Performance Support | Network Systems |
| Pre-packaged
Outside control Out of context | Outside expertise
In-context learning User control | Open expertise
Dynamic Community control |
Figure 1. Evolution of learning technologies to better support
work performance, from instructional design to performance support
systems to network systems, which include knowledge-management
systems and communications tools.
Systematic models for designing instruction became standard practice in the 1960s and 70s. A key accomplishment during these years was the Armed Forces' adoption of a systematic planning model for all their training requirements (Dick 1987), which continues in revised form to this day. Instructional design (ID) has developed into its own discipline with research journals, academic departments, and a community of practitioners located primarily in higher education, government, and corporate settings. Figure 1 highlights three important features of ID models:
1. ID models produce pre-packaged solutions. The systematic planning prescribed by ID should be familiar to engineers and computer systems analysts: needs identification and problem formulation, followed by solution design, development, implementation, and evaluation. These generic planning stages proceed logically and rationally to solve problems of various kinds, not just instructional problems. ID planning typically takes place on behalf of a third-party client, with the resulting instruction delivered as a finished package or product.
2. ID models rely on outside expertise. Content expertise is necessarily pulled out of the work context and packaged into the product. The design team is comprised of design and production specialists, working in concert with subject experts freed up from their normal work and temporarily assigned to the design team.
Because of the separation between developer and client, and between subject experts and consumers, control shifts from the practitioner community to the design labs where products are developed. ID products can be extremely useful, but control lies in the hands of the designers, not in the hands of the users themselves.
3. By its nature, instruction is removed from the work context.
Sometimes people need to be prepared before they start a new job.
Learning is often more efficient when workers are pulled away
from their daily tasks, grouped together according to their knowledge,
and trained directly on identified skill deficits. Instruction
is predicated on this notion. When I do instruction, I am not
working. The two spheres are kept separate for convenience and
efficiency.
The limitations of ID models became apparent as alternatives were developed. A new generation of learning supports became available in the 1980s and 90s, known generally as performance support tools or electronic performance support systems or EPSS (see Gery, 1991). The field of human performance technology subsumes these concepts as well as other interventions designed to improve work performance (Stolovich & Keeps, 1992). These models shift attention away from learning per se and toward job performance. Workers need to be able to perform in a variety of settings with a number of tools. To support effective performance, information and procedures should be available when they're needed within the natural work environment. Many times workers don't need to store knowledge; they can simply refer to a help system or job aid. This is often preferable to out-of-context instruction because it is more efficient, but also because workers often learn better in authentic performance settings.
In some ways, the performance-support movement constitutes a radical departure from traditional instructional design. In other ways, though, the two paradigms share assumptions. Key features of this second paradigm are briefly outlined below.
Solutions are still pre-packaged and outside are still in control. Just like designed instruction, EPSS systems are designed by outsiders and provided to end users in pre-packaged forms. Help systems, job aids, and EPSS systems all bear the stamp of traditional packaged solutions. EPSS developers use linear planning models similar to ID. Workers rely on the outside experts to diagnose the problem, determine the need, and develop and package the right solution.
Learning moves back into the work context. Whereas instruction separates learning from performing, EPSS brings learning back to the daily work setting. This is preferable in many ways, because on the job, the need for learning or information is more immediate, and the benefits more tangible.
End users enjoy more control over access and use of the product.
Even though performance supports are externally developed, workers
have increased control over their use. Some workers may make extensive
use of an EPSS system, others may not. Some may prefer one resource
over another. By their improved integration into the work environment,
performance-support tools become more easily adapted by people
doing their jobs.
Many training specialists are ready to stop right here. However, a whole new array of learning technologies are becoming available that differ markedly from traditional instruction, and even from performance-support tools. I call these "network systems," but the paradigm is so new, and so rapidly changing, that an accepted label hasn't yet emerged. Network systems include a variety of tools, including:
Network technologies. Information networks such as the World-Wide Web form the basic infrastructure of network systems. At the local level, iintranets can be used to provide a common information base within a company or organization (Gonzalez, 1998).
Web browsers. Web browsers are the basic tool for accessing and viewing information resources on a web, whether global or local.
Search engines. Search engines are popular on the World-Wide Web, but are vastly underutilized in local work environments. A powerful search engine, coupled with an information archive, together become a virtual performance-support system.
Push, pull, and filtering technologies. Information is the currency of the new web environments, yet we suffer from primitive methods of information filtering and accessing. How do you get the right information? When do I know the information is accurate, timely, and directly relevant to my problem? Filtering and push/pull technologies are being developed to help us get the right information when we need it.
Knowledge-management systems. These systems are comprehensive attempts to get the tacit knowledge of an organization down into explicit, documented databases. Knowledge-management systems typically impose some structure onto information, yet a heavy structure is not really needed to benefit from network systems.
Email systems. Email is the starting point for person-to-person communication online. Tools are improving rapidly, but further enhancements are needed to the functionality and the human-machine interface, in order to make email a real benefit to daily work.
Threaded discussion and conferencing tools. Listservs, threaded discussions, and conferencing tools take email (or voicemail) and adapt it to purposes of group discussion.
Groupware and collaboration tools. Groupware tools facilitate more than discussions. They allow collaborative production and authoring of products and documents.
Multimedia presentation technologies, including audio, graphics, and video. Quality communication depends upon quality presentation of material. Multimedia tools can facilitate this, but much remains to be done before end users feel empowered in their authoring and presentations. Powerpoint is a case study in a presentation tool that has grown in power while maintaining an ease of use that invites novices and everyday use.
Theorists are working hard to keep up with this new generation of learning technologies. Right now theorists interested in this area are scattered across a number of disciplines, including:
--EPSS and human performance technology;
--computer-supported collaborative work (CSCW);
--computer-supported collaborative learning (CSCL);
--computer-mediated communication (CMC);
--human-computer interaction (HCI); and
--technical communications;
--instructional technology.
This list doesn't include the various fields that make use of these learning technologies, such as cognitive science, instructional design, business, organizational development, and so on.
How do network systems relate to previous paradigms? Here are some basic similarities and differences, drawing again on Figure 1.
Network systems are open to any expertise. The expertise needed within a network system may be drawn from outside or from among the workers themselves. Network systems are not fussy about where knowledge comes from-They are very acquisitive and opportunistic in their knowledge-getting. FAQs (lists of frequently asked questions), job aids, reference information, manuals, documentation, instructional modules, readings, customer interactions, email archives, expert systems, structured information bases-All of these are examples of how knowledge might be stored and accessed in a network environment.
Networks are always changing. There is no pre-packaged solution with a network system. They are never finished, always changing. They may appropriate and include packaged elements, but the whole is much greater than that. The whole system cannot be designed, but rather nurtured and grown like a living organism. This dynamic quality contrasts sharply with designed solutions such as instruction or EPSS systems. Dynamic networks can be messy, redundant, poorly organized, and idiosyncratic. On the other hand, their amorphous nature allows greater adaptability and responsiveness to problems that inevitably arise.
Practitioners serve as co-designers. Networks depend on community members for their content and much of their structure. Workers themselves become sources of expertise and knowledge about solving problems. The success of the network depends in large measure on a sense of ownership that practitioners feel toward the system. If a network knowledge system is seen as an instrument of control by management, it can never achieve its potential. Only when workers routinely use and contribute to the system can a network system mature. People need to get in the habit, as they address a work problem, of leaving a record of how they solve it. Useful knowledge artifacts can be stored electronically and accessed when a similar problem arises in the future.
Training departments must feel an ambivalence with respect to networking technologies. On the one hand, they support learning and performance, so that's good, right? On the other hand, training departments lose their monopolistic control over learning and performance support. If learning is happening in large measure independent of the training department, where does that leave us as training specialists?
Of course, training specialists must re-evaluate their core function and determine whether their role is to support learning and performance, or merely to provide training and performance aids. The broader mission will keep them busy if they can adapt to the new environment.
Another way to look at these paradigms is to see each successive
paradigm subsuming and including the previous one. Instruction
is a legitimate type of learning support; the broader view of
performance support systems can accommodate training or instruction
as a component. Similarly, network systems can be vehicles for
the delivery of training or the accessing of performance-support
tools. But with each new paradigm, additional choices emerge for
supporting learning, superseding the previous approach.
In this paper we have discussed three evolving paradigms for supporting learning and work performance: instructional design, performance support, and network systems. Each approach has a legitimacy and a proper place; however, new technologies have recently allowed greater flexibility in supporting learning and performance on the job. Networking technologies help to make work environments open systems, where the sharing and accessing of expertise and knowledge is commonplace. This opening up of knowledge access has a direct political effect: Workers and workgroups become empowered to take more responsibility for their own learning and performance. They need not always wait until a training program is provided. As workers take more responsibility for their own learning, the organization is able to adapt more readily to changes in the competitive environment. To the extent that this happens, work organizations can indeed become learning organizations.
The need to adapt to change is already upon us. Organizations of all kinds are working to adopt networking tools to support knowledge use. Moving in this direction requires a major rethinking of roles and responsibilities, and a whole new set of procedural routines and habits. Ironically, the technologies themselves become both an obstacle and a facilitator for this kind of change. While resistance to technology is always a concern, once people see the power of new methods and models, a positive spiral can occur, leading to greater integration and more effective use of the tools.
Training managers can serve a critical role in providing initial
training and support for new technologies. Just as importantly,
they can help organizations come to see learning and support in
a new way that encourages workers to become co-designers and co-responsible
for their own learning and performance. This new role of learning
support specialist will not go away, and will become a core function
with the modern learning organization.
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