We pass through life only once. Few tragedies
are more extensive than the stunting of life . . . by a limit
imposed from without, but falsely identified as
—Steven J. Gould, “The Mismeasure of Man” (1981)
One of the key problems addressed and solved by e-learning is instructor variability. Avoiding the extremes of creativity and ordinariness, e-learning instructional designers have opted for the solid middle road of competence. In the process of channeling to a central performance core, the designers also have built in a range of best practices that typically would exceed those of even the most extraordinary instructor. It is thus not surprising that when such smart and resourceful strategies are joined to cost controls, technology advances and ROI, e-learning has become the favored training mode.
But what is the next stage? Will the evolution be primarily or exclusively technological? Will dazzling gadgetry dominate and obscure the need for content and instructional design similarly to develop parallel forms of growth? Perhaps it is time reassess the basic assumptions of e-learning design. Traditionally, that involved three components: content, format and delivery. With the commitment to cost controls, overarching evaluation was added, bridging instruction and implementation, in many cases embedded in course design to ensure follow-up. But although the harmonizing of these four components has significantly upgraded training, is it the state of the art? Is it the best that can be offered given the unrelenting pressure for productivity and innovation?
Perhaps the best way to begin that process of review is to acknowledge from the outset a number of fundamental limitations, not external but built into the very format of current e-learning and that if identified and addressed can prepare the way for a second generation of development.
Five limitations of current e-learning training are identifiable:
- Course expectations narrowly focus on how, not why; on knowledge, not understanding.
- The range of applications provided is predictably reassuring, but fails to encourage wider and more creative adaptability.
- Learning capacity is assumed to be fixed or limited, but in either case is not engaged as an active cooperative learning partner.
- The range of audience intelligence is untested and hence untapped.
- The training focuses solely on measuring institutional and incremental gains, not the monitoring and tracking of continuous improvement.
To bring e-learning to a new plateau and to overcome the limitations noted above requires two changes, one external, the other internal, each reinforcing the other. The external involves employee testing, but of a different kind. The internal requires not only tapping such employee diagnostics, but also refocusing the training to address understanding and optimum adaptability.
Current e-learning design avoids the limits of a singular instructor by offering a broad-based composite. In effect, the course, or more exactly its format, becomes the instructor. Even with interactive formats using an electronically sustained teacher-trainer-coach, the kinds and levels of interaction are usually prescribed by the course script. Although open-ended prompts may stir a greater range of response, the intelligence capacity of learners has not been factored in. So the first corrective is to help the instructional designers be smarter about their audiences’ contributions to the learning process—to perceive them not solely as objects but as subjects of instruction. And that involves a different kind of employee testing.
Two kinds of metrics are needed to sustain a new level of e-learning: relationship styles and learning styles. The first can best be accomplished by the administration of some version of a personality profile, such as Myers-Briggs (especially the new team version); the second by a multiple-intelligences test.
Character profiles define not only interpersonal but also learning relationships within and across quadrants and divisions. They also determine hierarchical preferences for either directive or non-directive management and instruction. In short, who we are and how we relate is also how we learn.
Multiple intelligences (MI) refers to the distribution into eight learning dimensions as defined by its originator Howard Gardner. It is seldom used for e-learning diagnostics or applied to business training. Minimally, MI uniquely offers five distinctions:
- Intelligence is not singular but multiple; we are cognitively richer than our IQ.
- Everyone is multi-talented.
- MI preferential range is determined by genetics, environment and cultural goals.
- Dominant and strong intelligences can be used to improve less employed and weaker intelligences.
- Cognitive multiplicity is brain-wired.
Testing and then fusing relationship and leaning styles generates with rare precision the range and variety of both individuals and groups. Such learning thresholds and benchmarks become the new and expanded database and targets for training design. Performance expectations are not only raised, but also targeted. The metrics specify the attainable higher performance levels. The goal is more precisely bigger. In addition, the expanded focus on the psychological and intellectual contributions of participants also can sustain an individualized and long-term evaluation process. Monitoring and tracking continuous growth can provide a significant supplement to course evaluation. But for such metrics to yield the greater gains of productivity and creativity, they have to be optimized. That in turn requires developing new conceptual frameworks and designs.
The framework requires a fundamental change of focus from “How smart are you?” to “How are you smart?” This involves a double shift: from the singular IQ to the multiple MI; and from what is fixed and known to what is evolving and discoverable. In other words, human learning potential comes back into the equation but is now quantified. Diagnostics joined to the unique and generic ways people are smart grants two growth gifts: Employees now know more, and training can now ask for more. The knowledge gained is extended and extending. Employees can better understand their interpersonal dynamics on the one hand and their multiple talents on the other hand. Their self-knowledge is greater and more available. Above all, they are in a state of informed self-actualizing readiness and thus are poised for greater performance expectations.
But the shift in framework also requires a change in learning goals: from knowledge to understanding and from predictable implementations to optimum adaptability. Diagnostics helps facilitate both. The level and reach of training no longer addresses the lowest but the highest common denominators, individual and group. The learning and performance expectations of attendees is thus immediately but realistically more expansive. Parameters are stretched and thus can better address stretch goals. It expresses confidence that incremental success is within the range of their ability. Most important, the ultimate learning goal is not just knowledge but understanding.
Additional knowledge is always desirable, but it does not offer or lead to innovation and optimum adaptability. Knowledge and creativity are not paired—understanding is. In fact, the sign of deep understanding is innovation. The value of the symbiotic relationship between understanding and creativity is that it positions employees for questioning current operations as the optimum way of doing things. So if real change is desired—the how—the goal has to be understanding—the why.
The other limitation of knowledge is application. Training routinely includes a range of illustrative applications. But typically the examples are scripted to be of a piece with the training and institutional goals. They are what the company wants to see happen, now and precisely. The sample applications are prescriptive and limited. They are shaped by knowledge as a limiting factor. Indeed, when evaluation is properly done and is generally free of the limited workshop parameters, what emerges is that the implementation of the training is limited to the original problem sets. Application is so confined that employees emerge programmed for limited but predictable success. Not only is innovation jeopardized, so is optimum adaptability. Thus, training is always less and reaches for less than what it can be, just as it shortchanges its participants and their performance potential.
Incremental training yields just that—a prescribed series of baby steps. What usually determines such parameters is the assumption that employees and workshops can only be effective if they narrowly focus on limited competency acquisition. If and when further progress is needed, then another incremental session is scheduled. But control is still vested exclusively in the trainer and the training—it is not shared. Everything comes from one side—they call the shots. Even encouraging extensive participation, role-playing and simulations is driven by already-defined workshop goals.
Knowledge is thus paradoxical. It expands but limits; it opens doors but only to a pre-selected room. It gives but does not ask for a different and unpredictable giving in return. Turning knowledge over to understanding begets a different process. It welcomes with thanks the incremental knowledge extension but now seeks to go deeper, to go inside the knowledge to see what makes it tick, to speculate on what is behind it all. To be sure, limits will be encountered. Indeed, they may predictably be determined by individual metrics. But the limits will be deeper. In addition, more of what makes each one smart will be engaged and stirred perhaps to be smarter; more and less predictable applications may surface. Occasionally innovation will emerge and surprise even the innovator.
When e-learning dynamics involves two-way sharing, knowledge crosses over and partners with understanding. Linking the known and expanded ways employees relate and are smart to goals of understanding and optimum adaptability can create the threshold for a new generation of e-learning. It potentially would also have a profound and lasting impact on the way employees engage and relate to each other and to each other’s smarts. In fact, that interpersonal process as well as work redesign constitutes in fact the new requirements for horizontal implementation and application. In effect, the development would be carried forward with each employee charged with sustaining multiple and hopefully optimum relationships with both human and work design. Tracking the effectiveness of workshops now can be supplemented by a system of monitoring the continuous improvement of individuals, teams and divisions. Finally and hopefully, the emergence of this now-optimized e-learning and new data tracking systems would enjoy vertical alignment. It might persuade organizations to review their mission to define how they and their employees are smart, individually, collectively and collaboratively.
Irving Buchen is vice president of academic affairs at Aspen University. He can be reached at firstname.lastname@example.org.Filed under: Measurement, Technology