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Guidelines for Designing Closings

Online classes in the context of pedagogical effectiveness

WIRELESS and DISTANCE LEARNING

Advantages of Informal Learning

Simulation Strategies in Online Education

Strategies for Mentoring and Coaching

Advantages of Blended Learning

The Design of e Learning

What Are Coaching and Mentoring

Guiding Principles of Informal Learning

Simulation in online education

Guidelines for Design for Online Coaching and Mentoring

The Benefits and Limitations of Mentoring and Coaching

What Is Informal Learning and Why Is It a Useful Approach to Online Curricula

Addressing this complexity requires an equally complex approach to design. In fact, the more complexity that designers encounter, the larger and more varied the number of solutions they bring to a situation. This body of solutions is called a portfolio of techniques and represents a “bag of tricks” that instructional designers can call on when faced with an e-learning problem.

The Solutions to Effective Teaching Online

Unfortunately, that’s not the message that the industry press offers us. In an economy and industry that emphasizes “next big thing,” “experts” offer easy and allencompassing solutions to complex problems of learning and instructional design. These solutions have served as one of the biggest impediments to instructional designers developing a rich portfolio for designing e-learning. Before we can explore the development of such a portfolio, we have to consider the easy and all-encompassing design solutions for e-learning that have been offered and why they are neither easy nor all-encompassing.

For starters, consider these claims:

• e-learning is more effective than classroom learning.

• Games are the only way to teach online because the today’s youngsters seem to be excited by games (Prensky, 2002).

• Simulations are the best way to teach online and all learning should be interactive and engaging (Aldrich, 2003).

• Enterprise learning is the answer because it’s much cheaper and more efficient to manage all learning from a central source (Gold, 2003).

• e-Learning must be personalized because different people have different learning styles and computers can tailor the learning experience to individual needs.

• Learning comes in mix-and-match pieces that can be recombined at the moment of need to create a course that addresses a learner’s unique content needs (Longmire, 2004).

• Finally, some people believe that we just haven’t measured enough to prove that e-learning is effective.

The Problems with the Solutions

But think about this practically. Are the strategies that make a great algebra class the same ones that make a great physical education class? Civics? Cooking? Private investigator licensing? These subjects share nothing in common, so why should they be forced to share a pedagogy in common? Perhaps, then, e-learning is not a noun to describe the learning experience, but an adjective that merely identifies the medium of instruction. The nouns are “mathematics,” “manufacturing training,” “new hire orientation,” and “rocks for jocks” (that is, geology for nonscientists). The courses each have unique material, unique sets of learners, unique development and implementation budgets, and unique development schedules and are offered by different types of learning institutions— some offering courses for academic credit, some offering them to maintain an existing job, some just for fun.

For designers to take their e-learning to the next level, they have to move past these “I’ve got the universal solution” approaches because they simply aren’t universal. Consider the responses to each of the universal solutions presented in the previous section:

• The effectiveness of e-learning compared to the classroom: The research suggests that e-learning is merely as effective as classroom-based learning— no more, no less. These comparison studies also assume that the material in both formats has been professionally designed (Russell, ongoing).

• The limitations of game-based learning: Although youngsters do enjoy their computer games, most of them recognize that learning and computer games are not the same activity and have different expectations for the two.

• The limitations of simulation learning: Simulations are useful for teaching many types of content (Sugrue, 2004), but not all content. For example, one need not simulate the experience of swimming. It can be taught by letting learners actually swim (an off-line experience).

• The limitations of enterprise learning: Although enterprise-wide learning is a great strategy, there are few courses that both the receptionist and the CEO need to be enrolled in. Furthermore, because many organizations like to empower their operating units, resulting differences in operations may result in differences in training that render enterprise training inappropriate.

• The limitations of learning styles: Although learning styles are a popular theory, few studies show that learning styles really contribute to actual learning achievement (Sugrue, 2004). So addressing them in the design of courses is a time-consuming effort that pays few dividends. Even if learning styles were proven to be effective, the difference between effectively presenting content for verbal and visual learning styles involves more than presenting visuals first or second, which is the dominant approach to such design. Rather, developing courses to reach different styles requires that the courses be re-developed completely for each learning style. A course for visual learners would rely almost exclusively on pictures and other visuals, while a course for verbal learners would rely almost exclusively on text.

• The limitations of reusable learning content: Although some learning materials can indeed be reused, the use of reusable learning content—called reusable learning objects—in most corporate environments—especially those in organizations with fewer than 50,000 workers—has not worked. As one director of a major consulting firm that decided to implement learning objects admitted, “It was a disaster.” Even in private, most learning objects experts admit that much of the concept does not yet work in practice, saying that efforts to design learning objects focus more on standards for using them with particular types of software than the instructors who will actually need to use them.

• The need for more measurement: Although some people claim that e-learning produces a high return on investment, empirical studies conclude that e-learning has failed to generate the productivity gains it has promised. In fact, one of the fundamental justifications for computerizing learning has been the promise of increased productivity of educators. Computers have led to such productivity gains in other fields. For example, by letting customers order products online, companies have achieved significant reductions in inventory costs and improvements in delivery times. e-Learning has not delivered such benefits. For example, some proprietary studies say that the only savings that have been realized from e-learning have been travelrelated. In addition, many instructors who teach online courses find that they take more work than their classroom equivalents (National Education Association, 2000).

In other words, rather than looking for a single silver bullet to effective e-learning, instructional designers might look inward—at the specific performance problem or content to be presented—for suggestions on ways to effectively teach online.

The Right Way?

When looking at these specific design challenges, another approach that’s prevalent within the world of instructional design is to look for the “right way” to do things. The “right way” often refers to research-based solutions to challenges. When addressing problems like these, designers consider what might be more effective: teaching a lower-level psychomotor skill with visuals alone or teaching one with visuals and sound.

The answers make a number of assumptions:

• That indeed a researcher has conducted research on this specific problem. Despite the claims of many authors and speakers (for instance, Wallace [2004] claims that training and the related field of human performance technology are “research-based disciplines”), in many instances, there is no research.

• In those situations for which research has been performed, the research also needs to be relevant to the case at hand. In some cases, the research was performed with a group of learners who share nothing in common with yours. For example, most of the science of multimedia is based on research with U.S.-based college students. Most of these students are in their late teens and early twenties and have not held full-time professional employment (Clark & Mayer, 2002). Most trainers work in environments that employ people who are considerably older and who have held professional employment for an extended period of time. Both the physical capabilities and learning strategies employed by the research group and the group of actual learners substantially differ. In the research groups mentioned earlier, most of the participants speak and write English as their first language, but much training goes to people who use English as a second or third language. A substantial body of research suggests that second-language learners have different strategies than first-language learners.

• In addition to differences among learners, many of these studies controlled the learning situation so extensively that the content under study substantially differs in reality from the problem about which the designer has an interest. For example, some studies suggest that off-topic learning games distract interest. But the studies only looked at brief learning segments (less than 4 minutes). In most actual learning programs, these activities often exceed 15 or 30 minutes. Therefore, the studies may not provide complete insights into the situation (Thalheimer, 2004).

• But perhaps the most significant omission of this “scientific” research is that hardly any of it states the practical considerations facing the designers of the learning experiences. Most corporate instructional designers have limited budgets with which to develop their courses, but few studies state either the budgets or development schedules used to create the courses that were covered in the study. Most academic instructors have even less design and development time than their corporate counterparts. For example, university instructors are advised to allot just one hour of preparation for each hour of classroom instruction. Admittedly, this metric assumes that the instructor is already conversant in the subject matter. Instructors are supposed to spend their time, instead, on their academic research. So although a learning strategy suggested by the research might seem appropriate to a given situation, the designer might not have the actual resources to implement it and thus must choose a different alternative. In many instances, the alternative seems less than optimal at the time the decision was made but, in the end, may prove just as effective educationally as the original strategy. Similarly, many instructional designers turn to e-learning not because it is the best choice for a given situation, but because it is a requirement of the assignment. So e-learning will be chosen regardless of its likely effectiveness. The instructional designer doesn’t choose the medium in an instance like this; the instructional designer chooses strategies that make the medium work to its best advantage.