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Figure 6. 3. Specific learning elements.







Studying Learner Self

• Books, articles, guides

• References

• White papers

• Asynchronous content

• job aids

• Glossaries

• FAQs

Content Delivery_______________________

Focus

• Classroom lectures

• Synchronous content

• Demonstrations

• Reviews/discussions

• Video

• Videoconferencing


-Navigation Practicing

• Authentic tasks

• Role play

• Projects

• Case studies

• Peer discussion

• Discussion forums

____________________ Experience and

Practice Focus

• Exercises

• Diagnostic labs

• Practice labs

• Mentoring/tutoring

• Experiments


 


Teaching Guided N


ion Coaching


The Handbook of Blended Learning

a problem-solving skill. The design criteria for creating this best practice unit of study are:

• It is a collaborative group activity.

• The activity uses an authentic problem scenario.

• The activity is mentored by an expert.

• Correct performance is demonstrated by an expert.

• Learners will work in self-managed project teams.

• The activity will be supported with:

Reference manuals

Procedure guides

Asynchronous Web-based instructional content

In this example, the instructional strategy uses elements aggregated from all quadrants of the learning ecology to form a unit of study to address the specific instructional strategy.

A partial list of our current learning elements is shown in Table 6.1. The variety of these elements provides a rich palette for developing units of learning. Applying the model is a relatively straightforward activity of deciding overall strate­gies and then aggregating elements.

We have found that coupling a blend of online modalities with traditional classroom treatment has allowed more efficient use of classroom time (through prework) as well as extending the overall learning time (through postclass

TABLE 6.1. LEARNING ELEMENTS.

• Classroom (instructional) content

• Self-paced Web content

• Self-study guides

• Certification

• Practice tests

• Remote labs

• E-mentoring

• Asynchronous discussion forums

• Documentation

• Procedural job aids

• Guided lab activities

• Learning management system

• Transfer of information (recorded audio and slide presentations)

• Webcasts

• Video

• Performance support


A Learning Ecology Model for Blended Learning from Sun Microsystems



e-mentoring and online discussion). We have also found that individual instructors and students come to use the palette of learning elements in individualized ways that we had not anticipated. For example, nonnative English speakers sometimes pre­fer English content, which they then translate themselves. Clearly this can be time-consuming. In some cases, they use online English content to supplement their native language classroom because it affords the additional time to translate.

It is noteworthy that much of our application of the learning ecology model has a feel of experimentation. This is not unexpected given that new technologies, designs, business pressures, and possibilities keep shifting the field. At the outset, we decided not to attempt to create a model for the learning design but rather a framework where emerging models could grow and experimentation could thrive.

In this sense of evolution, we find an emerging modality particularly inter­esting: remote laboratories. Here the initial problem is quite simple. As the cost of equipment for high-end IT courses increases (into the millions of dollars), it becomes impractical to locate training equipment in each training center. Consequently like most other IT trainers, we have concentrated costly equipment in a few locations, which are then remotely accessed by learners. Lab activities have always been an important part of practical, hands-on IT training classes. Now, however, the lab equipment may be in another state or country. Originally this was simply a practical exercise in cost management as a way to fill class­room needs. Given our learning ecology, the next logical step is to move " remote labs" beyond the classroom as " online labs." From this perspective, the guid­ance, monitoring, feedback, and support for the student's lab experience are provided by an online instructor rather than a classroom instructor. The learning ecology focuses on the learning outcomes (within technical limitations), not whether the experience is classroom or online.

Another interesting, and unexpected, business possibility has begun to emerge from the learning ecology model: personalization of the online experience. From a technical point of view, automated personalization of an online experience (be­yond simple display variations) can be very complex and is always costly. Such per­sonalization systems require not only many different potential components, but also (at least) rich, dynamically updated user data; interaction and data capture between systems distributed across many electronic domains; meta data appended to all the " objects" in each of the potential elements; and secure identity man­agement. These types of requirements drive system costs in significant ways. Consequently, the decision to support automated personalization is always a difficult trade-off between demonstrable improvement in effectiveness and cost. The learning ecology model has reminded us that individual learners play a very important role in personalizing their own experience. They make choices. This invites exploring learner choice-based personalization modes that may be



The Handbook of Blended Learning


effective and yet of lesser cost and system complexity. Perhaps developing feed­back modes, improved navigation cues, and other " meta modalities" for the eco­logical mix provides an avenue for important developments. Along this line, we find the potential role of learning management systems (LMS) intriguing.

Regardless of what other advantages LMS may or may not offer, we believe that they are critical in the evolution of the learning ecology. Specifically, an LMS is conceivably where the whole learning ecology can be made explicit. By moving away from the notion of courses and toward a notion of learning paths and re­sources, the individual (and his or her manager or training administrator or men­tor) can examine the total range of possibilities and discuss the totality of a person's learning needs. The LMS can also anchor the conversation in a discussion of assessment and effectiveness at various levels. At the highest level, the conversa­tion can be about the individual's career and life learning requirements, whereas at more component level, there is a need to engage a specific component of the total learning ecology. This allows the individual to make informed and person­ally advantageous choices.

LMS implementations are still quite immature in most cases. They are only now emerging from the implementation phase and entering the mainstream of culture. As the ecology expands and LMSs become more embedded in the culture of cor­porations, we anticipate a virtuous cycle of self-directed learner engagement.

From Learning Ecology to Knowledge Ecology

The managed e-learning environment combined with a common learning ecol­ogy has the potential to bring together communities of geographically dislocated employees in an enterprise to work toward common performance goals. By pro­viding enterprise work groups open access to information, collaborative or problem-based learning activities, and discussion and chat tools, there is increased opportunity for the groups to use their learning experiences to formulate best practice processes and procedures that improve their overall organizational performance. As these best practice methods are developed, they can be added to the learning ecology, thus ex­tending the knowledge base of the ecology and the enterprise.

Our conception of the learning ecology originally focused on the question of engaging new networked-enabled technology in the world of workplace learning for Sun Microsystems. Over the past year, our worldview has expanded to address knowledge management issues. Like many others in industry, we are seeing the convergence of learning, libraries, and knowledge management efforts, all increasingly enabled by digitization, technical compatibility, and a vision for content and data interoperability. In our case, this trend has been punctuated by


A Learning Ecology Model for Blended Learning from Sun Microsystems



our organizational and business changes. We have merged our education and training business with our knowledge management initiatives. Thus, we are expanding the learning ecology into a knowledge ecology.

One important area of focus is internal employee support, providing critical up-to-date access to new product information, software and hardware updates, performance-support procedures and diagnostics, localized content, and rule-based content and systems. An even more important area is a focus on the needs of our external customers, providing role-based and role-driven content, sup­porting content for new products and technologies, solutions-oriented content, software and hardware updates, and performance-support tools for solutions.

We have discovered that by modifying our original learning ecology frame­work, we can conceptualize the creation and delivery of diverse knowledge or learning options that support knowledge services. The resulting knowledge ecosys­tem creates an environment in which people are provided opportunities to gain knowledge or learning through methods and models that best support their needs, interests, personal situations, and individual learning styles.

Returning to our learning ecology matrix, we have modified the ë: -axis to reflect the ways a person accesses content (Figure 6.4). The left end of the x-axis focuses on a

FIGURE 6.4. KNOWLEDGE ECOLOGY MATRIX.


 


 


 


 


" -'-": • ": ¹•'■

The Handbook of Blended Learning

person locating explicit knowledge resources by using methods designed for " collecting content." Knowledge resources are explicit, codified content such as facts, concepts, principles, procedures, or processes. These resources are domain neutral; they are gen­eralized, serve a broad audience, and are applicable in a variety of situations because they are valid regardless of the context in which they are applied.

The right end of the x-axis focuses on people who are sharing tacit knowl­edge resources while participating in activities designed for exposing distributed, collective intelligence by means of connecting people. Tacit knowledge resources are exposed through dialogue, social interactions, and collaboration as people interact within a realistic, situated environment. These exposed resources are unique to specific situations or problem domains, serve a specific community of practice, and apply only to the dynamic context in which the problem occurs.

By modifying the x-axis, we can reconceptualize the quadrants of the matrix to arrive at four general families of knowledge modalities for a knowledge ecol­ogy: exploring, informing, guiding, and participating (Figure 6.5). People explore resources for ideas and practical insights in a neutral environment. Experts inform people in common theories and practice in a neutral environment. In addition, experts guide people as they apply both knowledge and skills to new situations in a realistic environment. People participate in a community to create understanding

FIGURE 6.5. GENERAL KNOWLEDGE MODALITIES.



A Learning Ecology Model for Blended Learning from Sun Microsystems 89


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