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Two broad approaches exist for learning technology implementation: The adoption of a centralized learning management approach. This may include development of a central learning support lab where new courses are developed in a team-based approach—consisting of subject matter expert, graphic designers, instructional designer, and programmers. This model can be effective for creation of new courses and programs receiving large sources of funding. Most likely, however, enterprise-wide adoption (standardizing on a single LMS) requires individual departments and faculty members to move courses online by themselves. Support may be provided for learning how to use the LMS, but moving content online is largely the responsibility of faculty. This model works well for environments where faculty have a high degree of autonomy, though it does cause varying levels of quality in online courses. Personal learning environments (PLEs) are a recent trend addressing the limitations of an LMS. Instead of a centralized model of design and deployment, individual departments select from a collage of tools—each intending to serve a particular function in the learning process. Instead of limited functionality, with highly centralized control and sequential delivery of learning, a PLE provides a more contextually appropriate toolset. The greater adaptability to differing learning approaches and environments afforded by PLEs is offset by the challenge of reduced structure in management and implementation of learning. This can present a significant challenge when organizations value traditional lecture learning models.

Self-organised learning networks provide a base for the establishment of a form of education that goes beyond course and curriculum centric models, and envisions a learner-centred and learner controlled model of lifelong learning. In such learning contexts learners have the same possibilities to act that teachers and other staff members have in regular, less learner-centred educational approaches. In addition these networks are designed to operate without increasing the workload for learners or staff members.

Instead of learning housed in content management systems, learning is embedded in rich networks and conversational spaces. The onus, again, falls on the university to define its views of learning.

Active and Reflective Processing. Active learners tend to learn while doing something active---trying things out, bouncing ideas off others; reflective learners do much more of their processing introspectively, thinking things through before trying them out [12]. Active learners work well in groups; reflective learners prefer to work alone or in pairs. Unfortunately, most lecture classes do very little for either group: the active learners never get to do anything and the reflective learners never have time to reflect. Instead, both groups are kept busy trying to keep up with a constant barrage of verbiage, or else they are lulled into inattention by their enforced passivity. The research is quite clear on the question of active and reflective versus passive learning. In a number of studies comparing instructor-centered classes (lecture/demonstration) with student-centered classes (problem-solving/discussion), lectures were found to be marginally more effective when students were tested on short-term recall of facts but active classroom environments were superior when the criteria involved comprehension, long-term recall, general problem-solving ability, scientific attitude, and subsequent interest in the subject [15]. Substantial benefits are also cited for teaching methods that provide opportunities for reflection, such as giving students time in class to write brief summaries and formulate written questions about the material just covered [15,20].

reflective learners do well at individual research and design.

Unfortunately---in part because teachers tend to favor their own learning styles, in part because they instinctively teach the way they were taught in most college classes---the teaching style in most lecture courses tilts heavily toward the small percentage of college students who are at once intuitive, verbal, deductive, reflective and sequential. This imbalance puts a sizeable fraction of the student population at a disadvantage. Laboratory courses, being inherently sensory, visual, and active, could in principle compensate for a portion of the imbalance; however, most labs involve primarily mechanical exercises that illustrate only a minor subset of the concepts presented in lecture and seldom provide significant insights or skill development. Sensing, visual, inductive, active, and global learners thus rarely get their educational needs met in science courses.

Strategies for Fostering Reflection Hatton and Smith (1995) reported four activites that in in the process of reflection: Action Research Projects Case and cultural studies Practical experiences Structured curriculum tasks: Reading fiction and non-fiction Oral interviews Writing tasks such as narratives, biographies, reflective essays, and keeping journals. However, although these strategies have the potential to encourage reflection, there is little research evidence to show that this is actually being achieved. Obviously "fact" questions do not promote reflection (e.g., What are the functional areas of an air base?). But posing hypothetical situations produced similarly disappointing results (e.g., Assume you have inherited a significant sum of money and wish to buy land in an environmentally sensitive area on which to build. What factors will go into your decision and why?). In contrast, the most successful probe asked learners to write a one page letter to a parent, sibling or other significant person in their lives.

Extending evaluative feedback might have even more powerful effects. Providing probes may cause the learner to continue to think about the topic, such as: "Have you thought about how a skilled operator might do this?" "But how much does safety really get compromised when you don't use safety shoes?" Pointing out other possibilities may also result in additional thinking about relationships among factors not previously considered, such as:  "Another factor you might consider is how many different tools will be required if you use different size bolts in the design?" "But what if the rate of water flow is doubled?" Although such feedback may be provided via written comments, they are probably most powerful when used interactively in interpersonal dialogue. Carrying on a dialogue with one or more learners about the work they have submitted is probably the ultimate in promoting reflection via feedback. But the logistics of doing so and having discussion leaders who are skilled in the content and possess good interpersonal skills may be beyond the capacity of the system to provide; unless it is computer mediated in some way. Other hints for encouraging reflection include: Seek alternatives. View from various perspectives. Seek the framework, theoretical basis, underlying rationale (of behaviors, methods, techniques, programs). Compare and contrast. Put into different/varied contexts. Ask "what if. . . ?" Consider consequences.

The concept of an e-portfolio is multifaceted — it is a technology, a pedagogical approach, and a process, as well as a product. Its purpose can range from tracking development within a program to finding a job or monitoring performance.

a culture of folio thinking, a pedagogical approach that focuses on designing structured opportunities for students to create e-portfolios and reflect on their learning experiences.

Instead of prioritizing e-portfolio technology, folio thinking addresses the adoption and integration of e-portfolio praxis in existing contexts as a critical first step toward a successful implementation that can lead to wider scalability and longer-term sustainability of the e-portfolio initiative.

A growing number of colleges and universities are requiring students to practice reflective writing or to keep a learning journal

There are numerous models of reflection that can help students get started. One such model is the Gibbs Cycle of Reflection which is an easy template for analyzing a learning experience. Choose one event that happened and ask the following questions:

Because the subjects were thinking about what they got wrong, they learned how to get it right.

The problem with praising kids for their innate intelligence — the “smart” compliment — is that it misrepresents the psychological reality of education. It encourages kids to avoid the most useful kind of learning activities, which is when we learn from our mistakes. Because unless we experience the unpleasant symptoms of being wrong — that surge of Pe activity a few hundred milliseconds after the error, directing our attention to the very thing we’d like to ignore — the mind will never revise its models. We’ll keep on making the same mistakes, forsaking self-improvement for the sake of self-confidence. Samuel Beckett had the right attitude: “Ever tried. Ever failed. No matter. Try Again. Fail again. Fail better.”

And the main thing to keep in mind is that if you are not teaching a writing course, there is no law that says you have to comment.

There's a quick and easy form of "proto-commenting" that is remarkably effective--especially appropriate perhaps for think pieces: putting straight lines alongside or underneath strong passages, wavy lines alongside or underneath problem passages, and X's next to things that seem plainly wrong. I can do this almost as fast as I can read, and it gives remarkably useful feedback to students: it conveys the presence and reactions of a reader.

Two-fers:

Writing in class gives students direct access to me as they think through their ideas.

Ask students to reflect on their writing habits and process.

Ask students to tell you about their regular or most significant interactions with technology

ongoing reflection on the writing students do, a process that will keep you informed about the writers you teach.

MOOCs reduce barriers to information access and to the dialogue that permits individuals (and society) to grow knowledge.

Knowledge is a mashup. Many people contribute. Many different forums are used. Multiple media permit varied and nuanced expressions of knowledge. And, because the information base (which is required for knowledge formation) changes so rapidly, being properly connected to the right people and information is vitally important.

MOOCs share the process of knowledge work – facilitators model and display sensemaking and wayfinding in their discipline. They respond to critics, to challenges from participants in the course. Instead of sharing only their knowledge (as is done in a university course) they share their sensemaking habits and their thinking processes with participants. Epistemology is augmented with ontology.