The ROI of Enterprise 2.0 / Social Anything is not how much did it cost to
deploy the technology; it’s what gains have we seen in productivity, employee
engagement and customer satisfaction as a result of new collaborative behaviours
that are aided and propelled by Enterprise 2.0 / Social Anything
technologies.
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To Really Drive Enterprise 2.0 Forward We Need A Behaviour Change - 3 views
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They forget adoption occurs only when people behave in a way that allows collaboration to manifest across an organization.
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The HR / Learning Professionals are having massive difficulty adjusting to a world with Enterprise 2.0 / Social Anything technologies, but they can’t get in front of it in time to actually establish the behaviours for an organization … even if they knew what behaviours to depict in the first place.
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The technologists are happy discussing Enterprise 2.0 / Social Anything features, gizmo’s and futuristic trends … but they forget about the behaviours that are needed to actually make the software more effective in the first place.
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Whether using new or traditional technologies, the key to digital transformation is re-envisioning and driving change in how the company operates. That’s a management and people challenge, not just a technology one.
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Dropping Enterprise 2.0 / Social Anything tools into the company theater is not going to guarantee your employees/leaders are collaborating and it’s certainly not going to drive reciprocity.
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it’s the behavior of people that has to change in parallel with the deployment of any Enterprise 2.0 / Social Anything technology.
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Is the Revolution Justified? : The Digital Scholar: How Technology Is Transforming Scho... - 9 views
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And Oblinger and Oblinger (2005) claim as one of the defining characteristics of the net generation that ‘they want parameters, rules, priorities, and procedures … they think of the world as scheduled and someone must have the agenda. As a result, they like to know what it will take to achieve a goal. Their preference is for structure rather than ambiguity’. This rather begs the question, ‘was there evidence that previous generations had a stated preference for ambiguity and chaos in their learning?’
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It is amazing to me how in all the hoopla and debate these days about the decline of education in the US we ignore the most fundamental of its causes. Our students have changed radically. Today's students are no longer the people our educational system was designed to teach. (Prensky 2001)
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I think this statement is anachronistic. In fact, the "new students" today who do not fit into the traditional educational system are in many cases people who were raised in the system, and then either rejected it or were rejected by it in some way. Our educational system is designed to train conformist drones, who do not know how to learn without school. There are many who are also able to live in both of these worlds, the traditional and the new, but I think they can bring new insights to the traditional school environment.
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I think this is a red herring as far as technology is concerned. it's much more to do with a pervasive social issue about inclusion and exclusion, probably worldwide, but much more marked in the UK due to the enthusiastic implementation of Thatcherism by her and subsequent governments. Many students know or suspect that there is no point for them in school and schools exclude like everyone else does those pupils who are likely to be expensive. Cost has truly overtaken value as the main point of reference
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That's interesting. I doubt that the older generation were inherently more moral. I suspect that they regarded plagiarism more seriously because it's easier to hold censorious views about a crime that's difficult to commit. When the crime becomes easy to commit fewer people stand out against it. There is also the issue that plagiarism falls into the category of wrong doing that doesn't obviously hurt anybody - like speeding or smoking cannabis.
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Brown (2009) reports, Recently, the Nielsen Norman Group study of teenagers using the web noted: ‘We measured a success rate of only 55 percent for the teenage users in this study, which is substantially lower than the 66 percent success rate we found for adult users’. The report added: ‘Teens’ poor performance is caused by three factors: insufficient reading skills, less sophisticated research strategies, and a dramatically lower patience level’.
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Summary: discussions about net gen are not significant. There is not evidence of significant difference between net gen and previous gens. Also there is evidence of significant variation within today's younger generation. Issue also lacks significance because we still need to cater for very large number of other gen learners.
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A new generation is behaving fundamentally differently – there seems little real evidence beyond the rhetoric that the net generation is in some way different from its predecessors as a result of having been exposed to digital technologies. There is some moderate evidence that they may have different attitudes. There is a general change in society which has relevance for learning – certainly the overall context is an ICT-rich one, and people are using the Internet for a variety of learning-related activities. People are learning in different ways – although firm evidence of informal learning is difficult to gather, there is much by the way of proxy activity that indicates this is the case. There is growing dissatisfaction with current practice in higher education – there seems little strong evidence for this. Probably more significant to the culture of education has been the shift to perceiving the student as a customer. There is certainly little evidence that the dissatisfaction is greater than it used to be, but what may be significant is that there are now viable alternatives for learners. Universities have lost their monopoly on learning, which reinforces the next point.
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Higher education will undergo similar change to that in other sectors – there are some similarities between higher education and other sectors, such as the newspaper and music industries, but the differences are probably more significant. However, the blurring of boundaries between sectors and the viability of self-directed, community-based learning means that the competition is now more complex.
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The first is that there is lag between society's acceptance of a technology and then its adoption in higher education. Brown (2009) suggests that in society the stages of technology diffusion can be defined as critical mass (ownership by 20–30 per cent of the population), ubiquity (30–70 per cent) and finally invisibility (more than 70 per cent). If higher education were to wait for the invisibility stage to be reached before it engaged with a technology, then given the time it takes to implement policies and technology, it really will look outdated. For example, in 2007, those using social networks might have been in the minority; now they will be in the majority. This is the problem with waiting for data to determine decisions – if you made a decision based on 2007 data that social networks were largely unused, it would look out of date in 2010. What is significant is the direction of travel, not the absolute percentages at any given time.
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I haven't read any of this book yet, but this quote is running along the lines of my own thinking for my own interaction with the web and all its tools and structures. I'm beginning to feel that many of the new tools used for organization, aggregation, and note taking are too regimented for what I want right now, too task-oriented. I'm figuring out how I learn best, and the most important part of that process that has been missing for me in the past is connection to creativity. Of course, the internet is a place where so much creation is going on and I can certainly find inspiration from it. But in terms of working out my projects using solely these new tools, I keep running against a wall. I'm not exactly sure if that's what Oblinger and Oblinger are talking about, but that's what I thought of.
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1.1. Connecting learning objects to instructional design theory: A definition, a metaph... - 9 views
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The purpose of this chapter is to introduce an instructional technology concept known commonly as the “learning object.” First a review of the literature is presented as groundwork for a working definition of the term “learning object.” A brief discussion of instructional design theory is followed by an attempt to connect the learning objects approach to existing instructional design theory, and the general lack of such connective efforts is contrasted with the financial and technical activity generated by the learning objects notion.
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An instructional technology called “learning objects” (LTSC, 2000a) currently leads other candidates for the position of technology of choice in the next generation of instructional design, development, and delivery, due to its potential for reusability, generativity, adaptability, and scalability (Hodgins, 2000; Urdan & Weggen, 2000; Gibbons, Nelson, & Richards, 2000).
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build small (relative to the size of an entire course) instructional components that can be reused a number of times in different learning contexts
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Moreover, those who incorporate learning objects can collaborate on and benefit immediately from new versions. These are significant differences between learning objects and other instructional media that have existed previously.
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Supporting the notion of small, reusable chunks of instructional media, Reigeluth and Nelson (1997) suggest that when teachers first gain access to instructional materials, they often break the materials down into their constituent parts.
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if instructors received instructional resources as individual components, this initial step of decomposition could be bypassed
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The Learning Technology Standards Committee chose the term “learning objects” (possibly from Wayne Hodgins’ 1994 use of the term in the title of the CedMA working group called “Learning Architectures, API’s, and Learning Objects”)
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Learning Objects are defined here as any entity, digital or non-digital, which can be used, re-used or referenced during technology supported learning. Examples of technology-supported learning include computer-based training systems, interactive learning environments, intelligent computer-aided instruction systems, distance learning systems, and collaborative learning environments. Examples of Learning Objects include multimedia content, instructional content, learning objectives, instructional software and software tools, and persons, organizations, or events referenced during technology supported learning (LOM, 2000).
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The proliferation of definitions for the term “learning object” makes communication confusing and difficult.
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It would seem that there are almost as many definitions of the term as there are people employing it.
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In addition to the various definitions of the term “learning object,” other terms that imply the general intention to take an object-oriented approach to computer-assisted instruction confuse the issue further.
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Depressingly, while each of these is something different, they all conform to the Learning Technology Standards Committee’s “learning object” definition. An in depth discussion of the precise meanings of each of these terms would not add to the main point of this discussion: the field is still struggling to come to grips with the question, “What is a learning object?”
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At the same time, the creation of yet another term only seems to add to the confusion. While the creation of a satisfactory definition of the term learning object will probably consume the better part of the author’s career, a working definition must be presented before the discussion can proceed.
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Therefore, this chapter will define a learning object as “any digital resource that can be reused to support learning.”
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This definition includes anything that can be delivered across the network on demand, be it large or small.
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This definition of learning object, “any digital resource that can be reused to support learning,” is proposed for two reasons.
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First, the definition is sufficiently narrow to define a reasonably homogeneous set of things: reusable digital resources. At the same time, the definition is broad enough to include the estimated 15 terabytes of information available on the publicly accessible Internet (Internet Newsroom, 1999).
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Second, the proposed definition is based on the LTSC definition (and defines a proper subset of learning objects as defined by the LTSC), making issues of compatibility of learning object as defined within this chapter and learning object as defined by the LTSC explicit
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With that compatibility made explicit, the proposed definition differs from the LTSC definition in two important ways.
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The definition also drops the phrase "technology supported" which is now implicit, because all learning objects are digital.
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Second, the phrase "to support" has been substituted in place of "during" in the LTSC definition. Use of an object "during" learning doesn't connect its use to learning
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The definition adopted for this chapter emphasizes the purposeful use (by either an instructional designer, an instructor, or a student) of these objects to support learning
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Armed with a working definition of the term learning object, the discussion of the instructional use of learning objects can proceed.
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[I]nstructional design theories are design oriented, they describe methods of instruction and the situations in which those methods should be used, the methods can be broken into simpler component methods, and the methods are probabilistic. (p. 7).s11 {margin-left:0; line-height:2.400000; text-indent:36;}
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Because the very definition of “theory” in some fields is “descriptive,” design theories are commonly confused with other types of theories that they are not, including learning theory and curriculum theory (Reigeluth, 1999a).
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The following discussion takes a step in this direction, by recasting two of the largest issues in the learning objects area – combination and granularity – in instructional design terms
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there is astonishingly little conversation around the instructional design implications of learning objects.
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To enable computer agents to automatically and dynamically compose personalized lessons for an individual learner
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at this point a brief discussion of metadata, the focus of the Learning Object Metadata Working Group’s efforts, is necessary.
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he Learning Objects Metadata Working Group is working to create metadata for learning objects (such as Title, Author, Version, Format, etc.) so that people and computers will be able to find objects by searching
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The problem with 7(d) arose when people began to actually consider what it meant for a computer to “automatically and dynamically compose personalized lessons.”
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his meant taking individual learning objects and combining them in a way that made instructional sense, or in instructional design terminology, “sequencing” the learning objects.
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The problem was that no instructional design information was included in the metadata specified by the current version of the Learning Objects Metadata Working Group standard.
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The lack of instructional design discussion at this standards-setting level of conversation about learning objects is disturbing, because it might indicate a trend.
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Once technology or software that does not support an instructionally-grounded approach to learning object sequencing is completed and shipped to the average teacher, why would he or she respond any differently
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Discussion of the problem of combining learning objects in terms of “sequencing” leads to another connection between learning objects and instructional design theory.
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The most difficult problem facing the designers of learning objects is that of “granularity” (Wiley, et al., 1999).
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Reuse is the core of the learning object notion, as generativity, adaptivity, and other –ivities are all facilitated by the property of reuse.
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designating every individual graphic and paragraph of text within a curriculum a “learning object” can be prohibitively expensive
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Stanford's open courses raise questions about true value of elite education | Inside Hi... - 4 views
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Search form | Follow us: Get Daily E-mail Thursday, December 15, 2011 Home NewsAssessment and Accountability Health Professions Retirement Issues Students and Violence Surveys Technology Adjuncts Admissions Books and Publishing Community Colleges Diversity For-Profit Higher Ed International Religious Colleges Student Aid and Loans Teaching and Learning ViewsIntellectual Affairs The Devil's Workshop Technology Blog UAlma Mater College Ready Writing menu-3276 menu-path-taxonomy-term-835 od
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This made Stanford the latest of a handful of elite American universities to pull back the curtain on their vaunted courses, joining the Massachusetts Institute of Technology’s OpenCourseWare project, Yale University’s Open Yale Courses and the University of California at Berkeley’s Webcast.Berkeley, among others. The difference with the Stanford experiment is that students are not only able to view the course materials and tune into recorded lectures for CS221: Introduction to Artificial Intelligence; they are also invited to take in-class quizzes, submit homework assignments, and gather for virtual office hours with the course’s two rock star instructors — Peter Norvig, a research executive at Google who used to build robots for NASA, and Sebastian Thrun, a professor of computer science at Stanford who also works for Google, designing cars that drive themselves. (M.I.T., Yale and Berkeley simply make the course materials freely available, without offering the opportunity to interact with the professors or submit assignments to be graded.)
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Based on the success of Norvig and Thrun’s experiment, the university’s computer science department is planning to broadcast eight additional courses for free in the spring, most focusing on high-level concepts that require participants already to have a pretty good command of math and science.
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For one, the professors can only evaluate non-enrolled students via assessments that can be graded automatically.
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With a player like Stanford doing something like this, they’re bringing attention to the possibilities of the Web for expanding open education