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tim mcnamara

1.1. Connecting learning objects to instructional design theory: A definition, a metaph... - 9 views

  • 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.
  • What is a learning object?
  • 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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  • grounded in the object-oriented paradigm of computer science.
  • build small (relative to the size of an entire course) instructional components that can be reused a number of times in different learning contexts
  • 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.
  • 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.
  • if instructors received instructional resources as individual components, this initial step of decomposition could be bypassed
  • 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”)
  • provided a working definition
  • 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).
  • The proliferation of definitions for the term “learning object” makes communication confusing and difficult.
  • It would seem that there are almost as many definitions of the term as there are people employing it.
  • 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.
  • 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?”
  • 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.
  • Therefore, this chapter will define a learning object as “any digital resource that can be reused to support learning.”
  • This definition includes anything that can be delivered across the network on demand, be it large or small.
  • This definition of learning object, “any digital resource that can be reused to support learning,” is proposed for two reasons.
  • 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).
  • 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
  • With that compatibility made explicit, the proposed definition differs from the LTSC definition in two important ways.
  • First, the definition explicitly rejects non-digital
  • The definition also drops the phrase "technology supported" which is now implicit, because all learning objects are digital.
  • 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
  • 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
  • Armed with a working definition of the term learning object, the discussion of the instructional use of learning objects can proceed.
  • Instructional design theory and learning objects
  • Reigeluth
  • [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;}
  • 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).
  • 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
  • Combination
  • there is astonishingly little conversation around the instructional design implications of learning objects.
  • item (d) in the Learning Objects Metadata Working Group’s PAR (LOM, 2000) reads as follows:
  • To enable computer agents to automatically and dynamically compose personalized lessons for an individual learner
  • at this point a brief discussion of metadata, the focus of the Learning Object Metadata Working Group’s efforts, is necessary.
  • Metadata, literally “data about data,” is descriptive information about a resource
  • 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
  • ​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.”
  • 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.
  • 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.
  • ​The lack of instructional design discussion at this standards-setting level of conversation about learning objects is disturbing, because it might indicate a trend.
  • 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
  • Wiley (1999) called this “the new CAI – ‘Clip Art Instruction’” (p. 6).
  • Discussion of the problem of combining learning objects in terms of “sequencing” leads to another connection between learning objects and instructional design theory.
  • Granularity
  • The most difficult problem facing the designers of learning objects is that of “granularity” (Wiley, et al., 1999).
  • How big should a learning object be?
  • Reuse is the core of the learning object notion, as generativity, adaptivity, and other –ivities are all facilitated by the property of reuse.
  • designating every individual graphic and paragraph of text within a curriculum a “learning object” can be prohibitively expensive
  •  
    Chapter 1
anonymous

Nuts and Bolts: The 10-Minute Instructional Design Degree by Jane Bozarth - 0 views

  • Good eLearning is about design, not software
  • When approaching a project, ask: “What is it you want people to do back on the job?” Then, “What does successful performance look like?” “How will you measure that?” Design that assessment first. Then design the instruction that leads to that goal.
  • instructional design and visual design are different things. Visual design is just as important (and it isn’t about making things “pretty”), and it needs to be done before the development phase begins.
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  • Revisit your assessment (remember that? You designed it before anything else). Will this information in any way affect successful performance? If not, can you add a link to the policy and an e-mail introduction with a disclaimer? Can you cut the verbiage (here’s a trick: what if you had to pay $5 per word? I bet you could cut it then.)? Or, if there’s really that much content, should you break it into pieces?
  • just because it’s online doesn’t mean you can control it. Build it with this in mind.
  • Zooming and spinning words, irrelevant animations, and neon “next” buttons do not heighten engagement. They confuse and distract learners
  • “You know, I don’t think that will solve the performance problem. Can we talk about some ways to get you a better solution?” Designing a solution that doesn’t solve the problem, or that makes it worse, doesn’t do anything to help the organization, the field, or your department’s reputation – or your own. “Instructional designer” is a job title. “Performance consultant” is a mindset. 
  • Instruction does not cause learning.
  •  
    Learning Solutions magazine
Lone Guldbrandt Tønnesen

Avoiding the Trap of Clicky-Clicky Bling-Bling - 1 views

  • "All that is clicky-clicky bling-bling does not make for an effective learning experience."
  • s a load of elearning junk
  • It's just shiny wrapping paper covering up a pair of crummy socks with holes in them.
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  • " Ruth Clark and Richard Mayer in the industry classic e-Learning and the Science of Instruction, explain that seductive details are "interesting but irrelevant material added to a multimedia presentation in an effort to spice it up
  • Seductive details are those elements in a program that draw you in, attract the eye and engage the brain. They seduce your interest, but distract from the main point.
  • It's interactive! It's intriguing! But it's exhausting, and let's face it"—there's no point. Fatigue sets in and you move on
  • This is the premise underlying the arousal theory, the idea that entertaining and interesting embedded effects cause learners to become more emotionally aroused and therefore they work harder to learn the material.
  • . Designers who don't understand the basics of effective instructional design are committing what Clark Quinn of Quinnovation calls "instructional design malpractice.
  • CCBB design shines and sparkles wildly in the sun
  • When we force learners to practice without context, they've memorized facts but may not be able to apply them correctly in context.
  • Too much clicking can lead to learner fatigue, is distracting to the learner, and doesn't promote deeper understanding
  • We need to provide more contextual opportunities for drill exercises that will help the learner both retain and apply the knowledge they are practicing.
  • "Well-written, multiple-choice questions teach and assess knowledge within the context of a game. Poor questions simply allow the gamer to play the game without learning.
  • that the addition of interesting yet unimportant augmentations can divert learners from learning the main points that are being made
  • . You're best served to spend your time designing the right type of course and spending less time looking for ways to 'jazz it up'"
  • . Now, take a look at the screen and see where your eye lands first. Is it the flashing Next button in the bottom right corner? Or is it the important content bit at the center of the screen? Ask an objective outsider to take a look, too
  • Pilot your program with some test learners
  • heck in with them immediately afterwards, one week, three weeks. See what they remembe
  • , don't take this to mean that elearning shouldn't look good.
  • What about your LMS? At Kineo, where I work, we love using Moodle and Totara as an LMS solution for our clients, not only because of the great features and the fact that it's open source, but always because we can make it look like almost anythin
Lone Guldbrandt Tønnesen

Learnlets » Quip: design - 0 views

  • The focus has to be on the learning experience design first, and then you can worry about how you might build the delivery environment
Lone Guldbrandt Tønnesen

Learnlets » Slow Learning - #change11 - 0 views

  • Our limitations are no longer the technology, but our imaginations
  • “work is learning and learning is work”,
  • how would you construct an optimal performance environment for yourself?
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  • We see that we learn by being engaged in meaningful activity, and working with others.
  • I like Collins, Brown, & Holum’s Cognitive Apprenticeship as a model for thinking more richly about learning.  Other learning models are not static
  • I’m really arguing for the need to come up with a broader perspective on learning
  • I’m looking to start matching our technology more closely to our brains
  • meaningfulness, activation and reactivation, not separate but wrapped around our lives
  • I think this framework will need to start with considering the experience design, what is the flow of information and activity that will help develop the learner
  • I don’t need or want an LMS and I often don’t need a ‘teacher’ in the traditional sense, though I welcome the wisdom of coaches and mentors.
  • In self regulated learning, evaluation is a metacognitive event
  • . Much of what my students discussed is similar to my ideal. Briefly, here are some elements, organized under the four categories of appreciative inquiry: 1) Discovery-the best of what we have previously experienced: sense of accomplishment, respect, sharing ideas, supportive atmosphere to enable taking risks. 2) Dream-best of what might be: have real life application, synergy and energy, flexible and fun, open discussions, clear direction, ideas flying around, taking on complex ideas, confidentiality in that “what happens in Vegas, stays in Vegas”. After these discussions, we went on to 3) Design-what it might truly look like and 4) Delivery-what will we commit to, an individual ranking of items central to creating a best learning experience.
  • The majority of us cannot live on the farm or in the bush; but can we design learning experiences along a similar model where learners contribute something of value to the community?
Lone Guldbrandt Tønnesen

Learnlets » Learning Experience Design thru the Macroscope - 0 views

  •  But with mobile technologies, we have the capability to truly start to deliver what I call ‘slow learning’: delivering small bits of learning over time to really develop an individual.
  •  Most of our learning comes from outside the learning experience.  But can we do better?
  • to develop individuals in micro bits over a macro period of time rather than macro bits over a micro bit of time (which really doesn’t work)
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  •  We have pieces of the puzzle ( smaller chunks, content models) and we have the tools (individualized delivery, semantics), but putting them together really hasn’t been done yet.
  •  We still have to figure out what our design process would look like,
  •  It’s really trying to build a system that is more mentor like than instructor like.
  • You have more small chunks of content, and more distributed performance model.
  • The point is to take the fact that technology is no longer the limit, our imaginations are.
  • : "Are you trying to teach information or skills? Okay – a skill. Well, that will require practice.
  • that calling it “slow learning” gives the opposite impression of what it actually is
  • and one could argue that what you are describing could actually be FAST learning
  • “spaced learning”
Lone Guldbrandt Tønnesen

Stanford's open courses raise questions about true value of elite education | Inside Hi... - 4 views

  • 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
  • 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.)
  • MOOCs question the value of teaching as an economic value point.”
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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.
  • It raises the question: Whose certification matters, for what purposes?
  • For one, the professors can only evaluate non-enrolled students via assessments that can be graded automatically.
  • it can be difficult to assess skills without being able to administer project-based assignments
  • With a player like Stanford doing something like this, they’re bringing attention to the possibilities of the Web for expanding open education
anonymous

Karim Rashid - 0 views

shared by anonymous on 02 Feb 12 - Cached
  •  
    Designer recommended by author Daniel Pink
Ivan Travkin

The Open Data Handbook - Open Data Manual - 4 views

  •  
    This handbook discusses the legal, social and technical aspects of open data. It can be used by anyone but is especially designed for those seeking to open up data. It discusses the why, what and how of open data - why to go open, what open is, and the how to 'open' data.
anonymous

Gamification in the Realm of Employee Training - 1 views

  • instead of thinking about creating learning objectives, gamification forces a designer to think about creating a challenge. All good games begin with a challenge; instruction should begin with a challenge and not with objectives
Lone Guldbrandt Tønnesen

Authentic Learning ~ #change11 - 5 views

  • We know that people learn best by being actively and collaboratively involved in learning but in universities, we continue to use lectures and other one-way, vessel filling, sage-on-stage, methods to tell students what they need to know
  • An authentic learning approach enables educators to design tasks and assessments that are based on the kinds of activities that are performed in the so called ‘real world’.
  • An authentic learning pedagogy focuses on students collaboratively creating genuine products that are polished and professional, and that are shared and published.
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  • realistic
  • think in the same ways as professionals
  • Technology-based cognitive tools
  • the creation of real products and artefacts, and are more worthy of the investment of time and effort in higher education than decontextualised exercises and tasks.
  • The creation of genuine sharable products ensures that authentic learning is in a position to capitalize on the participatory culture afforded by social media.
  • our model to guide your design: http://web.me.com/janherrington/AuthenticLearning/
Lone Guldbrandt Tønnesen

Learnlets » The 7 c's of natural learning - 2 views

  • Yesterday I talked about the seeding, feeding, and weeding necessary to develop a self-sustaining network
  • Choose: we are self-service learners.  We follow what interests us, what is meaningful to us, what we know is important. Commit: we take ownership for the outcomes.  We work until we’ve gotten out of it what we need. Crash: our commitment means we make mistakes, and learn from them. Create: we design, we build, we are active in our learning. Copy: we mimic others, looking to their performances for guidance. Converse: we talk with others. We ask questions, offer opinions, debate positions. Collaborate: we work together. We build together, evaluate what we’re doing, and take turns adding value.
  • With this list of things we do, we need to find ways to support them, across both formal and informal learning. 
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  • In formal learning, we should be presenting meaningful and authentic tasks, and asking learners to solve them, ideally collaboratively.
  • While individual is better than none, collaborative allows opportunity for meaning negotiation.  We need to allow failure, and support learning from it. We need to be able to ask questions, and make decisions and see the consequences.
  • I think there are 8 elements!! I miss Collate, this is not the same as Choose, it is about organising anbd structuring what we learn, (constructing our emergent uderstanding) as opposed to the selection of a direction.
  • in informal learning, we need to create ways for people to develop their understandings, work together, to put out opinions and get feedback, ask for help, and find people to use as models.  By using tools like blogs for recording and sharing personal learning and information updates, wikis to collaborate, discussion forums to converse, and blogs and microblogs to track what others think are important, we provide ways to naturally learn together.
  • the intersection of 1) self-organized learning and 2) online collaboration is what I consider should be a primary focus of organizational learning professionals
  • Common web 2.0 practice is to link back to what has been copied, a form of collaboration or perhaps cooperation.
  • However, real learning involves research, design, problem-solving, creativity, innovation, experimentation, etc
  • informal learning is NOT, by definition, manageable
  • just trying to raise awareness that what we typically do formally is not well aligned with how people really learn, and that supporting some of these activities is the key to unlocking organizational innovation.
  • but instead to provide a conducive environment and encourage them
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