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5 - PRIMARY Keyword matches for ARTICLE
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What is Instructional Design?
Many definitions exist for instructional design - all of them are an expression of underlying philosophies and view points of what is involved in the learning process. Distinguishing the underlying philosophy of learning (in terms of: How does learning occur? What factors influence learning? What is the role of memory? How does transfer occur? What types of learning are best explained by the theory? Learning Theory) can help instructors and designers select the design model most congruent with their education philosophies. The following is a listing of ID definitions:
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Prescriptive Models
Behaviorist
Prescribed Methodologies
Modern Approaches
Phenomenological Models
Cognitivist
Constructivist
Postmodern Approaches
Comparative Summaries
Behaviorism vs
Cognitivism vs
Constructivism
Models, like myths and metaphors, help us to make sense of our world. Whether it is derived from whim or from serious research, a model offers its user a means of comprehending an otherwise incomprehensible problem. An instructional design model gives structure and meaning to an I.D. problem, enabling the would-be designer to negotiate her design task with a semblance of conscious understanding. Models help us to visualize the problem, to break it down into discrete, manageable units.
The value of a specific model is determined within the context of use. Like any other instrument, a model assumes a specific intention of its user. A model should be judged by how it mediates the designer's intention, how well it can share a work load, and how effectively it shifts focus away from itself toward the object of the design activity.
Models, like other tools, shape the consciousness of those who use them. The tool molds the wielder who molds the tool, ad infinitum. Our models frame the reality we impose on the world and the experience that is forged out of their use brings us to higher levels of understanding about the design problem, but only within the framework of the specific models we adopt.
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This community shares information and resources in the area of online learning design and development. Though primarily aimed towards instructional designers, content developers and e-learning professionals, students, teachers and trainers should also find this group to be an informative resource.
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Historically, instructional development has tended to be an artistic endeavor, carried out in a cottage industry setting (Molnar, ). All aspects of development responsibility including analysis of the training or educational problem, design of the instruction, development of the materials, and in many cases, production of the media, evaluation, and revision were concentrated in the individual instructional developer. The developer's approach to each instructional problem tended to be ad hoc and subjective. The developer himself, more often than not, tended to have expertise in the subject matter being addressed, rather than formal training in instructional design science.
This model of the Renaissance man as instructional artist, solving each training problem as it arose with a combination of experience, intuition, and personal insight, began to become suspect as instructional development activities grew larger and more complex and as the consequences of inadequate training grew more and more expensive. Figure represents three points on a continuum of instructional development methodology. The artistic-intuitive approach, with its dependence on the judgement and multi-disciplinary skills of the individual developer gradually has yielded to more systematic approaches to the design and development of instruction and training systems and materials.
As shown on the figure, the search for better and more systematic ways to handle instructional problems led to the development of some important tools, including task analysis, the use of well defined behavioral objectives, and sophisticated measurement and evaluation methods. To protect against the consequences of poor training, more reliance was placed on empirical methods, which involved repeated tryout and revision of materials (Merrill & Boutwell, ). This stage in the evolution of a technology of instructional design is represented by the empirical phase of Figure .
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Development
There are two main methods for presenting the instructional content to learners (Merrienboer, ):
* Deductive - having the learners work from general information to examples
* Inductive - giving the learners examples to abstract
In addition, there are two main approaches for helping the learners to learn:
* Inquisitory - having the learners find examples or general information
* Expository - explicitly giving examples and general information.
Examples are representations of real life, such as case studies, models, scenarios, etc. While general information are principles, concepts, relationships between pieces of information, etc.
Which of course leads to four basic instructional strategies:
* Deductive-inquisitory: present general information and have the learners find and produce examples
* Deductive-expository: present general information and then present some examples
* Inductive-inquisitory: present examples and then have the learners abstract the general information
* Inductive-expository: present examples and then present the general information
Normally, the best method for building deep knowledge structures (having the most viscosity) is the inductive-inquisitory strategy. However, it is normally the most time-consuming (lacking in velocity). This is why training developers often become experts in the subject matter -- while creating the concepts, principles, procedures, etc. for the training program, they produce within themselves deep knowledge structures; while in turn, the users of these training design products only produce surface knowledge.
The deductive-inquisitory is also quite good but requires a bit more work as the designer normally has to ensure the learners have both the basic knowledge and general information to support the deductive aspect of it.
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17 - SECONDARY Keyword matches for ISD
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If you’ve spent years learning to use Instructional Systems Design processes to create e-Learning, the slight anarchy inherent in constructivist design may leave you feeling a little dizzy. Before you decide that constructivism has nothing to offer your organization, read this article to get a more complete perspective on the techniques and the resources available.
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Here are some of the wonderful responses that we received to this recent query in our TRENDS Newsletter.
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Free resources and fee based, white papers, discussion groups, and research reports. How To reports for beginners, product reviews for instructional designers and purchasers, to market analysis of the industry for market watchers and shapers.
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The ultimate objective for educational software is that it should be educationally beneficial, thus it is important in such environments to understand how usability contributes (or not) to educational goals (Jones et al., ). Squires and Preece ( ) argue that scholars have not considered the implications of usability features of an educational package in order to achieve educational goals. To this end, these authors advocate that there is a need to help evaluators consider the way in which usability and learning interact". To this end, this paper argues that there is a need for usability scholars to consider the way in which usability and learning (special emphasis on user interfaces of web-based courses), interact. It is therefore, the aim of this paper to review usability methods and learning theories currently used to design e-learning applications, examine specific usability attributes that need to be considered and report some preliminary findings derived from a test using a web-based testing system.
* Match between designer and learner models
* Navigational fidelity
* Appropriate levels of learner control
* Prevention of peripheral cognitive errors
* Understandable and meaningful symbolic representations
* Support personally significant approaches to learning
* Strategies for cognitive error recognition, diagnosis and recovery
* Match with the curriculum
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When and how does fun enhance learning, motivation, engagement, and retention? What can we learn from recent work on emotion and design? What makes learning fun for different topics and different types of learners? What do recent studies of computer and video games teach us about designing online learning? When does fun turn into gaming instead of learning? Can current models for instructional design support the implementation of courses perceived to be more fun? Are there new instructional models needed for e-learning? What makes an e-learning technology effective under what circumstances? Which processes can better aid in the selection and use of these technologies? What are the factors influencing the design and delivery of a rich and compelling e-learning experience? Why are so many existing courses "page-turners" and how can the learner experience be better incorporated into all phases of course design, development, and evaluation?
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Lots and lots of links
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I have often bemoaned the fact that training people do not look to what their colleagues in other departments are doing for examples of how technology can be applied to learning initiatives. There’s a bigger picture out there, yet "learning professionals" often get so precious about their perceived uniqueness that they can’t see the valuable lessons in e-business. The truth is that there is nothing that we do in e-learning that has not already been done, and done a great deal better, in e-business.
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Learning with software heuristics
The analysis in the previous section of the possible relationships between the Nielsen heuristics the notions of cognitive and contextual authenticity can be used as the basis of developing a set of 'learning with software 'heuristics. By looking for links between the individual relationships it is possible to propose an initial set of 'learning with software' heuristics:
* A need for a match between designer and learner models is implied by considering intrinsic feedback and the relationship between learner and designer models. At some level of system definition intrinsic feedback should provide a legitimate and understandable representation of cognitive tasks which ensures that the model formed by learners will be consistent with the designer's model. A low level representation close to the core language of a system will probably be confusing. Representation at too high a level will result in a superficial model, which will not be of genuine use, and may even be misleading. The designer and learner models do not need to be the same, but there should be no differences between them, which would cause misconceptions in the learner's model of the relationship between the interface and the system.
* A requirement for navigational fidelity is apparent when navigational structure, cosmetic authenticity, limited representation of the world and superficial complexity are considered. Interface designs that provide good usability may compromise authenticity by providing simplistic representations of the real world. The use of elaborate multimedia features may result in superficially complex interfaces which focus interaction on incidental navigation, rather than intended learning tasks.
* The need to consider appropriate levels of learner control follows from a consideration of learner control and shared responsibility, self directed learning (both with regard to credibility and complexity), tailoring and consistent protocols. A socio-constructivist view emphasises that learners should have a sense of ownership of their learning. This implies that they should have the maximum amount of control while still working in a supportive learning environment. The locus of control among peers during collaborative work is important.
* The need for the prevention of peripheral cognitive errors is implied by the relationship between complexity and error prevention. Cognitive errors should be relevant to the major learning issues. Peripheral' usability related errors should be anticipated and avoided. Where possible novice versions of an application should be provided.
* The requirement for understandable and meaningful symbolic representation follows from a consideration of representational forms and the use of symbols within and across applications. Learners should not be burdened with having to learn and remember arcane forms of interaction. The interface should place a low cognitive demand on the learner and functionality should be obvious. The same symbols, icons and names used to represent educational 'objects' and concepts should be used consistently throughout an application.
* The need to support personally significant approaches to learning follows from a consideration of multiple representations, learners' support materials and metacognition. It should be clear what learning styles are supported and which aspects of an application's design relate to learning style characteristics.
* The need for strategies for the cognitive error recognition, diagnosis and recovery cycle is implicit from the discussion of pedagogical techniques. Established strategies to promote the cycle of recognition, diagnosis and recovery should be used, e.g. cognitive conflict, scaffolding, and bridging.
* There is a clear need for a match with the curriculum is evident from a consideration of curriculum relevance and teacher customisation.
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The Theory into Practice Database: Database of learning theories, concepts and models
Instructional Design Models: Despite the title, this list provides links to Web resources on a myriad of aspects of instructional psychology and design (University of Colorado at Denver, )
The Encyplopedia of Educational Technology: Great extensive collection of short papers using small multimedia snippets to make the theories more tangible (San Diego State University, )
Instructional Technology Global Resource Network: A collection of papers and other useful resources for instructional designers
Theory and Theorists of Instructional Technology: Another good collection of short articles on the most important personalities and theories in instructional technology (written by D. Geier as a final project for a course taught at San Francisco State University by Dr. Kim Foreman)
An Electronic Textbook on Instructional Technology: Online version of a CD-ROM designed to provide an introduction to instructional technology by Irene Chen
Teaching Models: A selection of teaching models by Virginia Tech University
Linkliste Neue Medien: Extensive list of examples and links regarding the use of IT in education (Rechenzentrum Uni Heidelberg, mostly German)
Lern-Psychologie: Self instructional program in educational psychology and theories of learning (in German)
Basic methods of instruction: A series of tutorials on basic instructional methods by C. Reigeluth
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General PM articles also available.
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The pages of guidelines use and promote a systematic approach to training, an approach that thousands of organisations take because of its logic, simplicity and practicality. A systematic approach to training:
~groups and organises training functions into logical and manageable steps;
~has built-in checkpoints so that an organisation can gauge whether its training is effective in accomplishing its goals or if it is making efficient use of its time and
resources;
~results in cost-effective, practical training that directly supports the work performance of employees.
Appendices
: Types and Forms of Questions for Surveys and Interviews
: Checklist for Formatting Questions
: Checklist for the NGT Leader
: The Analyst's Primer for Analysing Work Performance
: Planning Your Needs Analysis Worksheet
: Completing a Task Analysis
: Planning Your Evaluation Strategy
: A Framework for Evaluating Training
: Verbs at a Glance
: Some Typical Standards for Learning Objectives
: A Checklist for Writing Learning Objectives
: Bloom's Taxonomy
: A Training Design and Development Model
: Guidelines for Increasing the Effectiveness of an Instructional Design
: Training Design and Development Worksheets
: A Practical Guide to Classroom Methods
: Quality Standards for Developing Training Materials
: Training Design Checklist
: Tips for Using Climate-setting Exercises Effectively
: A Checklist for Developing a Job Aid
: Degree of Difficulty
: Case Study Design Procedures
: Case Study Development Checklist
: Guidelines for Developing Role Plays
: How to Prepare and Use Flipcharts
: Use of Overhead Transparencies and Flipcharts
: A Guide for Using Films and Videos
: Worksheet for Planning the Validation Strategy
: The Key Skills of the Instructor/Facilitator
: Guidelines for Giving Feedback
: A Leader's Guide to Discussion
: Techniques for Asking Questions
: Stimulating Discussion
: Questioning and the Learning Cycle
: Sample Learner Reaction Sheets
: Sample Pre-test and Post-test
: A Dozen Ways to Improve Training Transfer
: The Physical Learning Environment
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Learning Theories - Some Strengths and Weaknesses
What are the perceived strengths and weaknesses of using certain theoretical approaches to instructional design?
Behaviorism
Weakness -the learner may find themselves in a situation where the stimulus for the correct response does not occur, therefore the learner cannot respond. - A worker who has been conditioned to respond to a certain cue at work stops production when an anomaly occurs because they do not understand the system.
Strength - the learner is focused on a clear goal and can respond automatically to the cues of that goal. - W.W.II pilots were conditioned to react to silhouettes of enemy planes, a response which one would hope became automatic.
Cognitivism
Weakness - the learner learns a way to accomplish a task, but it may not be the best way, or suited to the learner or the situation. For example, logging onto the internet on one computer may not be the same as logging in on another computer.
Strength - the goal is to train learners to do a task the same way to enable consistency. - Logging onto and off of a workplace computer is the same for all employees; it may be important do an exact routine to avoid problems.
Constructivism
Weakness - in a situation where conformity is essential divergent thinking and action may cause problems. Imagine the fun Revenue Canada would have if every person decided to report their taxes in their own way - although, there probably are some very "constructive" approaches used within the system we have.
Strength - because the learner is able to interpret multiple realities, the learner is better able to deal with real life situations. If a learner can problem solve, they may better apply their existing knowledge to a novel situation.
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column chart showing Research Finding and Implications for Practice broken out by
Learning Effectiveness: Interaction with Content
Learning Effectiveness: Interaction with Instructors
Learning Effectiveness: Interaction with Classmates
Learning Effectiveness: Interaction with Course Interfaces
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SOME COMPLICATING FACTORS: IKIWISI, COTS, AND RAPID CHANGE
The recent developments of IKIWISI (I’ll know it when I see it), COTS (commercial-off-the-shelf) software, and the increasingly rapid change in information technology have combined to unsettle the foundations of the old airtight-requirements approach.
IKIWISI
Successfully specifying software requirements in advance is difficult. But when user- or group-interactive systems are involved, it proves nearly impossible. Users asked to specify requirements generally claim, "I don’t know how to tell you, but I’ll know it when I see it." Furthermore, users may initially feel that they "know it when they see an initial demo or prototype. But their needs and desires change once they begin operating the system and gain a deeper understanding of how it could support their mission. Thus, the requirements tend to emerge with continued use and mission understanding rather than be prespecifiable.
COTS
Another fundamental tenet of the air-tight-requirements approach is that the prespecified requirements completely determine the system capabilities. How-
ever, with large, pervasive COTS products, the COTS capabilities effectively determine the requirements.
Rapid change
As I discussed, specifying airtight requirements takes time. But particularly for Internet and Web-based systems, rapid change can create an impossible-to-win game of catch-up. As you slowly grind out and validate airtight requirements, rapid changes in COTS releases, competitive threats, stakeholders, reorganizations, and price structures make these requirements increasingly obsolete. And by the time you thoroughly change-control, update, and revalidate them, new developments make them obsolete all over again.
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The "edge of chaos" is a critical state between order and chaos in which nonlinear systems (e.g., interacting teacher and students) are at their optimum performance potential or maximum adaptability. Systems poised at the edge of chaos are maximally adaptive because of the complex connections and distinctions of their interacting agents. This complexity implies that the interacting agents are distinct enough to permit flexibility and yet connected enough to establish stability. Highly ordered assemblages such as crystals lack complexity because they have rigidly connected molecules without flexibly distinct movement. On the other extreme, highly chaotic assemblages such as gases also lack complexity because they have flexibly distinct molecules without structured connections. However, interacting agents on the edge of chaos such as students and a teacher are complex because they are distinct enough to permit flexible change and yet connected enough to establish stability. Furthermore, they can generate a holistic system of interaction that is emergent and not reducible to the individual agents. In other words, the whole is more than the sum of the parts.
Complexity may be further defined as "the ability to switch between different modes of behavior as the environmental conditions are varied" (Prigogine & Nicolis, , p. - ). Complex systems on the edge of chaos permit a flexible openness and sensitivity to varied options, which enable these systems to continually find and select the most attractive options of adjusting, replacing, or reorganizing at a higher level of fitness. However complex systems, which are either rigidly bound by ordered conditions (fused connections) or indiscriminately scattered by chaotic conditions (confused distinctions), are not able to continually adapt to higher levels of fitness (complexity).
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Unskilled and Unaware of It: How Difficulties in Recognizing One's Own Incompetence Lead to Inflated Self-Assessments - People tend to hold overly favorable views of their abilities in many social and intellectual domains. The authors suggest that this overestimation occurs, in part, because people who are unskilled in these domains suffer a dual burden: Not only do these people reach erroneous conclusions and make unfortunate choices, but their incompetence robs them of the metacognitive ability to realize it.
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The primary thesis of Value-Based Software Engineering (VBSE) is that the integration of a software system’s stakeholder value propositions into the system’s
definition, design, development, deployment, and evolution is critical to the system’s success. This white paper:
· Analyzes the sources of software project failure in the Standish Report, and shows that many of the failed projects were caught in the vise of valuei nsensitive
software engineering.
· Discusses promising research ideas for improving our capability to perform VBSE.
· Presents a roadmap for making progress toward VBSE and its resulting benefits.
The white paper concludes with a summary of the relations between VBSE and other software research and applications areas. It is unavoidably involved with software and information system product and process technology, and their interaction with human values. It is strongly empirical, but includes new concepts in need of stronger theory. It uses risk considerations to balance software discipline and flexibility, and to answer other key how much is enough?" questions. And it helps illuminate information technology policy decisions by identifying the quantitative and qualitative sources of cost and value associated with candidate decisions.
Failed Software Projects: Sources and Remedies
The CHAOS Report [Standish, ] surveyed several hundred software projects and found that only % of them were completed within their planned budget and schedule. The report analyzed the major sources of failure for the other projects, and found that eight problem sources accounted for % of the failures. Each of these sources is discussed below in terms of their relation to value-based approaches to software engineering.
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