George Appel’s Sandbox

Any ontology is a formal representation of reality, relative to a given domain and the objects and relationships that best describe one’s knowledge of the domain at that time.

Let’s get concrete!

I know enough about the American Civil War that I could develop a fair concept map (ontology) to represent the reality of the war as I see it in my mind.  If I were to ask a man on the street to do the same thing, chances are the representation would be less “complete” than mine.  Each would represent the extent of demonstrated knowledge for that domain at that time by us.

Could I improve my Civil War ontology?  Of course, if I used tools on the web, I could do so.  I could revisit the books I have read.  I could represent my enhanced knowledge using perhaps, a wiki.  Could my man on the street do the same?  Perhaps so.  I could use my knowledge to scaffold his representation and work with him, in collaboration, to use web tools to create new knowledge for him.  I might also enlist some other learners to do the same and at some point compare all of our ontologies and synthesize a whole new ontology which we would then publish on the net for others to see and share.

Sound quite simple, doesn’t it?  It will only work if I and my fellow learners adhere to principals inherent to the learning theory that buttresses our work.  That in this case is of course, social constructivism.  I take on the role of the “Most Knowledgeable Other”.  I can now identify the “Zone of Proximal Development” for my man in the street as well as myself.  And I have provided for a degree of “Social Interaction”.

Is the learning top down or bottom up?  If I choose the domain, The American Civil War, for myself, then I am controlling my learning.  If on the other hand, I chose the domain for the learner, then I control the learning.  However, the learning process is bottom up as we are creating knowledge for ourselves.  Yes?

My effort to create a concept map for the civil war is perhaps the first step in the learning process.  From the prospective of the man on the street it may be considered an “expert map”.  From my own perspective it falls far short of an expert map.  With more work, the addition of links to resources and collaborative help from an expert in the field, I might build a pretty good model which could serve as a basis for evaluation of other learners work.  I could also prepare “skeleton maps” for other learners who would benifit from this scaffolding.

Here is a good example of how what might appear to be an “expert map” created by the Centre for Teaching Excellence describing learning, falls short from my prespective.  Conspicuous by it abscence is the object “concept mapping”.

Let’s talk about knowledge.  Let’s talk about knowledge as it relates to a traditional K-12 curriculum.  About twelve years ago I designed a curriculum management software application.  As I began it’s development I decided that “it all begins with content areas”.  In other words the frameworks of content in our traditional formal educational systems for instruction are top down in nature.  Every school district develops courses within content areas.  They might be, mathematics, social science, language arts, science, foreign language, art, music, family & consumer science, technology, business, etc.  This domain of content areas is meant to represent the scope of knowledge to be addressed in the k-12 curriculum of that district.  For each element of that domain there exists an implicit or explicit content taxonomy.

Taxonomy

A taxonomy is just a classification of things. They are usually hierarchical. They do two things: give exact names for everything you’re dealing with (your ‘domain’) and show which things are parts of other things (sometimes called parent-child relationships, sometimes called broader-narrower).  In our case someone develops what I call major content strands.  For the domain music, they might be: The elements of music; Musical history & style; Listening to music; Performing music; Creating music; The role of music in society and valuing and evaluating music.  For each of these major strands there would appropriate sub strands, perhaps three or for levels deep.  Assuming the same thing is done for all other content areas in the domain, we would have a set of taxonomies as a framework for instruction.  This would represent the scope of instruction.  The assumption would be that every course objective in every course in any content area could be mapped into the content area taxonomy.  If this were done then we could define the sequence of learning and the degree of articulation of the instruction.

I mentioned earlier that content taxonomies are implicit or explicit.  In almost all cases, these taxonomies are not explicitly designed or used as guides for curriculum development.  Instead decisions about content are made primarily by textbook authors.  As an algebra teacher, my focus and thus the focus of the learners is on the table of contents of my textbook.  I assume that in other courses in the k-12 mathematics curriculum the rest of the “domain of content in mathematics” is being well addressed.

Ontology

An ontology is like a taxonomy in that it is going to contain all the entities in your domain (for one reason or another–probably its roots in philosophy–people often seem to use the term “universe” when talking about the domain of an ontology), and show the relationships they have to each other. However, it does more: it has strict, formal rules (a “grammar”) about those relationships that let you make meaningful, precise statements about your entities/relationships.

An ontology is a formal representation of a set of concepts within a domain and the relationships between those concepts. It is used to reason about the properties of that domain, and may be used to define the domain.

An ontology as a formal representation of reality as seen by it’s creator at the time it is created.

A Simple Knowledge Engineering System

As we said earlier, there is no one “correct” way or methodology for developing ontologies. Here we discuss general issues to consider and offer one possible process for developing an ontology. We describe an iterative approach to ontology development: we start with a rough first pass at the ontology. We then revise and refine the evolving ontology and fill in the details. Along the way, we discuss the modeling decisions that a designer needs to make, as well as the pros, cons, and implications of different solutions.

First, we would like to emphasize some fundamental rules in ontology design.  These rules may seem rather dogmatic. They can help, however, to make design decisions in many cases.

1) There is no one correct way to model a domain— there are always viable alternatives. The best solution almost always depends on the application that you have in mind and the extensions that you anticipate.

2) Ontology development is necessarily an iterative process.

3) Concepts in the ontology should be close to objects (physical or logical) and relationships in your domain of interest. These are most likely to be nouns (objects) or verbs (relationships) in sentences that describe your domain.

That is, deciding what we are going to use the ontology for, and how detailed or general the ontology is going to be will guide many of the modeling decisions down the road. Among several viable alternatives, we will need to determine which one would work better for the projected task, be more intuitive, more extensible, and more maintainable. We also need to remember that an ontology is a model of reality of the world and the concepts in the ontology must reflect this reality. After we define an initial version of the ontology, we can evaluate and debug it by using it in applications or problem-solving methods or by discussing it with experts in the field, or both. As a result, we will almost certainly need to revise the initial ontology. This process of iterative design will likely continue through the entire life cycle of the ontology.

Folksonomy

Folksonomy is a new term — I mean, literally, it came about in the last couple of years. It’s essentially what you see on del.icio.us or flickr by way of the use of tags. It’s in many ways the exact opposite of a taxonomy in that:

a. Folksonomies are flat (that is, they have no hierarchy, and show no parent-child relationships)
b. Folksonomies are completely uncontrolled (part of making a taxonomy is deciding what the names of your entities are, but in a folksonomy, there can be a thousand different words for the same thing)

Any relationships you see in a folksonomy have to be derived mathematically (statistical clustering).

However, a folksonomy is like a taxonomy in that they share the same purpose: classification. A lot of debate is going on right now about which is better, though of course the answer is that you use them for different purposes. It’s nice to have both.

• The core property of a taxonomy is that it possesses a hierarchical structure.
• A taxonomy classifies according to properties internal to the data, a classification can be made
according to external criteria.
• Taxonomies tend to mix with simple ontologies. Using more specific terms than just “ontology”
(like “ontology with inheritance hierarchy”) helps to give more clarity.
• Once a lot of properties and relationships are added to a hierarchical structure, the term “ontology”
is better suited than “taxonomy”.
• A classification tells you in which box your piece of data is, an ontology tells you what your data is.

Grass-roots categorization, by its very nature, is idiosyncratic rather than systematic. That sacrifices taxonomic perfection but lowers the barrier to entry. Nobody needs a degree in library science to participate.

It comes down ultimately to a question of philosophy. Does the world make sense or do we make sense of the world? If you believe the world makes sense, then anyone who tries to make sense of the world differently than you is presenting you with a situation that needs to be reconciled formally, because if you get it wrong, you’re getting it wrong about the real world.

If, on the other hand, you believe that we make sense of the world, if we are, from a bunch of different points of view, applying some kind of sense to the world, then you don’t privilege one top level of sense-making over the other. What you do instead is you try to find ways that the individual sense-making can roll up to something which is of value in aggregate, but you do it without an ontological goal. You do it without a goal of explicitly getting to or even closely matching some theoretically perfect view of the world.

Critically, the semantics here are in the users, not in the system. This is not a way to get computers to understand things. When del.icio.us is recommending tags to me, the system is not saying, “I know that OSX is an operating system. Therefore, I can use predicate logic to come up with recommendations — users run software, software runs on operating systems, OSX is a type of operating system — and then say ‘Here Mr. User, you may like these links.’”

It’s all dependent on human context. This is what we’re starting to see with del.icio.us, with Flickr, with systems that are allowing for and aggregating tags. The signal benefit of these systems is that they don’t recreate the structured, hierarchical categorization so often forced onto us by our physical systems. Instead, we’re dealing with a significant break — by letting users tag URLs and then aggregating those tags, we’re going to be able to build alternate organizational systems, systems that, like the Web itself, do a better job of letting individuals create value for one another, often without realizing it.

IWhy do we examine taxonomies, ontologies and folksonomies?  What part can they play in our quest to leverage learning with web tools?

Heraclitus has said that you cannot step twice in the same river. It is impossible to step twice in the same river because the river has flowed on; everything has changed. And not only has the river flowed on, you have also flowed on.

To paraphrase Marshal McLuhan slightly, “We shape our technologies and then our technologies shape us.”

Let’s examine the evolution and influence of changing technologies and the effect on learning environments, learning tools and learning demands in the last 70 years or so.  When I began school, we had books, a blackboard, chalk, ink wells and pens with nibs, pencils and our tablets.  We had the classroom library a number of dictionaries and perhaps a set of encyclopedias.  We learned to read, write and cypher with these tools.  The knowledge resided in our books and the mind of our teacher.  We learned by rote and recited what we learned.  The learning style was definitely behavioral in nature and decidedly top down.

Some years later, as a young teacher, I saw the advent and use of the slide projector, the mimeograph machine,  the film strip projector, the film projector, ballpoint pens, the opaque projector and the overhead projector.  We could roll in a cart with a TV on it if no one else was using it at that time.

There was someone on the staff called the “Audio-Visual Coordinator”, a forerunner of today’s “Informational Technology Director.”  We were expected to integrate these new tools into our teaching.  We submitted weekly lesson plans.  The teaching style was still behavioral but we had new ways to present content.  We could look farther afield for content.  I can remember some teachers who would show a movie every Friday.  TV never really worked out, even though our local Public Television station scheduled what they believed would be relevant material.  It was only accessible when they broadcast it.  (Synchronous)

Fast forward to today.  The overhead projector has morphed into “PowerPoint.”  The mimeograph machine has been replaced by the Xerox and scanner; the slide and filmstrip projector has been replaced by “Slideshare.”; the film projector by “YouTube“; the encyclopedias by “Wikipedia“; chalkboards by “Whiteboards” and lesson plans by “Moodles“.

The employment of these new web technologies requires no change in teaching style.  Teachers can continue to teach from a behaviorist stance; top down to passive learners.  However, that’s not the end of the story.  We have digital learners among us.  The social networking sites like Facebook, MySpace, Flickr, Delicious, blogs, wikis, aggregators, iPhone, etc. have contributed to a profound transformation in today’s young people around the world.

“We shape our technologies and then they shape us.”

Informal learners (our students) are in a different time and space than we were at their age.  They power down when they enter our classrooms.  The changing learning environment is a true paradigm shift and won’t allow us to step into the same river ever again.

I believe that the read/write Web, or what we are calling Web 2.0, will culturally, socially, intellectually, and politically have a greater impact than the advent of the printing press. I believe that we cannot even begin to imagine the changes that are going to take place as the two-way nature of the Internet begins to flower, and that even those of us who have spent time imagining this future will be astounded by what happens.  (Steve Hargadon)

Traditional – > New Environments

Teacher-centered instruction – >Learner Centered environments
Single sense stimulation – > Multisensory stimulations
Single path progression -> Multipath progression
Single media – > Multimedia; hypermedia
Isolated work – > Collaborative work
Information delivery -> Information exchange, publication, creation
Passive learning -> active/exploratory/inquiry-based learning
Factual/literal thinking -> Critical thinking, informed decision-making
Reactive response -> Proactive/planned action
Isolated, artifical context-> Authentic, real world context

“The new education must teach the individual how to classify and reclassify information, how to evaluate its veracity, how to change categories when necessary, how to move from the concrete to the abstract and back, how to look at problems from a new direction – how to teach himself. Tomorrow’s illiterate will not be the man who can’t read; he will be the man who has not learned how to learn.”
(Herbert Gerjouy as quoted by Alvin Toffler in “Future Shock, 1970, p. 414)

If in a new paradigm we all return to zero, what are our responsibilities to the future of education in America?

Instructional design and development must be based upon some theory of learning and/or cognition; effective design is possible only if the developer has developed reflexive awareness of the theoretical basis underlying the design.

Do learning theories compete?  Each has a different view of the student regarding how he/she learns, one’s previous knowledge and the role of the environment in learning.

The concept of learning styles is rooted in the classification of psychological types. The learning styles theory is based on research demonstrating that, as the result of heredity, upbringing, and current environmental demands, different individuals have a tendency to both perceive and process information differently.

It is said that behaviorism fell out of favor in the academic sphere in the 60′s.  However, one must keep in mind, that in the classroom, to this day, behaviorism is still the default learning theory upon which learning practice relies.  That is not to say there are no instances of learning practice informed by cognitivism, constructivism or other post modern theories.  Many of us have moved on particularly with respect to cognitivism and constructivism.

The cognitivist revolution replaced behaviorism in 1960s as the dominant paradigm. Cognitivism focuses on the inner mental activities – opening the “black box” of the human mind is valuable and necessary for understanding how people learn. Mental processes such as thinking, memory, knowing, and problem-solving need to be explored. Knowledge can be seen as schema or symbolic mental constructions. Learning is defined as change in a learner’s schemata.

A response to behaviorism is that people are not “programmed animals” that merely respond to environmental stimuli; people are rational beings that require active participation in order to learn, and whose actions are a consequence of thinking. Changes in behavior are observed, but only as an indication of what is occurring in the learner’s head. Cognitivism uses the metaphor of the mind as computer: information comes in, is being processed, and leads to certain outcomes.

… constructivism does present an alternative view of learning other than the objectivistic conception of learning, and provides a set of design principles and strategies to create learning environments wherein learners are engaged in negotiating meaning and in socially constructing reality. However, it is not suggested here that all designers should adopt constructivism as the only solution to all instructional problems. Rather they should reflect upon and articulate their conceptions of knowing and learning and adapt their methodology accordingly. The challenge for the design community is to understand and evaluate the different perspectives, methods and assumptions appropriate to fundamentally different contexts. The possibility of different conditions for different outcomes is completely consistent with the long-standing notion in instructional design that different types of outcomes require different instructional conditions (Gagne, 1965; Reigeluth & Curtis, 1987).

The following teaching styles show the influence of the major learning theories.

Four Basic Teaching Styles (Penn State University)

Formal Authority: A instructor-centered approach where the instructor feels responsible for providing and controlling the flow of content which the student is to receive and assimilate. The formal authority figure does not concern himself with creating a relationship with the student nor is it important if the students build relationships with each other.
Demonstrator or Personal Model: A instructor-centered approach where the instructor demonstrates and models what is expected (skills and processes) and then acts as a coach or guide to assist the students in applying the knowledge. This style encourages student participation and utilizes various learning styles.
Facilitator: A student centered approach where the instructor facilitates and focuses on activities. Responsibility is placed on the students to take initiative to achieve results for the various tasks. Students who are independent, active, collaborative learners learners thrive in this environment. Instructors typically design group activities which necessitate active learning, student-to-student collaboration and problem solving.

Delegator: A student-centered approach whereby the instructor delegates and places much control and responsibility for learning on individuals or groups of students. This type of instructor will often require students to design and implement a complex learning project and will act solely in a consultative role. Students are often asked to work independently or in groups and must be able to effectively work in group situations and manage various interpersonal roles.  Can you see the threads of learning styles embedded in these?

Well into the 21st century, disagreement about the efficacy of each theory abounds.  Is one theory the best?  Can a teacher function in more than one of these realms in the classroom?  Are any mutually exclusive?  On what basis would a teacher perform best or even better?  What drivers influence a teacher’s decision re learning theories?

I think we need to use our newly acquired knowledge of the learning theories to examine our own classroom practices.  What theory or theories drive what we do in the classroom?  We need to reexamine our belief systems relative to the tenets of the theories.  Do learners begin with empty heads waiting for us to pour in the knowledge?  Do students have prior, albeit incomplete, knowledge of a particular concept?  If so, is that where we begin with each learner?  What role does the learner play in the learning experience?  Is it passive or active?  Is that role enhanced by collaboration?  Is the learning external or internal with respect to the learner?

I believe it is the case that, as teachers, we tend to teach in the way we were taught. We may not be able to clearly trace the genesis of our instructional design, but the likelihood is that it is “Behaviorist” in nature. That was certainly the case for me as a new mathematics teacher in the early 60′s. The characteristics of my teaching style were:
1. The process is sequential and linear
2. Planning is top down and systematic
3. Objectives guide development
4. Experts, who have special knowledge, are critical to ID work
5. Careful sequencing and the teaching of subskills are important
6. The goal is delivery of preselected knowledge
7. Summative evaluation is critical
8. Objective data are critical.

In the mid 60′s we were introduced to something called the “New Math“.  Suddenly, as math teachers we were talking about discovery learning, SMSG (School Mathematics Study Group), Mary P. Dolciani,  UICSM (University of Illinois Committee on School Mathematics), Max Beberman, rubber sheet geometry, base 5 and the commutative law.  I was totally swept up by the changes.  Cognitivism was the guiding force.  I got a grant from the National Science Foundation (NSF) and went off to Wayne State University for three summers of training.  I think it was Linus in “Peanuts” that said, “How can I learn new math with an old math mind”?  The real question should have been, “How can I, as a teacher, teach new math with an old math mind”?  The students were fine with the material, but the back lash was fierce and training for elementary teachers failed miserably.  One parent went to our school board meeting and insisted that we stop teaching about “ordered pairs“.  The “back to basics” movement and the unwillingness to provide sufficient support eventually buried the new math.  But the experience got us all thinking about the assumptions implicit in behaviorism and the attractiveness of cognitivism and constructivism.  There were, and still are, major problems with the systemic changes necessary to transform learning design and practice based upon these new theories.

Many have forgotten that similar things were happening in science and social studies curricula.  One of the most exciting was “Promise of America” published by Scott Foresman in the early seventies.  Imagine this:

This thematically-organized, cultural studies reader asks students to engage in a critical way our society’s deeply-held beliefs regarding social equality, education, free press, health care, work and success, and civil liberties.  Do we have certain birthrights as Americans as a result of promises made in our Declaration, Constitution, and other early sources?  How have these rights been amended or expanded over time, and to what degrees have these promises been kept for different groups?  Students will encounter a range of political and philosophical positions, historical depth and contemporary perspectives, and a variety of genres (speeches, newspaper editorials, photographs, cartoons, and expository essays) as they grapple with what it means to be an American.

It wasn’t long before parent groups were having us “black out” passages in the series and boycotted Scott Foresman at book exhibitions.  Students were looking at primary sources and questioning conventional wisdom!  It was not to be.  Like new math this incursion was squelched.

In biology, we had BSCS, a wonderful series of biology courses fully espousing cognitivism and laying the basis for much more performance task oriented science instruction.

We also had  found new heros like Jerome Bruner, and Seymour Pappert, (Mindstorms) a constructivist.  And low and behold, personal computers came on the scene and we began logo training in our elementary and middle schools.  Turtle graphics was the rage and constructivism had found a learning platform!  But that was just the beginning.

In the last forty five years I have seen the emergence of “new” learning theories and the accompanying debates about the efficacy of each. A reasonable grouping  of the major theories is; Behaviorism, Cognitivism, Constructivism, Social Constructivism and Connectivism.

Why talk about Learning Theory?  How does Learning Theory relate to learning design?

Instructional design and development must be based upon some theory of learning and/or cognition; effective design is possible only if the developer has developed reflexive awareness of the theoretical basis underlying the design.

In other words, the instructional design that we espouse is best delivered if what we do is willful and deliberate and flows from a knowledge of the tenets of these major learning theories.   It is sometimes called “Reflective Practice“. It is important to note that underlying each of these theories is a belief as to how we learn; the nature of the learner.

In future posts, we will look at the tug of war between cognitivists, constructivists and behavioralists. We will also address the question of each theories efficay, whether one can espouse more than one theory at a time, and if any pairs are mutually exclusive.  What do you think?  Is knowledge of learning theories a necessary but not sufficient condition in the kind of transformation in teaching and learning we are examining?

Here are three models of developmental learning stages.  Each gives us a sense of the developmental nature of the desired transformation in teacher and learner behavior.

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Many teachers feel they are on an uncharted journey when learning technology skills. The good news is that most teachers are on this journey together and that it has recognizable stages along the way. Given appropriate support at each stage, teachers can learn to integrate technology into the curriculum. The Apple Classrooms of Tomorrow (ACOT) studied how technology affects teaching and learning. The research results suggest this series of instructional stages:

Entry Stage
Although educators, students and the community are aware that technology creates new possibilities for learning and teaching, the system is slow to change. Access to computers is frequently an issue at the entry stage. It is often a time when teachers slightly modify classroom activities to include technology. For example, instead of having students conduct research with print resources, teachers will bring students to a computer lab. However, the nature of the activity stays the same. This can be a frustrating stage for many teachers. Collaborating with other teachers to exchange learning activities and ideas can help entry-stage teachers move ahead to the next stage.

Adaptation Stage
At this stage, technology becomes thoroughly integrated into teaching patterns. Teachers at this stage are often excited about using technology to prepare and present information. Teachers become more comfortable with having students pursue individual interests, but they still design and direct the activities. These teachers need to see effective models and lessons for integrating technology to help them envision a more student-centered learning environment. Collaboration and mentoring are critical at this stage.

Transformation Stage
At this stage, technology widely changes and expands the learning environment. Transformation-stage teachers use technology seamlessly in the classroom. Project-based learning activities are common, and students are self-directed. Students have many opportunities to design their own learning pathways, and teachers utilize new forms of assessment. There is an emphasis on higher-order thinking. These teachers continue to innovate and expand on technology use as new tools become available. Teachers at this stage should continue to collaborate with other teachers and to mentor others.
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The “one size fits all” approach to professional development does not meet the needs of all teachers. Sheingold (1990) believes that integrating technology into instruction involves more than learning how to operate machines. It deals with teachers’ attitudes about learning something new—something the student may understand better than the teacher. Researchers have identified phases teachers progress through as they become more involved in using technology.

Novice
Teachers generally try to establish order in a radically transformed physical environment. They deal with reorganizing furniture, unpacking boxes, running extension cords, untangling cables, and setting up computers. At this stage, they will develop basic computer skills including navigation around the desktop. They learn to get comfortable with the basic operations of equipment with students, or sometimes only a willingness to have students use equipment, i.e., without teacher support.

Apprentice
Teachers concerns begin to tilt toward using computers rather than connecting them. They view computer instruction for students as a new curricular topic or personal reward of free time. Teachers at this stage learn core technology skills to enhance personal productivity. They use their new technology skills to communicate with parents, students, and colleagues. Presentation tools are used to disseminate information to the whole class. Word-processed documents,ets are developed to individualize instruction. As teachers progress through this stage, they begin to build links between technology and instruction. They incorporate computer-based activities aimed primarily at teaching children how to use technology, e.g., keyboarding instruction and word processing. Technology supports instruction through drill-and practice and tutorial applications. They ask for software in particular subject areas. They want sample lessons and time to review software they can adapt to their established curricular and pedagogical preferences. They need support with planning and leading instruction in the computer lab.

Instructor
The new technology has become thoroughly integrated into traditional classroom practice. Lecture, recitation, and seat work remain the dominant form of student tasks; but students use word processors, databases, some graphic programs, and many computer-assisted instructional packages for approximately 30-40% of the school day. As teachers progress through this stage, they learn to individualize curriculum and instruction to meet a wider range of learning styles and abilities. They share and delegate teaching duties to the computer; however, the absence of the computer would not prevent the implementation of instruction. To move beyond this stage, teachers need to se models of hoe to plan a cross-curricular, learner-centered project.

Coach
At this stage, teachers rethink how they teach. Their role shifts from direct instructor to facilitator. They understand learners construct their own understanding based on their prior experience. They recognized the importance of building on the conceptual and cultural knowledge students bring to the classroom. Students collaborate on learning tasks. Technology is seamlessly integrated into the learning environment. It is a tool used to accomplish instructional goals, and it enables students to do things that were not be possible without it. The absence of computers would prevent the implementation of instruction. To move beyond this stage, teachers increase their own mastery by mentoring colleagues through peer teaching and by leading staff development. They use technology to participate in new kinds of professional development such as collaborative workgroups and on-line study groups. NCREL’s Indicators of Engaged Learning define the dimensions of teacher’s instructional practice at this stage.

Expert
The classroom is expanded to include anywhere learning takes place. The teacher models life long learning and has become skilled at involving students in developing authentic learning activities. Many classroom learning activities are extended to the family environment. Students are self-directed and spend more time learning from each other and experts in the community. They work in collaboration with people in different locations all over the world. Some are involved in apprenticeship programs. The technologies are transparent. Teachers at this stage begin to have a tremendous impact on the school and community. They are catalysts that cause significant change. They cannot get to this stage without a clear vision, leadership and administrative support, community support, access to current technologies including the Internet, time for planning and learning, etc.

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This model identifies four stages of teacher technology efficacy:

Stage 1: Preliterate end users – These teachers have no experience with computers and other technologies. Either they have never had the chance to be trained or they simply are not interested in becoming literate. The challenge is to help such teachers see the benefits technology can offer them: more efficient use of time, more easily managed tasks, less bulky paperwork, differentiation of instruction, ease of record keeping.

Stage 2: Software technicians – These teachers have begun to use common applications for their own personal use. They may search and surf the Web, keep in touch with family and friends using e-mail, use a word processing application for letters and forms, and chat online. Teachers at this level are ready to be introduced to the notion that computers can serve useful purposes in the classroom setting when technology is integrated into the curriculum.

Stage 3: Electronic traditionalists – These teachers are proficient in using technology in the classroom. The implementation, however, is an extension of traditional classroom functions: digital lesson plans, electronic grade books, drill and practice software, tests, quizzes, and tutorials. The emphasis is to assist such teachers in seeing new possibilities in the classroom: online projects, virtual field trips, distance learning, Webquests, and much more.

Stage 4: Techno-constructivists –These are the teachers who integrate technology into the curriculum so that it not only complements instruction but redefines it. The true techno-constructivists have come through the previous three stages and have realized the full potential of technology to help children build on their own experiences, construct their own meanings, create products, and solve problems successfully.

How important is it to label and monitor the stages of development of teachers and what about administrators?

Keep it simple, stupid.  Sounds reasonable.  But is it this case?  What level of simplicity/complexity should this learning object have.  Let’s look at my objectives for the learning object and then at possible pathways through the object for the learner.

My Objectives:

Through a process of blended learning, employing face to face and online experiences, in a constructivist, collaborative, learning mode; develop and publish a “Transformational Learning Object”, using a model-centric learning design, capable of;

1. enabling professionals to build a body of skills using web based tools.
2. document the skill set with an e-portfolio.
3. buttress the learning with an understanding and conceptualization of related theoretical constructs.
4. synthesize the skill set and the theory to transform learning in their classrooms.

Possible Learning Pathways.

1. Acquire minimum competency with several tools of interest and use.
2. Add a simple e-portfolio of learned skills.
3. Continue skill building and documentation (e-portfolio) plus factual, conceptual and procedural knowledge of behaviorism, constructivism, Bloom’s revised taxonomy and ontologies.
4. Construction of web based learning experiences for students.
5. Mentoring Fellow professionals.

The pathways chosen by the end users are intended to allow for Personal Learning Plans (PLP) based upon the developmental stage at which the user finds himself or herself and attainment of the next stage.

The learning process, posited on a transformation in teaching and learning, is not simple and requires a lot of careful planing and collaborative effort

Do you believe that a paradigm shift in our learning enviornments and tools is in process?  If so, what is your evidence?

Once in a while something comes along and has the appearance of a “killer app“.  For me it has been “Jing“.

Jing is a form of “screen capture” software.  Unlike most 2.0 apps, it resides on your desktop and it’s products can be saved in a variety of ways including generating a url for links to blogs, wikis, etc.  One part of the app allows you to capture all or a portion of a screen and annotate it in various ways.  The other allows you to capture a screen, start recording and capture up to 5 minutes of your actions on the screen and the accompanying audio.

Here’s an example of the video capability.  Imagine the power this gives one for building simple training video clips.

Can you think of any procedure that you carry out on your computer that you might want to share using Jing?

Wesley Fryer puts it best.

A big part of “the learning revolution” is the ability we now have, as educators, to engage in self-directed professional development at almost any time. We no longer have to wait for our school district or campus leader to schedule a formal day of PD to learn new knowledge and skills. Of course good teachers have never waited for those “formal” opportunities to learn and grow as an educator and learner, but the opportunities we have to be self-directed in our professional development are certainly better than ever today.

Developing and sharing a vision is a critical early step for any change initiative. When your vision and themes have been shared across a district, school system, school or community, people are likely to make decisions that are aligned with your organization’s overarching goals.

A shared vision is:

• Actionable: it can be linked to specific actions that people can undertake
• Inspiring and motivating: it taps people’s sense of mission and wish to contribute
• A target, not a plan: it sets the direction, but not the details, and it is flexible
• Widely known: by all stakeholders (anyone who has a stake in the system and its activities)
• Broadly accepted: it helps pull together people of differing opinions or positions

The structure under construction is meant to foster this shared vision.  Self direction is the key concept.

The structure has some qualities of a “learning object“, and is intended to be model-centered instruction.  Model-centric designers tend to build their designs around central, interactive models of environments, cause-effect systems, and performance expertise and supplement them with focusing problems and instructional augmentations

Model-centered instruction (Gibbons, 1998; in press) is a design theory based on the following principles:

•    Experience: Learners should be given opportunity to interact with models of three types: environment, cause-effect system, and expert performance.
•    Problem solving: Interaction with models should be focused through carefully selected problems, expressed in terms of the model, with solutions being performed by the learner, by a peer, or by an expert.
•    Denaturing: Models are denatured by the medium used to express them. Designers must select the level of denaturing that matches the learner’s existing knowledge level.
•    Sequence: Problems should be arranged in a carefully constructed sequence.
•    Goal orientation: Problems should be appropriate for the attainment of specific instructional goals.
•    Resourcing: The learner should be given problem-solving information resources, materials, and tools within a solution environment.
•    Instructional augmentation: The learner should be given support during problem solving in the form of dynamic, specialized, designed instructional features.

I am reluctant to call this structure a framework.  It seems to confining and limited.  I don’t want it to be exclusively “Top Down”.  I want to allow some room for “Bottom Up’” design by the end user.

Although it may not meets all of the qualifications of a learning object, I feel best referring to it as a “Transformational Learning Object”.

I can’t quite grasp the meaning of this; Denaturing: Models are denatured by the medium used to express them. Designers must select the level of denaturing that matches the learner’s existing knowledge level.

I could use some help.

This blog is meant to chronicle and reflect upon my efforts to develop a learning object to aid in the training of persons interested in 21st century learning and performance skills.
My vehicle for doing so will be Cmap Tools.

Considering that I believe I am primarily a visual learner, it’s not be surprising to me that I am drawn to concept mapping as a powerful learning tool. It was, though useful, somewhat impractical prior to the internet. That may have changed. What is it and where did it come from?
According to Joseph D. Novak in his article, co-authored by Alberto J. Canas , “The Theory Underling Concept Maps and How to Construct and Use Them“, published by the Florida Institute for Human and Machine Cognition in Pensacola Fl, 32502 (www.ihmc.us) in 2006 and revised in 2008;

“Concept maps were developed in 1972 in the course of Novak’s research program at Cornell where he sought to follow and understand changes in children’s knowledge of science (Novak & Musonda, 1991). During the course of this study the researchers interviewed many children, and they found it difficult to identify specific changes in the children’s understanding of science concepts by examination of interview transcripts. This program was based on the learning psychology of David Ausubel (1963; 1968; Ausubel et al., 1978). The fundamental idea in Ausubel’s cognitive psychology is that learning takes place by the assimilation of new concepts and propositions into existing concept and propositional frameworks held by the learner. This knowledge structure as held by a learner is also referred to as the individual’s cognitive structure. Out of the necessity to find a better way to represent children’s conceptual understanding emerged the idea of representing children’s knowledge in the form of a concept map. Thus was born a new tool not only for use in research, but also for many other uses.”

I’ll leave it to the reader to delve deeper into the article. It’s a great read!

There seem to be three leading online concept mapping, aka “Mind Mapping” tools; Inspiration, Bubbl.us and CmapTools. At the risk of oversimplification, Bubbl.us is basic in nature and is easily learned. Inspiration and it’s little brother, Kidsperation, have more bells and whistles and are not free. CMap Tools are a high level serious tool with a somewhat steeper learning curve.

What, exactly are concept maps? Again, Novak says:

One of the powerful uses of concept maps is not only as a learning tool but also as an evaluation tool, thus encouraging students to use meaningful-mode learning patterns (Mintzes et al., 2000; Novak, 1990; Novak & Gowin, 1984). Concept maps are also effective in identifying both valid and invalid ideas held by students, and this will be discussed further in another section. They can be as effective as more time-consuming clinical interviews for identifying the relevant knowledge a learner possesses before or after instruction (Edwards & Fraser, 1983). People often confuse rote learning and meaningful learning with teaching approaches that can vary on a continuum from direct presentation of information (which may be conceptually obscure or conceptually explicit) to autonomous discovery approaches where the learner perceives the regularities and constructs her/his own concepts. Both direct presentation and discovery teaching methods can lead to highly rote or highly meaningful learning by the learner, depending on the disposition of the learner and the organization of the instructional materials. These distinctions are shown in Figure 3. There is the mistaken notion that “inquiry” studies will assure meaningful learning. The reality is that unless students possess at least a rudimentary conceptual understanding of the phenomenon they are investigating, the activity may lead to little or no gain in their relevant knowledge and may be little more than busy work. In fact, the research basis for support of widely recommended inquiry learning is largely absent (Mayer, 2004; Kirschner et al., 2006; Sweller et al., 2007).

I have worked with Bubbl.us and it is quite practical and refreshing simple; however my sandbox activities have moved on to CMaps Tools. If you would like to see more examples created and posted by Cmap, here are some examples, (some very basic and others complex):

Our Solar System | The Crow and the Pitcher | Canada’s Geography | Speech Production | Impingment Syndrome | Political | Participation & Elections | Several Chess Openings | Modal Verbs | Catechism of the Catholic Church | Centre for Teaching Excellence | Weather (incredible!) | A Book Review? | Cmaps in Schools

Note that some use only linking mechanisms and others use the resource attachments and nested Cmaps. All of these examples are located on IHMC servers and are public. They can be accessed at these servers on line.
If you have downloaded Cmaps Tools, you can collaborate with others with maps in construction. Further, you can build your own maps and when and if you wish, load them to these public sites. Is your curiosity piqued? Download from here.
View these Cmaps Tools on YouTube.
Enough for now. In future blog posts I’ll share some of my sandbox efforts with Cmaps, scaffolding and it’s theoretical constructs.

Could one build a Cmap of their course?  Are concept maps always taxonomic?