Skills and Competencies as Representable Meta-knowledge for Tele-learning Design by Gilbert Paquette cirta-licef research Center



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2.2 Representation of meta-knowledge


Every domain such as physics, sociology or law is made of knowledge and facts. The domain that studies knowledge per se is particularly important for learning. Knowledge from this domain will be called meta-knowledge or generic knowledge. Since meta-knowledge is also knowledge (about knowledge), we can also distinguish between three categories of abstract meta-knowledge and their corresponding meta-facts, as we do for knowledge.

  • Meta-concepts represent knowledge attributes. They are concepts that define value systems to apply to knowledge from various domains.

For instance, when one claims that some knowledge in physics or economics is a priority, is valid or is useful, he uses a concept of priority, validity or usefulness that does not belong to physics nor economics, but to the domain that studies knowledge. Instanciating such a meta-concept to knowledge in an application domain results in the assignment of a meta-value to the knowledge we want to talk about. As a result, we get meta-examples in various domains such as: « the concept of atom is essential », « the  break-even point calculation procedure is useful in micro-economics » .

  • Meta-procedures are operations on knowledge. They are actions on knowledge or facts in various domains where they are applied.

Classification, defined as a set of operations to determine the smallest class of a taxonomy to which a particular object belongs, is an example of a meta-procedure. It is composed of operations intended to determine of what class the object is an example; we first consider the first-level in the taxonomy, then we examine the second-level sub-classes and so on, up to the terminal classes of the taxonomy. To instanciate such a meta-procedure consists in choosing the taxonomy and the object we want to classify within the taxonomy, for example, a taxonomy of vertebrates and a bat, or a taxonomy of professions and a given individual. The result is a meta-trace of specific operations in the application domain: « the bat satisfies the definition of vertebrate, of mammal, of cheiropter » or « the individual satisfies the definition of the members of a liberal profession, of law professionals, of lawers ».

  • Meta-principles are generic statements that apply to various domains aiming to control the use of other meta-knowledge objects or to establish relations between them. Depending if they are action or relational principles, they can be described as « knowledge control principles » or « knowledge association principles ».

One example is the following principle: “ to solve a complex problem, first solve a particular case of it”. Instanciating such a meta-principle is in fact choosing knowledge, here a problem, to which the meta-principle will be applied. Results are meta-statements like « to build a general procedure for compound interest calculation, first solve the problem using an interest rate of 10% », or « To diagnose a car breakdown, first diagnose the state of the electrical system ».

F
igure 2 shows how we assign a generic process (a skill) such as simulation to a search procedure in the Internet domain, using an A link from the generic process, instanciated in the Internet application domain, to a procedure in this domain. We also use another A link to assign a meta-value to a knowledge, tagging it as very important knowledge.

Figure 2 – A simulation meta-process applied (link A) to the Internet domain.

In the application domain of figure 2, the main knowledge unit is a procedure. It defines the main purpose of a possible learning unit “Search for information on the Internet”. This procedure is decomposed into sub-procedures using C links. One of them is “Execute the request”: it has a “Request” concept as input and produces (through an I/P link) a list of “Interesting Web sites”. These are in turn used as inputs to another sub-procedure, “Identify interesting information”, which precedes the final procedure: “Transfer information in a text editor”. The “Refine the request” sub-procedure is regulated (R link) by principles helping a user to refine a request.

The application (A) link on the main procedure shows that the learner will have to apply a generic skill: «Simulate a process» to the Internet domain. Figure 3 describes a graphic model for that meta-knowledge. The MOT graph provides a precise definition of the “Simulate a process” skill, adding to it more details such as inputs and outputs of sub-processes. If needed, we could add more details to the model by adding some of the control principles that heuristically could help achieve the generic task. The principles would have to be stated in sub-models of the process. Also, procedures and concepts in the model could be described with more detail.

N
otice that the instance “Simulate a process in the Internet domain” appears on both figures, linking the two models by a co-reference link (a meta-link embedded in the MOT system). On figure 2 it is a meta-fact from the a viewpoint in the Internet domain because it is defined in a meta-knowledge domain. On figure 3, it is shown as an instance (a trace) of the meta-process “Simulate a process” which gives a precise and inspectable definition of the skill.

Figure 3 – Graph of a meta-process: “Simulate a process”5

3. An integrated taxonomy of skills


We will now use the knowledge representation technique just outlined to define an integrated taxonomy of skills. We first present a comparison between the taxonomies presented in section one and then discuss the properties of this taxonomy.

3.1 A general to specific taxonomy


We have built a taxonomy of meta-processes representing skills, as well as problems and tasks, for our learning system engineering method MISA [Paquette 1999]. Table 3 presents the first three layers of this taxonomy and compares it to the taxonomies presented in section 1. Although these taxonomies have different purposes and terminologies, they roughly correspond.

A first layer of skills (or meta-processes) in our taxonomy corresponds to four general processes generally agreed upon as representing basic information processing phases. The second layer includes ten generic processes that can be ordered from simple to complex, as we will see later on. Third layer skills correspond to more specialized skills that are widely used in instructional design.



We can of course extend this specialization hierarchy to more layers. From layer to layer, we get more and mode specialized skills until every aspect of a skill is totally instanciated in a particular application domain such as in the following chain, from general to specific: Reproduce – Analyze – Diagnose – Diagnose a health problem – Diagnose a heart problem in a child.

Skills taxonomy layers

Active meta-knowledge

(Pitrat


Generic problems

(KADS)

Cognitive objectives

(Bloom)

Skills cycle

(Romiszowski)

1

2

3

Reception

1- Pay Attention










Attention, Perceptual acuity, Perceptual discrimination

2- Integrate

2.1 Identify

2.2 Memorize







Memorize

Reproduction

3- Instantiate/

Specify

3.1 Illustrate

3.2 Discriminate

3.3 Explicitate

Knowledge search and storage




Under­stand

Interpretation

4- Transpose/ Translate










Recall procedures Recall schemata

5- Apply

5.1 Use

5.2 Simulate

Knowledge use, Knowledge expression




Apply

Creation

6- Analyze

6.1 Deduce

6.2 Classify

6.3 Predict

6.4 Diagnose

Knowledge discovery

Prediction, Supervision, Classification, Diagnosis

Analyze

Restructure

Generate alternatives



7- Repair

Repair




8- Synthesize

8.1 Induce

8.2 Plan

8.3 Model/ Construct

Planning, Design, Modeling

Synthesize

Self-management

9- Evaluate

Knowledge acquisition




Evaluate

Think of implications, act on a decision, see through the action, self- correct

10-

Self- manage

10.1 Influence

10.2 Self-control










Table 3 - Comparative multi-layered taxonomy of skills, problems and metaknowledge

According to this taxonomy, “5.2 - Simulate a process”, a skill used in the example on figure 2 and 3, is a specialization of the “Apply” skill. Each of the skills in this taxonomy is described very precisely by its inputs and its products and by a detailed generic process similar to figure 3 showing how the inputs are transformed into specific products. The “Simulate a process” skill is compared below to the “8.3 Construct a process” skill which is a specialization of the second layer “Synthesize” skill.



Skill

Input

Product

Generic process

Simulate a process

A process, its procedures, inputs, products and control principles.


A trace of the procedure: set of facts obtained through the application of the procedures in a particular case

-Choose input objects

-Select the first procedure to execute

-Execute it and produce a first result

-Select a next procedure and execute it

-Use the control principles to control the flow of execution


Construct a process

Definition constraints to be satisfied such as certain inputs, products and/or steps

A description of the process: its inputs, products, sub-procedures with their input and output, and control principles.

-Give a name to the procedure to be constructed

-Relate it to specified input and product

-Decompose the procedure

-Continue to a point where well understood steps are attained.



Table 4 – Examples of two skills as meta-processes

From the description of the two generic skills on table 4, we can see that a pedagogical scenario on the same subject of “Information search on the Internet” but with a different skill objective such as “Construct a process” would be very different from the one based on the “Simulate a process” skill. In the first case, a kind of walk-through of the process is sufficient, while in the second case, we could need a project-based scenario where learners and engaged in a more complex problem-solving activity.


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