Notes

Not going to repeat anything that was mentioned in Suthers, 2008Suthers, D. D. (2008). Empirical studies of the value of conceptually explicit notations in collaborative learning. In A. Okada, S. Buckingham Shum & T. Sherborne (Eds.), Knowledge Cartography (1--23). Springer..

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Research into the cognitive and social aspects of learning has developed a clear picture of the utility of external representations in supporting learners’ active expression, examination, and manipulation of their own knowledge

• [Koedinger 1991], [Novak 1990], [Reusser 1993], [Scardamalia et al. 1992], [Snir et al. 1995])

Representational tools are software interfaces in which users construct, examine, and manipulate external representations of their knowledge.

They range from basic data manipulation and office tools such as spreadsheets and outliners to knowledge mapping software and enhanced modeling and simulation tools.

It is a software implementation of a representational notation that provides a set primitive elements out of which representations can be constructed.

The software developer chooses the representational notation. These primitive elements constitute an ontology of categories and structures for organizing the task domain.

Learners will see their task in part as one of making acceptable representational artifacts out of these primitives. Thus, they will search for possible new instances of the primitive elements, and hence (according to this hypothesis) will be guided to think about the task domain in terms of the underlying ontology.

The programmer instantiates it as a representational tool, while the user of the tool constructs particular representational artifacts in the tool.

notation/artefact distinction is crucial (Stenning & Yule 1997)

Such tools can help learners see patterns, express abstractions in concrete form, and discover new relationships.

Ideally, they function as cognitive tools that lead learners into knowledge-building interactions [Collins and Ferguson 1993], [Lajoie and Derry 1993]

• symbolic (this work)
• analogical

(Stenning & Yule 1997)

• [Guzdial 1997], who undertook a comparison of two forms of threaded discussion.

Not “which representation is better?” but rather “what kinds of interactions, and therefore learning, does each representational notation encourage?”

Representational tools mediate collaborative learning interactions by providing learners with the means to express their emerging knowledge in a persistent medium, inspectable by all participants, where the knowledge then becomes part of the shared context.

Representational guidance constrains which knowledge can be expressed in the shared context, and makes some of that knowledge more salient and hence a likely topic of discussion.

The concept of representational guidance is borrowed from artificial intelligence, where it is called representational bias [Utgoff 1986].

Guidance - to avoid negative connotation of bias.

Refers generically to aspects of one's knowledge that one might wish to represent, such as hypotheses, statements of fact, concepts, relationships, rules, etc.

(Does not imply that this is how we think, but rather that this is how we represent our knowledge to others)

Distinguish cognitive and perceptual operators in reasoning with representations (Zhang 1997).

Cognitive operations operate on internal representations, while perceptual operations operate on external representations. Takes place without an internal copy being made of the representation (although internal representation may change as result of these operations).

Distinguish contraints inherent in logical properties of representational notation from constraints arising from architecture of the agent using the representational notation.

Constraints are logical and semantic features of the representational notation.

Salience depends on perceptual architecture of agent. Difference in salience level - Zhang's distinction between obtaining information by “direct perception” versus application of perceptual operators. Information that is recoverable from a representation is salient to the extent to which it is recoverable by automatic perceptual processing rather than through a controlled sequence of perceptual operators.

The visual presence of the knowledge unit in the shared representational context serves as a reminder of its existence and any work that may need to be done with it.

It is easier to refer to a knowledge unit that has a visual manifestation, so learners will find it easier to express their subsequent thoughts about this unit than about those that require complex verbal descriptions [Clark and Brennan 1991].

These claims apply to any visually shared representations. However, to the extent that two representational notations differ in kinds of knowledge units they make salient, these functions of reminding and ease of reference will encourage elaboration on different kinds of knowledge units.

The ability to facilitate learners’ elaboration is important because substantial psychological research shows that elaboration leads to positive learning outcomes, including memory for the knowledge unit and understanding of its significance (e.g., [Chi et al. 1989], [Craik and Lockhart 1972], [Stein and Bransford 1979])

“Direct perception” requires computation, but automatic, requiring no executive control (Triesman & Souther 1987). Recovery of certain information from a representation may require controlled application of multiple direct perceptions… In a graph, perception of color is more direct, than perception of whether node is connected to another node (Lohse 1997). Visual search required for 2.

• the kind of external representation used to depict a problem may determine the ease with which the problem is solved [Kotovsky and Simon 1990], [Larkin and Simon 1987], [Novick and Hmelo 1994], [Zhang 1997]
• the constraints built into representations may restrict the problem solver’s search space, to the possible detriment or enhancement of problem-solving success [Amarel 1968], [Hayes 1989], [Klahr and Robinson 1981], [Stenning and Oberlander 1995].

Interaction of cognitive processes of several agents are different from individual agent [Okada and Simon 1997], [Perkins 1993], [Salomon 1993].

Learners may see their task as one of putting knowledge units “in their place” in the representational environment.