The Perfect Theory

Snelbecker also tackles design theories but not by contrasting them with learning theories like Reigeluth; instead, Snelbecker contrasts design theories from theoretical and practitioner points of view. The former is designed not to yield rules of practice but to help practitioners “design conditions that facilitate learning.” As such, theories, while closely related to practice (as opposed to learning theories), are indirect.

Theories, designed by Snelbecker’s knowledge producers, are expected to provide definitive answers by knowledge users (instructors and designers); however, because theorists exercise caution in drawing conclusions, theories seldom satisfy users who need immediate answers. I particularly appreciated the perspective that theorists view their work as progress reports designed to help users “consider the merits of alternative approaches.”

The irony is that while theorists do not want practitioners to consider their work as final answers, these same producers adopt dogmatic stances regarding their personal theory. Snelbecker’s solution involves posing three questions to the theorists:

1. Is any theory perfect?
2. Does any theory include everything?
3. Should any theory be the only theory?

After answering, “No” to each of these questions, Snelbecker concludes by recommending that theories identify the added value they provide to our understanding of how instruction can be designed.

Symbolic learning & the grounding problem

Citation

Harnad, S. “The Symbol Grounding Problem.” Physica D 42 (1990). 335-346.

Summary

In a short paper, the authors attempt to define symbolism as a cognitive science but find that the theory fails due to the symbol grounding problem: that symbols are composed only of other symbols and thus self-referential.

They define 6 basic learning behaviors:

1. discriminate
2. manipulate
3. identify
4. describe
5. produce descriptions
6. respond to descriptions

which cognitive theory must explain. Examining the first and third behaviors, the authors propose a dual representation: iconic (symbol) and categorical (internal analog transforms). However, they admit one “prominent gap:” no mechanism to explain categorical  representations. The authors thus dismiss symbolism as a sole solution and turn to connectionism as a hybrid solution: “an intrisically dedicated symbol system…connected to nonsymbolic representations…via connectionist networks that extract the nonvariant features.”

Response

The authors likely succeed for theorists but this was a little dense given my lack of background. I think I got the idea that a symbol (for example, a swastika) exists by itself and combined with “rules” (our prior learning and knowledge that the symbol has a recent association with the Nazi Party) to produce a composite symbol (loathing). I also took away that humans, especially in groups, are too complex to be semantically interpretable, and that connectionism (based not on symbols but on pattern activity in a multilayered network) may offer some answers.

The dual representation–iconic (symbol) and categorical (internal analog transforms)–seem to suggest a symbol paired with a real-world (our experience with/background on/knowledge of) event; however, the authors later define that as an interpretation. In addition, I’m not certain why the iconic representation is not symbolic as the authors state.

The conclusion makes sense (although this is classic Vygotsky–and connectionism seems like just another word for community): if a category is defined as a symbol (image) plus our experience with that symbol, I started to believe that all our knowledge is interconnected (within a single human) with past experiences–and agree that it may not be possible to model learning in a purely symbolic (i.e., no connection to the real world) fashion.

YAM (Yet Another Map)

Learning theory mapped to ID model