Archive for July, 1996

24 Jul

The Role of Student Tasks in Accessing Cognitive Media Types

Posted by cognitivecomputing in Education. Tagged: , , .

We believe that identifying media by their cognitive roles (e.g., definition, explanation, pseudo-code, visualization) can improve comprehension and usability in hypermedia systems designed for learning. We refer to media links organized around their cognitive role as cognitive media types (Recker, Ram, Shikano, Li, & Stasko, 1995). Our hypothesis is that the goals that students bring to the learning task will affect how they will use the hypermedia support system (Ram & Leake, 1995).

We explored student use of a hypermedia system based on cognitive media types where students performed different orienting tasks: undirected, browsing in order to answer specific questions, problem-solving, and problem-solving with prompted self-explanations. We found significant differences in use behavior between problem-solving and browsing students, though no learning differences.

Read the paper:

The Role of Student Tasks in Accessing Cognitive Media Types

by Mike Byrne, Mark Guzdial, Preetha Ram, Rich Catrambone, Ashwin Ram, John Stasko, Gordon Shippey, Florian Albrecht

Second International Conference on the Learning Sciences (ICLS-96), Evanson, IL, July 1996
www.cc.gatech.edu/faculty/ashwin/papers/er-96-03.pdf

24 Jul

Exploring Interface Options in Multimedia Educational Environments

Posted by cognitivecomputing in Education. Tagged: , .

Multimedia technology presents several options to the developers of computer-based learning environments. For instance, it is common to organize information by its physical characteristics. However, organizize information based on how users understand the material might improve comprehension. This theory of cognitive media – media organized by cognitive characteristics – was examined in studies using the AlgoNet system, a multimedia learning environment (Recker, Ram, Shikano, Li, & Stasko, 1995). To explore several interface options, AlgoNet2, a second version of AlgoNet, was created with the same domain information, but several new interface concepts. Students in an introductory programming class used AlgoNet2 to solve a problem involving graph theory. Students’ performance and comments suggest that many students lack effective learning strategies and those that do employ effective learning strategies are unaware of them.

Read the paper:

Exploring Interface Options in Multimedia Educational Environments

by Gordon Shippey, Ashwin Ram, Florian Albrecht, Janis Roberts, Mark Guzdial, Rich Catrambone, Mike Byrne, John Stasko

Second International Conference on the Learning Sciences (ICLS-96), Evanson, IL, July 1996
www.cc.gatech.edu/faculty/ashwin/papers/er-96-02.pdf

13 Jul

The Role of Ontology in Creative Understanding

Posted by cognitivecomputing in Language. Tagged: , , , .

Successful creative understanding requires that a reasoner be able to manipulate known concepts in order to understand novel ones. A major problem arises, however, when one considers exactly how these manipulations are to be bounded. If a bound is imposed which is too loose, the reasoner is likely to create bizarre understandings rather than useful creative ones. On the other hand, if the bound is too tight, the reasoner will not have the flexibility needed to deal with a wide range of creative understanding experiences. Our approach is to make use of a principled ontology as one source of reasonable bounding. This allows our creative understanding theory to have good explanatory power about the process while allowing the computer implementation of the theory (the ISAAC system) to be flexible without being bizarre in the task domain of reading science fiction short stories.

Read the paper:

The Role of Ontology in Creative Understanding

by Kenneth Moorman, Ashwin Ram

18th Annual Conference of the Cognitive Science Society (CogSci-96), San Diego, CA, July 1996
www.cc.gatech.edu/faculty/ashwin/papers/er-96-01.pdf

3 Jul

Dynamically Adjusting Concepts to Accommodate Changing Contexts

Posted by cognitivecomputing in Learning.

In concept learning, objects in a domain are grouped together based on similarity as determined by the attributes used to describe them. Existing concept learners require that this set of attributes be known in advance and presented in entirety before learning begins. Additionally, most systems do not possess mechanisms for altering the attribute set after concepts have been learned. Consequently, a veridical attribute set relevant to the task for which the concepts are to be used must be supplied at the onset of learning, and in turn, the usefulness of the concepts is limited to the task for which the attributes were originally selected.

In order to efficiently accommodate changing contexts, a concept learner must be able to alter the set of descriptors without discarding its prior knowledge of the domain. We introduce the notion of attribute-incrementation, the dynamic modification of the attribute set used to describe instances in a problem domain. We have implemented the capability in a concept learning system that has been evaluated along several dimensions using an existing concept formation system for comparison.

Read the paper:

Dynamically Adjusting Concepts to Accommodate Changing Contexts

by Mark Devaney, Ashwin Ram

ICML-96 Workshop on Learning in Context Sensitive Domains, Bari, Italy, July 1996
www.cc.gatech.edu/faculty/ashwin/papers/er-96-07.pdf