Difference between revisions of "Robustness"

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[[Category:PSLC General]]
 
[[Category:PSLC General]]
  
Robust learning is learning the achieves either or both deep conceptual understanding and strong procedural fluency.  Sometimes instructional objectives of a course may put more emphasis on one or the other, but often both are desirable.  Robust learning is measured with assessments of [[long-term retention]], [[transfer]] and [[accelerated of future learning]].
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Robust learning is learning the achieves either or both deep conceptual understanding and strong procedural fluency.  Sometimes instructional objectives of a course may put more emphasis on one or the other, but often both are desirable.  Robust learning is measured with assessments of [[long-term retention]], [[transfer]] and [[accelerated future learning]].
  
 
Instruction that achieves robust learning is designed so that the [[learning event space]] has some target paths that would cause an ideal student to acquire [[knowledge components]] that have either or both high [[feature validity]], that is, they are accurate, deep, and general, and high [[strength]], that is, they can be applied quickly and effortlessly.
 
Instruction that achieves robust learning is designed so that the [[learning event space]] has some target paths that would cause an ideal student to acquire [[knowledge components]] that have either or both high [[feature validity]], that is, they are accurate, deep, and general, and high [[strength]], that is, they can be applied quickly and effortlessly.

Revision as of 14:30, 28 December 2006


Robust learning is learning the achieves either or both deep conceptual understanding and strong procedural fluency. Sometimes instructional objectives of a course may put more emphasis on one or the other, but often both are desirable. Robust learning is measured with assessments of long-term retention, transfer and accelerated future learning.

Instruction that achieves robust learning is designed so that the learning event space has some target paths that would cause an ideal student to acquire knowledge components that have either or both high feature validity, that is, they are accurate, deep, and general, and high strength, that is, they can be applied quickly and effortlessly.