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Learning/Cognitive Sciences

A short list of driving forces that led to design's emergence into today's educational scene could include:
(a) Intuitive, visionary teachers who saw the value of these tasks to motivate students, give them meaningful contexts for learning while solving complex "real world" challenges.
(b) Research findings from the Learning and Cognitive Sciences that pointed to their potential value. A useful reference that summarizes these fields is the National Research Council's How People Learn, a must-have handbook for doing "informed teaching" with design tasks.

This section of DITC presents findings from the Learning and Cognitive Sciences that are relevant to design-based learning. They amount to a compelling set of cases that can come in handy in your day-to-day teaching:

  •  Case-Based Reasoning  Georgia Tech's Janet Kolodner talks about an innovative approach that she developed for machine learning based on providing them cases or examples from to learn, and how she then applied similar lessons to the LBD curriculum she created.
  •  Problem Finding/Solving  Solving problems has been well studied and involves topic-specific strategies. Such tasks usually state what needs to be solved: most have single correct answers. Open-ended design tasks often do not tell you what to solve or how -- the problem needs to be found before it solved.
  •  Surface/Deep Categories  Novice versus expert physicists categorized end-of-chapter problems differently. Novices notice surface features about problems, while the experts grouped them by deeper features.
  •  Memorizing/Understanding  More complex performances, like design, require require a flexible understanding of what is known to so that it can be adapted to new situations. Five features for developing students understanding are described here.
  •  Near/Far Transfer  Being able to take something learned and apply it to a new situation is the hallmark of learning. How similar the new situation is to the original setting and task determines if the application of learning involves "near transfer" or "far transfer".
  •  Short/Long-Term Memory  Some of cognitive science's most enduring findings revolve around limits of what we can keep in mind in the short-term, and what we can remember and recall in the long-term. Learn about the rule-of-thumb called the "magic number 7, plus or minus 2" and other findings regarding memory.
  •  Primacy/Recency Effect  The first and last things learned are often the best remembered items.
  •  Novice/Expert Studies  One mainstay of early Cognitive Science work was its study of expertises like chess and medical decision-making. Comparisons of novice versus expert thinking and performance were used to describe preferred outcomes for learners.
  •  Scaffolding  Giving support to enable people to perform accurately and optimally.
  •  Elaboration & Learning  One of the surprising, non-intuitive findings from Cognitive Science is that just interacting mentally with a topic, whether it makes sense or not, can lead to improved connection-making and learning.
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