Topics
“Topics” are relatively brief writings about specific subjects. They may contain information, opinion, a list of links, or the like. More formal published works appear under Publications.
Classroom Response Systems
Collaborative Group Techniques
Constructivism
Constructivism was introduced in the modern era by Jean Piaget as a way of thinking about cognition and knowledge, not as a metaphysical theory about what might exist. It’s fundamental tenet is: The mind organizes the world by organizing itself (Piaget 1937).
The “radical” version of constructivism was developed independently by Heinz von Foerster (1981) and Ernst von Glasersfeld (1984). Knowledge, from this perspective, is not a representation of “objective” facts, but a compendium of concepts, conceptual relationships, and rules that have proven useful in domesticating our experiential world.
Foerster, H. von (1981) Observing systems. Seaside, California: Intersystems Publications.
Glasersfeld, E. von (1984) An introduction to radical constructivism, in P. Watzlawick (ed.) The invented reality. New York: Norton. German original, 1981.
Piaget, J. (1971) The construction of reality in the child; New York: Basic Books. French original, 1937.
For a great deal more about radical constructivism — both more extensive and more authoritative than we can provide here — we direct you to the extensive writings on the Radical Constructivism web site.
(The essay that follows is lacking in “scholarly” background, citations, etc. The reason is that it was pulled out of a very specific context. We present it here in the spirit of “perhaps you will find it useful.”)
Constructivism and Science Education
In what way is a constructivist view of science education different from other views? The answer lies in the tenets of constructivist philosophy, which assert that all knowledge is constructed as a result of cognitive processes within the human mind. While this may appear to be a harmless enough statement, many find (so-called) radical constructivism somewhat unpalatable.
Early PER Findings
This document is quite old (early 1990s) and mentions nothing about all the relevant research since then. It's also lacking references. Caveat emptor.
The areas of cognitive research we will focus on are: (1) the prevalence and virulence of misconceptions; (2) the differences between the ways that experts and novices store domain-specific knowledge and solve problems; (3) the importance of goal-free activities; and (4) the effects of "meta-communicating" with students about the learning process. Each area has critically affected the development of our approach, and therefore, each area is reviewed to help you understand the construction of our materials and how they should be implemented.
Knowledge Structure
Extracted from a booklet accompanying a workshop for high school science teachers.
Neural Networks
Neural network (NN) modeling has developed as a major component of science’s attempt to understand the brain. The fundamental question is, how do the brain’s formidable information-processing abilities emerge from the self-organizing behavior of a collection of relatively simple neurons? NN modelers aspire to develop artificial systems with some brain-like abilities. Much of the progress in NN modeling has been made by physicists, who have extensive experience formulating and analyzing complicated mathematical models [1-4].
Physics Education Research
Question Driven Instruction
TEFA
Transfer of Learning
Transfer of learning is among the most important problems in education today. Students, especially in science, are all too often unable to apply what they learn to novel contexts both in, and outside the classroom. Making headway on the transfer problem is important since all of education is predicated on the premise that what is taught in one course will be used in relevant situations in other courses, as well as out of school and in the workplace. Research suggests, however, that lack of transfer is pervasive and persistent, and that promoting more transfer is a difficult enterprise given the complexity of factors that affect it.
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