- Sep 2023
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www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
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Recent work has revealed several new and significant aspects of the dynamics of theory change. First, statistical information, information about the probabilistic contingencies between events, plays a particularly important role in theory-formation both in science and in childhood. In the last fifteen years we’ve discovered the power of early statistical learning.
The data of the past is congruent with the current psychological trends that face the education system of today. Developmentalists have charted how children construct and revise intuitive theories. In turn, a variety of theories have developed because of the greater use of statistical information that supports probabilistic contingencies that help to better inform us of causal models and their distinctive cognitive functions. These studies investigate the physical, psychological, and social domains. In the case of intuitive psychology, or "theory of mind," developmentalism has traced a progression from an early understanding of emotion and action to an understanding of intentions and simple aspects of perception, to an understanding of knowledge vs. ignorance, and finally to a representational and then an interpretive theory of mind.
The mechanisms by which life evolved—from chemical beginnings to cognizing human beings—are central to understanding the psychological basis of learning. We are the product of an evolutionary process and it is the mechanisms inherent in this process that offer the most probable explanations to how we think and learn.
Bada, & Olusegun, S. (2015). Constructivism Learning Theory : A Paradigm for Teaching and Learning.
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- May 2022
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Local file Local file
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Active reading to the extreme!
What a clever innovation building on the ideas of the art of memory and Raymond Llull's combinatoric arts!
Does this hit all of the areas of Bloom's Taxonomy? I suspect that it does.
How could it be tied more directly into an active reading, annotating, and note taking practice?
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- Jul 2019
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www.tonybates.ca www.tonybates.ca
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Communities of practice are one of the ways in which experiential learning, social constructivism, and connectivism can be combined, illustrating the limitations of trying to rigidly classify learning theories. Practice tends to be more complex.
Constructivism - roots in the philosophical and psychological viewpoints of this century, specially Piaget, Bruner and Goodman. Learning occurs when the mind filters inputs from the world to produce its unique reality. The mind is believed to be the source of all meaning, direct experiences with the environment are considered critical. It crosses both categories by emphasizing the interaction between learner and the real world.
Social constructivism would emphasize critical experiences between the learner and other learners and mentors.
Connectivism is the integration of principles explored by chaos, network, complexity and self-organization theory. A lot of the content is now offloaded to the machine that was previously residing within the learner.
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- Mar 2019
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faculty.coe.uh.edu faculty.coe.uh.edu
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Edward Thorndike's three laws of learning. The page does not explain this, but his theories came out in about 1900. His three laws of learning appear to be relevant to our course work. This simple page features black text on a white page. It is brief and it simply describes the three laws of learning. rating 5/5
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www.instructionaldesign.org www.instructionaldesign.org
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This page is a simply presented list of many learning theories, both popular and less well known. The layout is clean. The pages to which the listed items link are somewhat minimal in nature so this would give a basic tour or overview of the models and would allow viewers to review the names of some of the learning theories. This page does not prioritize learning theories or identify and establish those theories that are the most prominent.
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- Jul 2018
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aeon.co aeon.co
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However, computers and algorithms – even the most sophisticated ones – cannot address the fallacy of obviousness. Put differently, they can never know what might be relevant.
One goal of systems science and modelling, to explore what might be relevant and give us better heuristics.
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