Rope-weaver’s principles: Towards more effective learning.
Aylward, R.C. ; Van Wyk, B. J. ; Hamam, Y.
Aylward, R.C.
Van Wyk, B. J.
Hamam, Y.
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Abstract
This paper introduces a new methodology to assist teaching and learning in a time-constrained environment at the hand of two time-on-task examples. These examples are from
the field of Electrical Engineering studies with a focus on first-year studies and an advanced software design course taught at the Tshwane University of Technology in South Africa. In an
endeavour to understand the timing model of the human brain to master and assimilate new information, a study was conducted to determine some of the parameters that could possibly have an influence on the timing model and how the brain perceives new information. From this study the Rope-Weaver’s Principles were derived and are built on three well-known theories, comparative judgment, the Guttman scale and the learning curve, integrated into the new methodology. The Rope-Weaver’s Principles are presented as an abstraction of the mathematical principles and the measures that underpin this study. The research was done from a participant-observer perspective with design research as central methodology. The research methodology involved a longitudinal study employing mixed-methods research. The results led to the observation of a toe or plateau in the infancy of the learning curve. The observed plateau has a direct influence on the order and time frame of the introduction of new study material in a formal educational programme. The results were found to adhere to the Weber-Fechner Law. This relates to other studies on animals, suggesting that the way the brain perceives stimuli or assimilate knowledge is hard-wired throughout the animal kingdom although the brain structures vary widely. It is proposed that Rope-Weaver’s Principles, complementary to the current pool of teaching and learning theories, lead to a better
mastery of the learning material or skills, moving persons under instruction from rule-based training – behaviourism, to maxim integration – constructivism.
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Date
2019-12-10
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Publisher
Institute of Electrical and Electronics Engineers (IEEE)
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Keywords
Analytic hierarchy network, Engineering education, Failure modeling, Just noticeable difference, Learning curves, Learning strategies.