Neural Dynamic Model for Optimization of Complex Systems

Out of all the complex systems in science education curricula, cellular respiration is considered to be one of the most complex and abstract processes. Students are known to have low interest and difficulties in conceptual understanding of cellular respiration which provides a challenge for teaching and learning. In this study, we took literature about modelling and teaching and learning cellular respiration as a starting point for the design of a concrete dynamic model in which students (n = 126) use Lego® to simulate the process of cellular respiration. Students used the simulation embedded in the context of finding the efficiency of a sediment battery as a future source of green energy and we tested the effects on conceptual learning and situational interest in an experimental study. Results on conceptual learning show that both experimental and control groups had comparable results in the test. The questions that students in the experimental group asked during enactment, however, gave notice of a focus on both isolated component parts as well as modes of organization at higher organizational levels which is linked to how biologists mechanistically understand complex systems. Both groups report a similar high measure to which the topic is meaningful in real life (situational interest value), whereas the enjoyment (situational interest feeling) was significantly increased in the experimental group. Furthermore, students report specific advantages (e.g., I now understand that one acid chemically changes into another and they do not just transfer atoms) and disadvantages (e.g., time issues).

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Applying a Dynamic Model of Situated Cognition to the Investigation of Mishaps

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/154193120504900302 ◽

2005 ◽

Vol 49 (3) ◽

pp. 219-223 ◽

Cited By ~ 4

Author(s):

Nita Lewis Miller ◽

Lawrence G. Shattuck

Keyword(s):

Complex Systems ◽

Dynamic Model ◽

Human Error ◽

Situated Cognition ◽

Organizational Factors ◽

Operator Error ◽

Military Command ◽

And Control ◽

Analysis Of Error ◽

The U.S

Complex systems will, inevitably, experience failures. The cause of these failures or mishaps may be labeled 'operator error,' but often they are actually caused by the confluence of technological, situational, individual, and organizational factors. Several models and theories of human error have been proposed over the years and are reviewed in this paper. The authors propose another model, the Dynamic Model of Situated Cognition (DMSC), to explain how complex systems fail. Miller and Shattuck (2004) developed the DMSC in an effort to link technological aspects of a system to the perceptual and cognitive aspects of that system. They illustrated the model by applying it to the USS Stark incident and to a military command and control simulation (Shattuck and Miller, 2004). The model also appears to have utility as a retrospective explanatory tool to identify when and where things went wrong. In this paper, the authors describe the DMSC as it relates to the analysis of error in complex systems and apply it to the February 2001 mishap in which the U.S. Navy submarine USS Greeneville collided with the Japanese motor vessel Ehime Maru off the coast of Oahu, Hawaii.

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