Insight diagram
Crea un Bucle de Realimentación Negativa, modelando el llenado de un vaso con agua. Esta versión incluye el concepto de manejo de tabla o no liberalidad.
Universidad del Cauca. 
Profesor: Miguel Angel Niño Zambrano
curso: Enlace Curso en Moodle
Videos ejemplos: Enlace a la lista de videos del curso youtube
Clone of Ejemplo 1 v2: Llenar vaso con agua - BRN
Insight diagram
Crea un Bucle de Realimentación Negativa, modelando el llenado de un vaso con agua. Esta versión incluye el concepto de manejo de tabla o no liberalidad.
Universidad del Cauca. 
Profesor: Miguel Angel Niño Zambrano
curso: Enlace Curso en Moodle
Videos ejemplos: Enlace a la lista de videos del curso youtube
Clone of Ejemplo 1 v2: Llenar vaso con agua - BRN
Insight diagram
This version 8B of the CAPABILITY DEMONSTRATION model. A net Benefit ROI has been added. The Compare results feature allows comparison of alternative intervention portfolios.  Note that the net causal interactions have been effectively captured in a very scoped and/or simplified format.  Relative magnitudes and durations of impact remain in need of further data & adjustment (calibration). In the interests of maintaining steady progress and respecting budget & time constraints, significant simplifying assumptions have been made: assumptions that mitigate both completeness & accuracy of the outputs.  This model meets the criteria for a Capability demonstration model, but should not be taken as complete or realistic in terms of specific magnitudes of effect or sufficient build out of causal dynamics.  Rather, the model demonstrates the interplay of a minimum set of causal forces on a net student progress construct -- as informed and extrapolated from the non-causal research literature.
Provided further interest and funding, this  basic capability model may further developed and built out to: higher provenance levels -- coupled with increased factorization, rigorous causal inclusion and improved parameterization.
Version 8B: Calibrated Student-Home-Teachers-Classroom-LEA-Spending
Insight diagram
Clone of Mobility_JV1
Insight diagram
Clone of How many jobless graduates in the UK future scenarios
Insight diagram

Perceptual Control Theory Model of Balancing an Inverted Pendulum. See Kennaway's slides on Robotics. as well as PCT example WIP notes. Compare with IM-1831 from Z209 from Hartmut Bossel's System Zoo 1 p112-118

Balancing an Inverted Pendulum PCT Model
Insight diagram
Clone of Mobility_JV1
Insight diagram
From HBR study, 2014; combined with Solow Growth Model, explains why business seeks technological solutions.  Yet this is not sustainable, as there is a limit to the number of STEM-trained individuals to create technological solutions.
BridgingTheGap
Insight diagram

​Predator-prey models are the building masses of the bio-and environments as bio masses are become out of their asset masses. Species contend, advance and scatter essentially to look for assets to support their battle for their very presence. This model is designed to represent the moose and wolf population on Isle Royal. The variables include moose population, wolf population, moose birth rate, wolf birth rate, moose death proportionality constant, and wolf death proportionality constant. This model was adapted from https://insightmaker.com/insight/3A0dqQnXXh8zxWJtkwwAH9/Lotka-Volterra-Model-Prey-Predator-Simulation.

 Looking at Lotka-Volterra Model:

The well known Italian mathematician Vito Volterra proposed a differential condition model to clarify the watched increment in predator fish in the Adriatic Sea during World War I. Simultaneously in the United States, the conditions contemplated by Volterra were determined freely by Alfred Lotka (1925) to portray a theoretical synthetic response wherein the concoction fixations waver. The Lotka-Volterra model is the least complex model of predator-prey communications. It depends on direct per capita development rates, which are composed as f=b−py and g=rx−d. 

A detailed explanation of the parameters:

  • The parameter b is the development rate of species x (the prey) without communication with species y (the predators). Prey numbers are reduced by these collaborations: The per capita development rate diminishes (here directly) with expanding y, conceivably getting to be negative. 
  • The parameter p estimates the effect of predation on x˙/x. 
  • The parameter d is the death rate of species y without connection with species x. 
  • The term rx means the net rate of development of the predator population in light of the size of the prey population.

Reference:

http://www.scholarpedia.org/article/Predator-prey_model

https://insightmaker.com/insight/3A0dqQnXXh8zxWJtkwwAH9/Lotka-Volterra-Model-Prey-Predator-Simulation

Lotka-Volterra Model: Moose-Wolf Simulation
Insight diagram
How education causes the gap between socio-economic status?
Educación_universidad
Insight diagram
moderación del proceso de aprendizaje, desde la perspectiva social constructivista de Vigotsky
Clone of Proceso de aprendizaje vigotsky
Insight diagram
Model shows the U.S. Education System
U.S. Education
Insight diagram
Crea un Bucle de Realimentación Negativa, modelando el llenado de un vaso con agua. Esta versión incluye el concepto de manejo de tabla o no liberalidad.
Universidad del Cauca. 
Profesor: Miguel Angel Niño Zambrano
curso: Enlace Curso en Moodle
Videos ejemplos: Enlace a la lista de videos del curso youtube
Clone of Ejemplo 1 v2: Llenar vaso con agua - BRN
Insight diagram
 The lack of recognition of efforts is a plague of society, an immense amount of effort goes unrecognized. Meaning there is constant input on behalf of an individual with a varying degree of output. This is a highly concerning situation for the system as a whole. For a positive feedback loop to take place, inputs must balance with outputs, respectively. 

In this model, inputs balance with outputs creating a dynamic contribution.

Information Distribution Problem
Insight diagram
This version of the CAPABILITY DEMONSTRATION model has been further calibrated (additional calibration phases will occur as better standardized data becomes available).  Note that the net causal interactions have been effectively captured in a very scoped and/or simplified format.  Relative magnitudes and durations of impact remain in need of further data & adjustment (calibration). In the interests of maintaining steady progress and respecting budget & time constraints, significant simplifying assumptions have been made: assumptions that mitigate both completeness & accuracy of the outputs.  This model meets the criteria for a Capability demonstration model, but should not be taken as complete or realistic in terms of specific magnitudes of effect or sufficient build out of causal dynamics.  Rather, the model demonstrates the interplay of a minimum set of causal forces on a net student progress construct -- as informed and extrapolated from the non-causal research literature.
Provided further interest and funding, this  basic capability model may further de-abstracted and built out to: higher provenance levels -- coupled with increased factorization, rigorous causal inclusion and improved parameterization.
Clone of Version 6A: Calibrated Student-Home-Teachers-Classroom
Insight diagram
my first simulation for application in early childhood classroom management of behaviour
Years F-2 classroom management
Insight diagram
Marginalized Knowledge (Education)
Insight diagram
Crea un Bucle de Realimentación Negativa, modelando el llenado de un vaso con agua. Esta versión incluye el concepto de manejo de tabla o no liberalidad.
Universidad del Cauca. 
Profesor: Miguel Angel Niño Zambrano
curso: Enlace Curso en Moodle
Videos ejemplos: Enlace a la lista de videos del curso youtube
Clone of Ejemplo 1 v2: Llenar vaso con agua - BRN
Insight diagram
Clone of How many jobless graduates in the UK future scenarios
Insight diagram
Crea un Bucle de Realimentación Negativa, modelando el llenado de un vaso con agua. Esta versión incluye el concepto de manejo de tabla o no liberalidad.
Universidad del Cauca. 
Profesor: Miguel Angel Niño Zambrano
curso: Enlace Curso en Moodle
Videos ejemplos: Enlace a la lista de videos del curso youtube
Clone of Ejemplo 2: Llenar vaso con agua - No Linealidad - Tabla
Insight diagram
Clone of Mobility_JV1
Insight diagram

Dynamic simulation modelers are particularly interested in understanding and being able to distinguish between the behavior of stocks and flows that result from internal interactions and those that result from external forces acting on a system.  For some time modelers have been particularly interested in internal interactions that result in stable oscillations in the absence of any external forces acting on a system.  The model in this last scenario was independently developed by Alfred Lotka (1924) and Vito Volterra (1926).  Lotka was interested in understanding internal dynamics that might explain oscillations in moth and butterfly populations and the parasitoids that attack them.  Volterra was interested in explaining an increase in coastal populations of predatory fish and a decrease in their prey that was observed during World War I when human fishing pressures on the predator species declined.  Both discovered that a relatively simple model is capable of producing the cyclical behaviors they observed.  Since that time, several researchers have been able to reproduce the modeling dynamics in simple experimental systems consisting of only predators and prey.  It is now generally recognized that the model world that Lotka and Volterra produced is too simple to explain the complexity of most and predator-prey dynamics in nature.  And yet, the model significantly advanced our understanding of the critical role of feedback in predator-prey interactions and in feeding relationships that result in community dynamics.The Lotka–Volterra model makes a number of assumptions about the environment and evolution of the predator and prey populations:

1. The prey population finds ample food at all times.
2. The food supply of the predator population depends entirely on the size of the prey population.
3. The rate of change of population is proportional to its size.
4. During the process, the environment does not change in favour of one species and genetic adaptation is inconsequential.
5. Predators have limitless appetite.
As differential equations are used, the solution is deterministic and continuous. This, in turn, implies that the generations of both the predator and prey are continually overlapping.[23]

Prey
When multiplied out, the prey equation becomes
dx/dtαx - βxy
 The prey are assumed to have an unlimited food supply, and to reproduce exponentially unless subject to predation; this exponential growth is represented in the equation above by the term αx. The rate of predation upon the prey is assumed to be proportional to the rate at which the predators and the prey meet; this is represented above by βxy. If either x or y is zero then there can be no predation.

With these two terms the equation above can be interpreted as: the change in the prey's numbers is given by its own growth minus the rate at which it is preyed upon.

Predators

The predator equation becomes

dy/dt =  - 

In this equation, {\displaystyle \displaystyle \delta xy} represents the growth of the predator population. (Note the similarity to the predation rate; however, a different constant is used as the rate at which the predator population grows is not necessarily equal to the rate at which it consumes the prey). {\displaystyle \displaystyle \gamma y} represents the loss rate of the predators due to either natural death or emigration; it leads to an exponential decay in the absence of prey.

Hence the equation expresses the change in the predator population as growth fueled by the food supply, minus natural death.


Clone of Predator-Prey Model ("Lotka'Volterra")
Insight diagram
Simple population dynamics examples based on ​Lotka-Volterra equations.
KMA - 2. EA public
Insight diagram
Clone of Mobility_JV1