This project was prepared as part of a BioQUEST faculty development workshop entitled Mathematical and Computational Biology Education at University of Puerto Rico - Rio Piedras in July 2004. The BioQUEST Curriculum Consortium is committed to the reform of undergraduate biology instruction through an emphasis on engaging students in realistic scientific practices. This approach is sometimes characterized as an inquiry driven approach and is captured in BioQUEST's three P's (problem-posing, problem-solving, and peer-persuasion). As part of this workshop groups of faculty were encouraged to initiate innovative curricular projects. We are sharing these works in progress in the hope that they will stimulate further exploration, collaboration and development. Please see the following links for additional information:

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World Population: A Model Approach
 
 
Authors          Audiences          Overview           Materials          Resources           Future Directions
 

 


Authors


Lillian Bird
University of Puerto Rico - Rio Piedras


Julio C. Hernandez
Department of Education of Puerto Rico


David Torres
University of Puerto Rico - Rio Piedras


Annabelle Rivera
University of Puerto Rico - Rio Piedras

 
   
 


Possible Audiences:

Geography, Social Sciences, Demography and Mathematics Courses from junior high school to undergraduate students.  

 
 


Brief Overview:

World population is a matter of study under several subjects in many courses. It is important to take student to make inferfences in the given data and how to use the models to explains changes and when to use a certain model that may not be the best fit but explain specific observations. The Saxony (Gelfan) case was used to demosntrate the use of statisticals model in the analysis of populational issue.  

 
   
 


Project Materials:

In the mathematical analysis it was used the Excel and Power Point Programs.  

 
 


Resources and References:

Dr. Jose Molinelli, Chair, Department of Environmental Sciences UPR-Rio Piedras  

 
   
 


Future Directions:

It is pretended to analyze the use of two or more models at the same time and to test them in order to fit the appropiate one.