Cycle 5 (2015 Deadline)
Data sciences training and research to address crime and insecurity in El Salvador
PI: Oscar Picardo (email@example.com), Universidad Francisco Gavidia
U.S. Partner: Carlos Castillo-Chavez, Arizona State University
Project Dates: January 2017 - December 2017
Project Website: http://www.peer-stem.edu.sv/ (Spanish and English)
The 2015 UNESCO Science Report (Towards 2030) shows that El Salvador ranks poorly in Latin America in science, technology, and innovation (STI) capacity. However, improving Salvadoran STI capacity is challenging, as approximately 32% of the population lived below the national poverty line in 2014, the country is plagued by gang violence, and among countries not at war, El Salvador had the world’s highest estimated murder rate in 2015 (6,600 homicides out of a population of 6.3 million). Given this backdrop, the project seeks to increase STI capacity in El Salvador by addressing crime and insecurity in the country. To do so, the project team will launch a data sciences training and research program at the Universidad Francisco Gavidia (UFG) for 30 Salvadoran participants. Program participants will include ten UFG students, ten participants from Salvadoran judicial institutions or law schools, and ten STEM teachers selected from two public secondary schools in San Salvador. After an intensive two-month training phase, the participants will divide into a Judicial Group and a Teachers Group and begin a ten-month research phase. The program structure is modeled after the successful NSF research experience for undergraduates (REU) program, the Mathematical and Theoretical Biology Institute (MTBI), which the U.S. partner on this project has operated for 20 years.
Skills improvement workshop in STEM and programming in Python. (Photo courtesy of Dr. Picardo)
Inspired by the success of Dr. Rodrigo Guerrero Velasco in applying data sciences and epidemiology to combat crime in Cali, Colombia, the Judicial Group will create a crime data sciences laboratory at UFG to collect and analyze crime and violence data in El Salvador. Their research objective is to improve the tools to guide crime and violence prevention strategies in El Salvador. Education is a critical short- and long-term remedy to mitigate crime and violence, but the low average quality of teachers constrains efforts to improve educational efforts. To address this constraint, the Teachers Group will work to improve the professional development of Salvadoran STEM teachers. Specifically, the group will help teachers create hands-on STEM activities with an emphasis on data collection and analysis to supplement STEM curricula in public secondary schools. They will also form teacher Lesson Study groups at two public secondary schools.
This PEER project addresses USAID’s goals of mitigating crime and insecurity in El Salvador. By training the Judicial Group participants and creating a crime data sciences lab, the project should provide valuable data sciences resources that increase the competence of the judicial sector. By training public school teachers in San Salvador and promoting the development of new STEM curricula that are not focused on rote learning, the project should improve STEM education for at-risk youths, which can help mitigate the lure of gangs and provide the foundation for learning valuable technical skills. The focus on training teachers creates a multiplier effect, as these teachers can train their colleagues, and this network can reach more students than other types of programs. The training of UFG students also strengthens their marketable job skills and provides a pipeline of valuable government and private sector employees. In addition, the crime data sciences lab will be the first project for the new UFG Center for Mathematical Modeling in San Salvador to study crime, violence, and insecurity and their impacts on Salvadoran society.
During July-September 2017, the team created a MOOC course on 3D modeling with FreeCAD software. The course contains 32 tutorial videos, and is intended to provide the necessary tools to develop 3D object models with a 3D Printer. The team purchased equipment for experimental STEM Laboratories in three schools - “España”, “Concha Viuda de Escalón”, and “San Luis Talpa” - including 3D printers, robotics kits, complete physics laboratory set-up, specialized software, and laptops, so that students could use the equipment to carry out STEM projects, which, in turn, will help produce the measurable data the team needs for their research deliverables.
Since the beginning of the project, thirty teachers, ten UFG students, and ten instructors of the National Academy of Public Safety received took six courses with international instructors from Arizona State University, UNIANDES Colombia and UFG, including: (1) Applied Statistics; (2) STEM Methodolody (Design Thinking); (3) Python Programming; (4) Language “R”; (5) Didactic Planning for Sciences; and (6) Fundamentals of Data Sciences.
Potential Development Impacts: The teacher Bejamín Recinos, one of the beneficiaries of the project, established a Robotics Club in España School, along with his students winning several prizes in the national contest of educational robotics. The Concha Viuda de Escalon School developed its second STEM project fair, UFG staff were part of the qualifying jury, evaluating over 50 projects.
|Receiving the first prize with the Taiwanese ambassador and the Deputy Minister of Science and Technology||Teacher Ramon Benjamín Recinos and students in Robotics Club||Participants in the 2017 National Championship|
Research data and future plans
Since the installation of the STEM Experimental Laboratories in beneficiary schools has not been fully completed due to delays in equipment procurement and delivery, and due to the end of the school year, the team still plans to conduct equipment training and motivate teachers to take the MOOCS courses. If the project is extended beyond its originally planned project dates, the team intends to purchase robotics kits, provide a basic robotics workshop, and develop measurable research data to support the premise that by training the Judicial Group participants and by creating a crime data sciences lab, the available valuable data sciences resources would increase the competence of the judicial sector. Similarly, measurable data is anticipated to support the premise that by training public school teachers in San Salvador and by promoting the development of new STEM curricula that are not focused on rote learning, and by providing the foundation for learning valuable technical skills, STEM education for at-risk youths will be improved, helping mitigate school drop-out rates, the lure of gangs, episodes of violence, among other indicators.
Dr. Oscar Picardo's recent article
on science education and its contribution to violence reduction and his PEER project goals was recently published in La Prensa Gráfica.
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