General instructions

In the menu on the left you will find the visualizations that have been generated from the results of the student success prediction model on which this initiative is based. You will also find displays of relevant historical information. Choose the visualization you want to see. Once it is displayed, you will notice that you can interact with the graphs and filter the information as needed. Some of these displays contain identifiable information, so only authorized personnel can access them through credentials that will be requested.

Visualizations of Student Success

Visualizations of student success represent a fundamental advance in the scientific democratization of data by making available an indispensable service for the creation of problem solving, through predictive analysis. It will help us to overcome the challenges currently facing the implementation of a dynamic and integrated service to students, for the benefit of our institution as a leader in higher education in Puerto Rico. Advances in data analysis and computer technology have enabled colleges and universities to build powerful statistical models that predict student behavior. Our institution’s Student Success Visualizations are intended to use analysis to determine what factors are correlated with student retention, so that administrators and teachers can predict a student’s chance of success from their admission until graduation.

Institutional Data

The information and results that are presented in this portal come from the institutional data collected and processed in the Data Warehouse of the University of Puerto Rico at Cayey. This student information includes the information on transcripts, grades, courses and schedule from 2006 to the present. This data has been processed and stored in such a way that it can be used for institutional consumption using the tools of (data) mining, analytics and visualization.

 

Prediction Model

In today’s data-driven world, creating a competitive advantage depends on our ability to transform massive volumes of data into meaningful ideas, which allow us to temper our service according to the needs that our society is experiencing. The implementation of the prediction model will allow us to transform the support services traditionally offered to our students, turn them into a support infrastructure where the early detection of problems, the activation of a coordinated network of services and the monitoring of academic progress will positively impact success. student’s academic. The prediction model identified consists of the analysis of data in 5 stages of student life, which are broken down as follows: (1) Information related to the admission data (GPA of High School, School of Origin, among others) ( 2) Result of the exams of the remedial summer courses: (3) Notes and average of the students at the end of the 5 week: (4) Result of the attendance census: and (5) Average of the student at the end of the semester. This system will allow us to identify students at risk of not completing the grade, increase retention, identify when students reduce their level in academic skills, reduce failures and dropouts. The results we expect through implementation will allow us to identify the signs of risk early, where administrators, educators, and support services can deliver appropriate preventive intervention in real time.