Understanding Dropout Rates at Politecnico di Milano

Higher education dropout rates are a big problem around the world. Many students begin their university journey but do not finish their degrees. This paper takes a closer look at why students drop out, specifically at Politecnico di Milano, a university in Italy. The findings could help universities figure out how to keep more students in school.

#The Big Picture of Dropouts

When we talk about "dropouts," we're referring to students who leave their college programs before they earn their degrees. In many countries, around 30% of students don’t complete their education. Italy has even worse statistics, with more than half of students not graduating. This is not just annoying for universities; it's a waste of resources and impacts the skills of the future workforce.

It's like buying a plant, watering it, and then forgetting to put it in sunlight—eventually, it just withers away. Universities invest a lot in students, so when they leave, that investment is lost.

#Why Do Students Drop Out?

Dropouts happen for many reasons. Some students realize their degree program isn't what they expected. Others find the coursework too challenging. Some might even get involved in work or family commitments that take priority.

There's also a difference between various fields of study. For instance, some programs have high dropout rates early on because they have tough introductory courses. Others might see students leaving at the end of their studies. Schools can also vary in dropout rates due to factors like how engaged the faculty is or the Support Services available.

#Data from Politecnico di Milano

Polimi has a variety of degree programs across four schools: Architecture, Design, and Engineering. The school offers 23 different undergraduate programs. We looked into dropout patterns during the first year for these programs.

Using data from the university, we examined why students left their courses. We focused on the first year as that’s when many students decide if they want to continue.

#The Method We Used

We used some fancy statistical models that combine data from multiple sources to better understand dropout trends. Imagine trying to put together a puzzle with pieces from different boxes. It helps to have a method to track where each piece belongs.

In the first part of our analysis, we reviewed past dropout data to create a model that could predict when and why students drop out. We were also interested in understanding how factors like the degree program or school influenced dropout rates.

#Getting to the Numbers

We used something called a Cox model, which helps us look at the timing of events. In our case, the event was a student dropping out. By applying this model, we could see patterns and trends over time.

We also analyzed the data in two levels—considering both the program level and the school level. It’s like looking at both the individual trees and the entire forest at the same time.

#Identifying Risky Times

Our analysis highlighted critical periods when dropout rates increased. By understanding these times, universities can focus their efforts on providing support to students who may be at risk.

#The First Phase

In the first phase, we created a dropout curve that showed how many students left their programs over time. This curve helped us pinpoint which degree programs had the highest dropout rates.

For instance, some programs showed a steep drop in numbers at the end of the first year. This can often be attributed to students realizing they might not be in the right program after all.

#The Second Phase

Next, we looked at how to predict future dropout events based on our findings. This involved understanding how current students are likely to drop out based on past data. We gathered various factors such as grades, demographics, and program details to get a clearer picture.

#The Importance of Analysis

By investigating dropouts, universities can save resources and help students succeed. If data shows that students in a certain program are more likely to leave, universities can step in to offer help.

#The Results

Through our analysis, we found that dropout behavior isn't one-size-fits-all. Different programs and schools have unique dropout rates. As we dug deeper, we found that dropout rates can differ even within the same university.

#The Fun Part: Predicting Dropouts

We wanted to go beyond just observing patterns; we wanted to predict who might drop out. Using logistic regression, we created a model that incorporates various factors. It's like making a recipe where the right mix of ingredients can lead to a successful dish.

For our model, we took into account:

• Age
• Gender
• Educational background
• Performance in the first semester

These factors can help us identify students who are more likely to leave and allow universities to intervene early.

#What Did We Learn?

1. Early Warning Signs: Students who earn more credits in their first semester are less likely to drop out. It’s a bit like getting a solid start in a race; it boosts confidence.

2. Different Programs, Different Risks: Some programs have higher dropout rates than others. This could be due to coursework being too challenging or not meeting students' expectations.

3. The Impact of Admission Scores: Interestingly, students who score high on admission tests sometimes drop out at higher rates. This could indicate that these students were not adequately prepared for university-level work.

#What's Next?

While these findings are valuable, we know that they are just the beginning. Dropout behavior can change over time, especially as new challenges arise, like what we saw during the Covid-19 pandemic.

To truly grasp dropout dynamics, we need to keep refining our methods and exploring other factors that may contribute to why students choose to leave.

#Conclusion

Addressing dropout rates is key for universities. By understanding why students leave and using data to predict future trends, educational institutions can take steps to improve retention rates. The ultimate goal is to ensure that students not only enter higher education but also leave with a degree in hand.

With the right support and understanding, we can help students stay on track and achieve their educational goals. After all, nobody wants to buy a plant and forget to water it. Let's ensure that every student gets the attention and resources they need to flourish.