2015 DSSG Data Fest: Team High School Graduation

Computation Institute

1 Sept 201504:14

Summary

TLDRImproving high school graduation rates is a significant social issue in the United States, where about 700,000 students fail to graduate on time each year. To tackle this, several US school districts partnered over 14 weeks to create a data-driven solution to identify students at risk. By analyzing data like absences, grades, and demographics, they developed predictive models to prioritize students needing intervention. These models help schools identify risk factors, enabling personalized support to improve graduation outcomes and positively impact students' futures.

Takeaways

🎓 Improving high school graduation rates is a crucial social issue, impacting students' future success.
📊 Every year, approximately 700,000 students in the U.S. do not graduate on time, representing 1 in 5 students.
📉 Students who don't graduate on time face lower life expectancies and expected income compared to those who graduate.
🤝 The project partnered with regionally diverse school districts across the U.S. to develop a data-driven solution to identify students at risk.
🔍 Identifying students at risk of late or non-graduation requires analyzing both dynamic factors (absences, grades) and static data (demographics).
🧠 The team developed predictive models to rank students based on their risk of not graduating on time, helping schools prioritize interventions.
📈 The models demonstrated higher accuracy compared to existing baselines in predicting students at risk, even with limited features.
💡 Schools can use these models to identify different risk factors and drill down to individual student data for more personalized interventions.
🏫 Schools can also compare how their performance and risk factors measure up against other schools in the district.
🌟 The ultimate goal is to enable schools to implement effective interventions that improve graduation outcomes and students' overall life prospects.

Q & A

What is the main social issue addressed in the video?
-The main social issue addressed is improving high school graduation rates in the United States.
Why is graduating from high school important for students?
-Graduating from high school prepares students for higher education, improves their life expectancy, and increases their expected income.
How many students in the U.S. fail to graduate from high school on time each year?
-Approximately 700,000 students do not graduate from high school on time each year in the United States.
What is the objective of the project mentioned in the video?
-The objective is to develop a data-driven solution to identify students at risk of not graduating on time.
What kinds of data are used to track student progress in this project?
-The data includes grade-level information like absences, tardies, grades, and test scores, as well as static demographic information.
How does the model developed by the project help schools?
-The model predicts which students are at risk of not graduating on time and ranks them by the urgency of attention needed, enabling schools to prioritize interventions.
What is the goal of developing personalized interventions for students?
-The goal is to address the specific needs of students at risk of not graduating or graduating late by providing targeted, effective interventions.
How does the project evaluate the performance of the predictive models?
-The models are evaluated by how well they prioritize students at risk, with the ideal model ranking at-risk students above those not at risk.
What are some benefits of using this data-driven approach in schools?
-Schools can identify risk factors, compare performance between schools, and design more effective interventions to improve both graduation rates and students' overall outcomes.
What are the next steps for schools using the developed models and data insights?
-Schools can categorize students by different risk factors, drill down into individual student risks, and compare their performance with other schools to implement more effective interventions.

Outlines

00:00

🎓 Importance of High School Graduation

This paragraph highlights the critical social issue of improving high school graduation rates. Graduating from high school equips students for higher education, increases their life expectancy, and enhances their potential income. Despite these benefits, around 700,000 students in the U.S. fail to graduate on time each year. This issue requires attention and solutions to ensure more students can successfully graduate.

🧑‍🏫 Data-Driven Approach to Addressing Graduation Gaps

To tackle the high dropout rate, a data-driven approach has been implemented with various U.S. school districts. These districts are diverse, both regionally and in student populations, yet they share a common goal of ensuring timely graduations. The first step in this process is identifying students at risk of not graduating, which involves gathering data on their academic performance, behavior, and demographics.

🔍 Identifying Students at Risk

This section discusses the importance of personalized interventions for students at risk of either not graduating or graduating late. Despite being labeled as 'not on time,' these students have varying outcomes and require different approaches. By analyzing data from school partners—ranging from grades and attendance to demographics—a profile of each student’s risks can be developed over time.

📊 Predictive Models for Graduation Outcomes

Based on the collected data, predictive models were developed to assess which students are likely to graduate on time. These models generate a prioritized list of students needing urgent attention, ranked by their risk levels. The ideal model accurately identifies at-risk students, and initial evaluations show promising results compared to existing baselines, despite the limited data used over the summer.

📈 Leveraging Data for Improved Interventions

The final section outlines how schools can use the information from the models to develop effective interventions. Schools can categorize students by risk factors, explore specific reasons for individual student risks, and compare their performance to other schools. By understanding these factors, schools can create targeted interventions that not only improve graduation rates but also positively impact the overall well-being of students.

🙏 Conclusion: Improving Graduation Rates, Improving Lives

In conclusion, this data-driven approach provides valuable insights into the factors affecting student graduation outcomes. Schools can use this knowledge to design better interventions, ultimately leading to improved student success and better life outcomes beyond high school.

Mindmap

Keywords

💡Graduation Rates

Graduation rates refer to the percentage of students who successfully complete high school within a given timeframe, typically four years. In the video, it is emphasized that improving graduation rates is a crucial social issue, as students who graduate on time are better prepared for higher education and have better life outcomes, including higher life expectancy and income.

💡Students At Risk

Students at risk are those who are likely to not graduate from high school on time or at all. The video explains how identifying these students is key to improving graduation rates. Data such as absences, grades, and test scores are used to predict which students are most at risk, allowing schools to intervene and provide the necessary support.

💡Data-Driven Solutions

Data-driven solutions are approaches that rely on analyzing data to make informed decisions. In this context, data provided by partner school districts—such as student attendance and grades—was used to develop models that predict which students are at risk of not graduating on time. These solutions help schools create targeted interventions.

💡Personalized Interventions

Personalized interventions are tailored strategies designed to address the specific needs of individual students at risk. Since students have different reasons for not graduating, the video highlights the importance of using data to identify the unique challenges faced by each student and implementing personalized solutions to help them succeed.

💡Predictive Models

Predictive models are statistical or machine learning algorithms used to forecast future outcomes based on historical data. In the video, these models are developed using student data to predict which students are at risk of not graduating on time. The models rank students by the urgency of their needs, helping schools prioritize interventions.

💡Demographic Data

Demographic data includes information such as a student’s race, gender, socioeconomic background, and other static attributes. This type of data, combined with academic performance metrics, helps in developing more accurate predictive models to assess which groups of students are more likely to face challenges in graduating on time.

💡Risk Factors

Risk factors are elements that contribute to a student being at risk of not graduating. These include poor attendance, low grades, and behavioral issues. The video discusses how identifying different categories of risk factors allows schools to better understand why certain students struggle and to create interventions that address these specific risks.

💡Interventions

Interventions refer to the actions taken by schools to support at-risk students and improve their chances of graduating. In the video, the term refers to the specific, data-driven strategies that schools can implement after identifying students in need of help. Examples include tutoring, counseling, or adjusting teaching methods to meet students' needs.

💡School Districts

School districts are administrative divisions of public schools, each responsible for managing a group of schools in a certain region. In the video, several public school districts across the U.S. serve as partners in developing data-driven solutions to improve graduation rates. These districts represent diverse student populations with varying graduation outcomes.

💡Graduation Outcomes

Graduation outcomes refer to the different possible results regarding a student’s completion of high school. In the video, these include students who graduate on time, students who graduate late, and those who do not graduate at all. The goal is to improve these outcomes by identifying students at risk early and intervening to help them succeed.

Highlights

Improving high school graduation rates is a crucial social issue.

One in five students in the United States does not graduate from high school on time.

Approximately 700,000 students fail to graduate on time each year in the U.S.

The team has been working with diverse public school districts for 14 weeks to develop a data-driven solution.

The goal is to identify students at risk of not graduating on time.

Students at risk are divided into two categories: those who may not graduate at all and those who may graduate late.

Despite sharing a label, students not graduating on time have different outcomes and need personalized interventions.

Data used includes grade level information (absences, tardies, grades, test scores) and demographic information.

Features predictive of whether a student will graduate on time were generated from the data provided.

The models developed predict which students are likely not to graduate on time.

The models rank students by their urgency of attention for intervention.

Evaluation shows the models perform well above existing baselines, even with limited data.

Schools can use this information to identify risk factors contributing to students' risks.

Tools help schools identify factors for individual student risks and compare performance between schools.

The goal is to not only improve graduation outcomes but also positively impact students' lives.