K12 Analytics to Prevent Students from Dropping Out

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The average dropout rate of US high-school students is 9%, as of 2019. Though it decreased quite substantially over the last decade, this is still high. How can educational institutions lower this number, encouraging students to proceed with their studies? 

Applying K12 data analytics can be a useful solution for dropout prevention in schools. Let’s find out what drives students to drop out and how high schools can leverage the power of AI, big data and machine learning to keep their learners motivated and engaged. 

The Main Reasons of Students’ Dropping Out

Here are some of the main reasons why students drop out of high school:

  • Individual Factors. Student’s abilities, talents, desires and inclinations are ultimately different. This is the core reason behind education personalization. When an educational program is poorly matched with students’ actual interests and life goals, the risk of dropping out increases because of the low academic performance, lack of motivation and lack of understanding how learning a specific set of subjects will help them in the future. Some students also need a special approach to study successfully. For example, 36% of students with a disability drop out of high school. 
  • Family Factors. 5% of US students who dropped out of high school have parents without a high-school education. In this case, the students are more likely to follow their parents’ path since parents are the most powerful role models for kids, according to different studies
  • School Factors. According to a study, 75% of students have negative feelings about the high school they are studying in. The reasons for such an attitude are pretty diverse —  the students may have communication and socialization issues, misunderstandings with teachers and even face bullying. 
  • Community Factors. The issue of dropping out is even more relevant for students from low-developed communities. They are at a higher dropout risk by default because of their social and cultural environment. They also have a higher risk of developing alcohol or drug addiction. They may lack literacy and local authorities support, a learning-centered mindset, and an understanding of the importance of education. 

Dropout Prevention Measures

What are the ways to prevent students from dropping out? Preventing students from quitting high school becomes more attainable when the students themselves, their parents and the educational institutions are equally interested in keeping students enrolled, engaged and motivated.

Below are some tips for each of the parties in the educational process to decrease chances of a student dropping out. 

What Can Students Do?

  • Ask for help. This is one of the most obvious tips, and nevertheless, it works. There is nothing shameful in asking for help from peers and teachers. Still, the school environment should be healthy and encouraging, letting students be more open when they need assistance with their studies. 
  • Move step by step. Splitting a huge goal into several achievable ones is one of the best practices that work equally well in business, in someone’s personal life and in education. Students are welcome to set smaller goals (for example, keep their academic performance rate high for a week, and then, do the same the next week). This is also a good strategy for students who lack motivation since they become better able to track their progress and get inspired by it. 
  • Learn the most interesting disciplines deeper. Not all academic disciplines are equally interesting and useful for a certain career choice. As one more option to support interest in studying, the students can dig deeper into the topics and subjects that interest them most. 

What Can Parents Do?

  • Stay involved. A lot of the issues that can lead to a student dropping out are easier to prevent than to solve. Still, parents should stay involved in their child’s educational process, communicate with teachers if needed and support the student along the way. 
  • Support, assist and encourage. Parents’ love and assistance matter a lot both in childhood and adulthood. Sometimes, a few sincere words of support said by parents are enough to motivate a student not to give up. 
  • Consider a break instead of quitting. Even when a problem seems unsolvable and parents can’t persuade their child to proceed with education, they still can suggest taking a year-long break. This time frame is enough to re-evaluate the learning experience, find out more about the reality of being an adult and make a more conscious life decision. 

What Can School Do?

  • Organize personalized and flexible studying. Both of these approaches are becoming trendy in the post-pandemic times. What’s more, education personalization and the opportunity to study flexibly can also become the reasons to keep learning. 
  • Provide career consulting. Some students decide to leave the high school since they see no practical usability of the knowledge they receive. A lot of them also know that finding a job with little to no prior experience will be a challenge. The combination of these factors increases the dropout rate, so in this context, schools are welcome to deliver more practice-oriented educational content and help the students to stay well-versed in the labor market trends. 
  • Introduce mentorship programs. This is another winning opportunity for the students who are on the verge of dropping out. A mentor (for example, a former student or volunteer) can share their personal experience, support, assist, guide and inspire them to proceed with their studies. 

K12 Data Analytics for Dropout Prevention

Data analytics and artificial intelligence is already largely applied in the field of education. AI helps with creating personalized learning programs, enriches education experience, reduces time spent on routine tasks and much more. Using artificial intelligence and K12 data analytics for students dropout prevention is one more promising use case of the technology in education. 

Still, the biggest challenge for integrating AI into the educational workflows and extracting insights from big data is that this data comes in a heavily unstructured and unclassified format, which makes K12 analytics quite challenging.

K12 data analytics solutions, such as AnalyticVue, help educational institutions gather student data from various systems, structure and classify it to get a big picture, and extract valuable insights according to the specified parameters.

Let’s find out how to use data analytics in education to reduce, prevent and predict students dropping out. 

  1. Gather Information

To get started with using data analytics for schools, it is necessary to gather the necessary information from multiple Student Information Systems, assessments and distant learning tools. Gathering K12 data from the online education management platforms becomes even more essential during post-pandemic times since a lot of the students face health, family and personal issues that directly affect their performance, willingness to study and plans for the future. 

As for the data the educational institution has to gather at the first stage of integrating the data analytics platform, let’s consider the example of Pontificia Universidad Javeriana Cali (Colombia). The university uses the AI system for dropout prevention, powering their solution with the following data and corresponding hypothesis:

  • Academic issues
  • Student-institution empathy
  • Financial situation
  • Pedagogical problems
  • Vocational orientation 

By weighing these factors individually and as a whole, the university has been able to predict if a certain student is likely to drop out, thus enabling educators to apply preventive measures to help the student continue their studies. 

  1. Predict Possible Issues

Being guided by the data gathered on the previous stage, and taking historical K12 information for the previous periods into account, it becomes possible to determine the risks and predict the likelihood of dropout for student groups in general and for each student individually. 

For example, the authors of Using Big Data to Predict Student Dropouts research, use multiple risk predictors to find out how a certain factor increases or decreases the risk of dropping out, which includes age, gender, family status, grades and others. Their study revealed that decreased academic performance, lack of financial support from parents and student gender (female) are the highest risk factors. 

  1. Prevent Dropping Out Using Individual Methods

At this stage, it is necessary to personalize dropout prevention strategies as much as possible. For example, a school can assign a mentor for those students who are in the high dropout risk group because of their low academic performance. 

For those who strive to combine studies and support a family, an educational institution may suggest flexible or distant learning programs, evening lectures or summer education initiatives. Still, the biggest challenge for the schools that want to keep their dropout rates low is actually readiness to act on K12 data insights and support their students. 

Conclusion

There are a lot of reasons why students decide to quit their education and consider other opportunities to invest their time and money in. Nevertheless, high school education matters. Educational institutions can leverage AI-powered K12 data analytics solutions like AnalyticVue to prevent students’ dropout and deliver more personalized and flexible learning experiences while keeping learners engaged and motivated.

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