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Students
Home›Students›Why Data-Driven Insights Are the Key to Elevating Student Outcomes

Why Data-Driven Insights Are the Key to Elevating Student Outcomes

By Matthew Lynch
February 21, 2022
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Any teacher can tell you that student growth is arguably one of the most important aspects of teaching. Objectively measuring student-growth may seem difficult, but with the increase in data collection and analysis techniques, insights into student growth are becoming more accessible. These data-driven insights are the key to elevating student outcomes because you can see exactly where improvements need to take place. 

Benefits of Data-Driven Insights 

Student data can assess what extra help individual students need. Students that are given individual work based on their ability level can advance at their own pace. In classrooms, sometimes it is hard to continue with lessons without certain students feeling left behind; so, by using data, you can create individual lessons for students to gain extra help on topics they are struggling with. 

Algorithms can be used to predict student achievement. When used properly, these algorithms can identify patterns in student behavior and academics, which can then be used to predict future outcomes. By making these predictions, teachers are able to take a proactive approach to student problems and plan an intervention before these behaviors become a hindrance on student success.

Additionally, algorithms can analyze data that helps with student retention rates. Higher education institutions have begun to use algorithms to identify warning signs of struggling students, so they know when to intervene. These warning signs are found through student success data and help the students get the personalized attention that they need to continue with their education. Clearly, these data-driven insights are useful in educational institutions of all levels in order for every student to get the help they need, regardless of age. 

Data can also identify areas in which equity is not present in an educational institution. For example, data that shows low enrollment for adult learners can help determine what factors block the accessibility of education for these people. The institution with this information can then analyze it to determine what they can do differently to make learning more accessible. In the example previously discussed, the school may discover that day classes are a barrier that adult learners face when trying to achieve higher education; this may be because of factors such as work and childcare needs. Understanding student data can help schools maximize learning potential and accessibility for all students. 

How to Obtain Data-Driven Insights 

Algorithms are used to determine placement in schools based on student data. These placements can help students learn at their proper academic level and ability, ensuring they do not miss anything important and learn what they need to succeed. For example, algorithms can assess student data to determine if a student is a good fit for a specific instructional program. When students are paired with a program compatible with their strengths, they are more likely to succeed academically. 

Algorithms can be used to assess data from tests as well. This testing information allows teachers to reflect on what they can do better to help students. For example, if a teacher sees that most students got a specific question wrong on a test, the teacher can ask him/herself how to teach it better so students understand better.

One thing to remember when using algorithms based on data is that these technologies can carry bias. Technology cannot observe and report on external factors that may be influencing student data, so always proceed with caution when using algorithms to make assumptions about student achievement. 

Remember, schools need to share data with parents. Data transparency is an essential part of data collection because it allows parents to understand their child’s learning growth. Making this information easily accessible can help parents better understand how they can help their children. 

Conclusions 

Although data has been proven time and time again to be extremely helpful in monitoring and boosting student success, teachers may feel overwhelmed by the thought of collecting and analyzing this data. However, there are many resources to help you with your collection and understanding of this student information. Remember not to let the fear of the process deter you from using this valuable resource. There are many different software and online templates that can help you gain this information to help students succeed to their full potential!

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