Kinsley Stocum

BLOG: Strategies for Improving the Impact of First-Year Student Data

Blog Post created by Kinsley Stocum on Aug 20, 2019

With average attrition costs at nearly $10 million per institution, improving student retention rates, especially from the first to second year, can have a significant impact on institutional budgets and resource allocation. Unfortunately, those looking to combat the issue with data-informed interventions often quickly realize that while there may be lots of data, actionable insights are few and far between. Moreover, it can be difficult to know which data, when acted upon early, will most positively impact student retention and success.


In sum: Water, water everywhere!


If trying to make heads or tails of the gigs of data your students generate seems like a lost cause, fret not. Below, we've distilled our data collection philosophy to three simple strategies you can use to shape how your campus gathers and utilizes this info for maximum impact and minimum stress.

The Key Three: Early, Easy, and Systematic

 

1. Early Data Collection

It is currently common practice for many institutions to focus on mid-term grades and first-semester GPAs to trigger interventions with first-year students. However, changing the trajectory of the student experience after 8 or 15 weeks can be overwhelmingly difficult, especially when the issue is academic. Students establish academic habits and behaviors as well as social circles and involvement patterns during the first few weeks. They also experience challenges, including a tougher academic environment, homesickness, increased freedom, and more.

 

While the consequences of these foundational experiences and behaviors may not be seen right away, research (Woosley, 2003) has shown that students' initial college experiences, especially within the first few weeks, are linked to long-term outcomes. Therefore, the first step in improving the impact of our first-year student data is the development and use of targeted early indicators.

 

Like red flag systems of the past, early indicators signal issues may need to be addressed. Unlike those first systems, however, today's early indicators go beyond simply lighting flares to identifying patterns and behaviors that need to be addressed at both the class and individual levels. Done right and your early indicators prompt early interventions—giving your support resources time to make an impact within that crucial time frame before midterm reports.

 

2. Easy Data Collection

Another common obstacle institutions face when it comes to first-year students is capturing full and complete data. You know what we mean—not all faculty submit midterm grades or attendance records. Not all courses use learning management systems. Not all students complete surveys. And no one appreciates new requirements and systems that create additional tasks to generate data.

 

To overcome this obstacle, we need to get creative and make data collection easy—and most importantly, part of the workflows already taking place. For instance, taking class or event attendance does not have to be a manual task. Tools that allow students to log into a course can take the load off of faculty. Or better yet, digital classroom engagement tools (e.g., polls, quiz questions, etc.) can be used to automatically record attendance. Surveys, too, can be streamlined or shortened, incorporated into first-year seminars, put into simple tools, and more. Additionally, survey data can be linked with other data sources so that questions don’t have to be repeated.

 

In sum: simplifications to data collection not only decrease the workload on data providers, they can also improve the quality of the data by standardizing data sources and removing opportunities for human error.

 

3. Systematic Data Collection

Finally, our third strategy for improving the impact of first-year student data is to be systematic and strategic about the data collected and used. While conversations about big data push our desire for digits to ever growing heights, it is becoming increasingly apparent that not all data is equally useful. As T.S. Eliot laments in Choruses from the Rock, "Where is the knowledge we have lost in information?" It's time to get that knowledge back.

 

Research has unearthed a plethora of key issues related to student success and retention in one way or another—issues like academic performance, social integration, financial means, motivation and class attendance, to name a few. A systematic approach requires thinking about these issues holisticallyensuring they are coveredbut also simplyeliminating duplications. Some issues may be measured through easy tools (e.g., attendance through a classroom engagement system). But some issues, such as commitment and motivation, may need to come directly from the student on a survey. Once the data elements and sources are put in place, the data needs to be integrated so that individual elements are placed in a broader context. Class attendance issues may prompt different inventions when placed alongside other concerns such as finances or homesickness. Thus, to make an impact, an institution needs a systematic approach including a variety of tools to easily collect and integrate a set of focused data.

 

 

Overall, big data alone won’t solve the first-year student retention issue. To make an impact, data must be received early, gathered and analyzed easily, and acted upon in a systematic manner.

 

Looking for additional guidance on how these strategies can be implemented using the data your campus is currently working with? Check out Cirque by Macmillan Learning for more information on how we make it easy to gather and intervene on the most impactful early insights.

 

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