The Key Three: Early, Easy, and Systematic
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.
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.