While higher education institutions use analytics to inform instructional decisions, many believe it is now more than an optional solution. Student data has evolved to offer more than completion rates and test scores. Strong analytics capabilities help institutions improve their programs and effectively predict and respond to changes. These functions drive continuous growth for institutions. One EDUCAUSE Review study states that institutional analytics has become critical to informing strategic actions and providing proactive student services.
This guide explores the importance of data-driven education and key ways to use data analytics for improving certificate program outcomes.
Data in education involves analyzing information and forming actionable insights. Institutions use it to identify learning gaps, evaluate instruction methods, implement targeted instruction, assess student progress, and address inequalities. The following are some of the key ways certificate program analytics lead to institutional success:
There are numerous broad categories in which you can identify, collect, and analyze improvement data:
Explore these seven ways to use data analytics to improve certificate program outcomes.
To build an effective, accurate data analysis system, create specific targets to measure against the certificate program performance metrics. One Complete College America report mentions that institutions should measure priorities by considering the institution’s mission and strategic plan. Your key performance indicators (KPIs) should demonstrate how the program helps achieve these higher goals.
Engagement metrics can transform the student experience. Consider using data solutions to track student interaction with learning materials, time spent on learning activities, and participation in discussions. These metrics will establish their engagement levels and identify where the certificate program could improve to boost engagement.
Refine your curriculum by analyzing program improvement metrics that enable content optimization. For instance, you may adjust teaching methods and learning materials for different demographic groups or learning styles.
Another strategy for using data to improve program outcomes is to showcase the value and impact of your certificate program. You can analyze post-program employment data like starting salaries, job placement rates, and career advancement opportunities.
You may also do ROI analysis by measuring program costs against employment outcomes. Doing so allows you to gauge the economic value of your certificate program and share the results with prospective students. You can also use the data to determine where your program can improve to address skill gaps and current industry needs.
Use student performance data to refine your current curriculum. The data shows you which content areas and skills students find challenging. This information allows you to make data-informed decisions about curriculum adjustments, ensuring that changes effectively enhance the learning experience.
If your institution has several delivery methods, such as in-person, online, or hybrid learning options, compare the performance metrics across all avenues. The results help you determine the most effective approach for specific content areas.
Predictive analytics helps you recognize students who are at risk of dropping out. It identifies these students by analyzing assessment results, attendance records, and engagement patterns. The early alert system triggers a timely support suggestion. This awareness allows you to create customized intervention and support strategies based on unique demographic factors.
For example, if the data shows that the at-risk student has outstanding tuition, you might need to implement a program that offers financial or emotional assistance. If their attendance rates are low due to family responsibilities, it helps to implement additional academic support programs. This type of program may offer classes for this student group at a more convenient time, preventing academic setbacks.
You can use predictive analytics to forecast enrollment. These features predict future enrollment trends based on demographic shifts, historical data, and labor market changes. Labor market data specifically allows you to recognize emerging skills and knowledge areas that the institution should incorporate into certificate programs to meet industry needs.
When implementing a data analysis solution, you need to ensure that faculty members know how to use it for the best results. Refine their data literacy skills by incorporating training and technical support. These techniques enhance their proficiency in locating, interpreting, and understanding data. It should also teach instructors how to use the data to inform instructional decisions. Collaboration between faculty members is a great method for building on each other’s understanding for more accurate interpretations.
A data-driven education provides institutions with the tools and knowledge needed to boost student engagement, student enrollment, and institutional success. Watermark aids higher education institutions in their mission by offering software solutions that inform program management.
Watermark Planning & Self-Study promotes continuous improvement through data-driven decisions that enable collaboration, identify curriculum gaps, and demonstrate progress. Meanwhile, Watermark Student Success & Engagement helps track student progress and provides early alerts for at-risk students. Our software has helped institutions increase their retention rate by 6 percent in one year and garnered 260 percent more engagements with students. Request a demo with us today and learn how your institution might benefit from Watermark.
