Integrating Data Analytics into Higher Education

Higher education institutions are using data analytics to quantify how student experiences affect a variety of student success outcomes. Incorporating data analytics in an integrative way can help universities navigate their toughest decisions and create a culture of continuing improvement for both students and faculty. Colleges and universities can use data analytics to gain insight into critical questions, such as which programs to offer and which teaching methods are most effective, and ultimately affect the internal motivation to meet an institution’s strategic goals.

Which programs to offer:
The skills required for a current entry-level worker have never been more different than previous generations. Ever-changing technologies in the workplace have strained universities in deciding which programs and curriculums will best prepare their graduates to succeed not only in their first job but throughout their entire career. Data analytics can help universities with decision making and adjust curriculum closer to real-time than ever before.

Creating datasets that map credentials to student skillsets pre-graduation will allow universities to better track how those skills affect workplace performance. This real-time relationship allows universities to better understand how certain courses and skills affect future outcomes and adjust as needed. Additionally, building relationships with employers will help create a roadmap of desirable skills for recent graduates and help the universities understand what’s needed in the workplace. With the advancements in technology and openness to data analytics, there are options to better prepare students in not only digital hard skills but also digital soft skills such as online collaboration.

How to teach: Today’s educators are presented with the challenge of teaching students who have grown up in an all-consuming digital world with access to a variety of different modes, forcing educators to adjust teaching styles to reach students most effectively.

Collecting data on measurable student events and experiences can help provide guidance to educators in determining how to structure their learning and resources. This can increase engagement and shift away from strictly lecture-based classes and into more project-based, experiential learning. Digital tools, such as AI, learn about student tendencies and adjust teaching and questions in real time to better identify gaps and drive students’ improvement. Administrators are also able to use data analytics in multiple ways to structure the learning environment. For example, resource allocation is improved by tracking usage rates, and organizational design can be changed based on new discoveries. Using data analytics to track and analyze patterns in classroom and energy usage can help more efficiently allocate resources and save energy.

Why we teach: Out of all the industries leaning into data analytics, higher education presents the greatest human and emotional element in motivating the adoption of these strategies. Using hard data on students, universities will be able to be proactive rather than reactive in helping each student achieve success.

For instance, using variables such as academic records, ID card transactions, or network logs will help more accurately predict when students need assistance or intervention and uncover students who need more or different guidance. Data analytics does not eliminate traditional university counseling and student support services, but rather supplements and increases the effectiveness of these services via more predictive capabilities. Weaving data analytics into the fabric of the university will help reinforce the mindset of all educators that the student comes first, and all efforts should be made to give them greater chances at positive outcomes.

Incorporating data analytics into the decision-making structure of universities gives administrators and educators the chance to learn from previous students to better set a course for the future. Data analytics doesn’t remove the need for human interaction, but can help guide conversations in a better way. It is important to introduce data analytics in an ethical way, however, making students aware of what data points are being collected and why and giving them a chance to opt-out if they desire.

Infinitive has been working closely with higher education institutions to keep them ahead of the competition and evolving marketplace by providing tailored transformation and technology solutions supported by comprehensive change management. Get in touch today and let us help you harness the power of data analytics to quickly transform and innovate for the future.