How to Empower Your Educational Decisions With Learning Analytics

Higher education institutions need to be at the forefront of technology transformations or they risk being left behind. Students will naturally seek learning opportunities that help them understand and harness today’s new tools (like AI, VR, and hybrid learning) in order to help them achieve their professional goals.

Embracing technology and leveraging its potential equips students with the skills and knowledge they need to thrive in the digital age. By understanding and incorporating innovative learning technologies, higher education institutions can continue to attract learners and pave the way for transformative educational experiences that meet the evolving demands of the modern world.

And in order to evolve, you need to be able to make data-backed decisions. As the saying goes, "What cannot be measured, cannot be improved," and the field of higher education is no exception. The use of learning analytics has emerged in recent years to help drive the crucial mission of guiding students to academic excellence.

Keep reading to find out how!

Learning Analytics for Data-Driven Decision-Making

The ability to collect, analyze, and interpret educational data has always been an essential component of learning. Learning analytics technology enables instructors and institutions to use student data—often obtained from a learning management system (LMS)—to inform decision-making and improve educational outcomes. Here are two ways this can work:

• By harnessing the potential of learning analytics, institutions can gain valuable insights into student learning, optimize instructional strategies, and enhance learner success.
  
• By analyzing data like student performance on assessments and engagement with content modules, educators can identify patterns, trends, and areas in need of improvement, empowering them to make informed decisions for the future and tailor instructional approaches to best serve their learners.

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Analytics Help Personalize Learning Experiences

One of the key advantages of learning analytics is the ability to personalize instruction based on individual student needs. By analyzing student data, educators can gain insights into students’ strengths, weaknesses, and learning preferences.

Instructors can then use the information to adapt learning resources and provide targeted interventions that address students’ specific needs, ultimately enhancing their learning experiences and outcomes.

Let’s say an instructor includes a ten-minute video with each online lesson for a particular course, followed by an assessment activity. The videos contain a lot of helpful information, but many of the students aren’t scoring well on these assessments. Learning analytics data embedded in the institution’s LMS shows the instructor that the majority of the students stop watching most videos after the first four minutes.

Although the instructor would like for their students to watch the full ten minutes of content, the data demonstrates that many students simply won’t commit to that length of time (for whatever reason). Rather than fight an uphill battle, the instructor can edit their videos to be shorter than four minutes, ensuring that the most vital information is covered quickly and efficiently so learners can benefit from the resource.

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Solve Problems While They’re Still Small

Learning analytics data is also useful for identifying at-risk students and providing timely interventions. It’s very common for courses in higher learning institutions to consist of a handful of assignments and two or three high-stakes assessments. If a student struggles with the material early on in a course, it can become increasingly challenging for them to “bounce back” and catch up with their peers.

Monitoring student data like course performance and engagement metrics enables instructors to identify learners who are struggling academically or disengaging from their studies. Early intervention strategies can then be implemented to provide personalized support, foster student success, and (hopefully) improve retention rates.

While the information collected with learning analytics technologies can significantly benefit learners, institutions must ensure that student data is collected, stored, and used in a responsible and secure manner. Learners need to be made aware that their data is being collected, and institutions must adhere to privacy regulations and obtain proper consent.

Transparency and clear communication with students about data collection and usage are essential to building trust and maintaining ethical standards in learning analytics.

In summary, educational analytics empowers us to gather data that was previously elusive or challenging to quantify, ranging from overall class retention to individual student progress. Armed with this valuable information, we can implement targeted improvements both at a macro and micro level within our classes.

Moreover, this newfound ability to identify specific student challenges from the outset enables us to proactively address them before they escalate. Gone are the days of waiting until the final exam to discover that a student needed to progress at a different pace than the rest. It's not just their grades that are at stake but also their self-confidence, and as educators, we understand the immense value of nurturing that.

FURTHER READING ON PERSONALIZED LEARNING TACTICS | ‘5 Ways Open LMS’s Personalized Learning Designer (PLD) Enhances Online Education’