Enhance personalized learning experiences with data-driven insights

The promise of educational technology is not just in digitizing the learning experience. When edtech is deployed to its fullest extent, it can add new and exciting capabilities that improve experiences for learners and instructors alike.

This concept applies to personalized learning — by using digital platforms, it's possible to customize the content served to students to make sure it suits their learning styles, current progress, and overall needs. While tailoring a lesson plan to each individual's requirements would have previously been a time-consuming and laborious manual process, it's now streamlined and effective. Data is the key: companies that excel in generating and applying data-driven insights in education have a strong position to shape the future of customized content.

Understanding data-driven personalized learning

Personalized learning is so powerful because there's more than one aspect of modern, digital learning eligible for customization. When edtech organizations incorporate personalization into their tech platforms, they can implement solutions such as content tailored to users' interests and needs, as well as courses with variable paces that adjust to fit learning styles.

Educators using these data-infused software platforms don't have to rely on automation to customize learning content, either. They can view analytical results themselves, understanding what their students respond to and which methods aren't having the intended results. These insights can shape the curriculum for future years, delivering a culture of continuous improvement and optimization.

The data that feeds analytics algorithms in the educational space includes a wide range of inputs, covering every corner of the experience. Commonly used data types include:

• Learner behavior data: The way in which learners interact with lessons, meaning the time spent on each lesson, their perceived engagement with the material, and more, is a useful signal. By viewing the way users move through lessons, educators can determine which pieces of content are having their intended effect.
• Performance data: When users complete interactive quizzes or more extensive tests at the ends of units, their results tell educators how much information they've retained. By measuring which subjects and specific concepts students are most familiar with, course designers can adjust their focus, strengthening weak areas.
• Social data: Ideally, students won't work entirely alone. When they collaborate digitally in group settings, course participants create a trail of data that shows how well they are able to apply what they've learned in a collaborative setting. These results can send strong signals about students' familiarity with the concepts as well as their capacity for teamwork.

With such strong signals coming from multiple inputs, it's clear that educators have plenty to work with when shaping the content of their courses for optimal results.

Benefits of using data for personalization

Across all types of learning, from the beginnings of K-12 education to supplemental professional training and everything in between, there is a need to optimize experiences with edtech. This is the promise of education data analytics: Educators can take significant benefits from software that analyzes data to generate personalized experiences.

Some of the specific effects of personalized education, which have wide applicability for educators include:

• Customized learning pathways: It's one thing to say that every student learns best when given a personalized lineup of coursework, and another to put this idea into practice. Data analysis makes customization feasible, allowing educators to automatically generate learning pathways that serve lessons to students that suit their specific needs, areas for improvement, learning styles, and aptitudes with various methods.
• Improved engagement and motivation: Presenting an education tailored to individual preferences and needs is a way to keep students optimally engaged with their work. When lessons presented to each learner are customized to suit that person's learning style and deliver meaningful information, there's less risk of students becoming discouraged when presented with work they don't find meaningful.
• Timely support and intervention: Educators with access to advanced data streams can use predictive analytics algorithms to determine when students are struggling with their work. Early warning factors allow instructors to take access and intervene, providing assistance and guidance to students. Rather than waiting for pupils to fail a test or course before taking action, it's now possible to see the warning signs early and offer tailored assistance.

Educators with software that implements data-based personalization can deliver experiences that conform to their students' needs and preferences and evolve to stay consistently relevant. This represents a major advantage over less data-rich approaches.

Improving personalized learning with data

While the advantages of personalized learning are considerable, unlocking these benefits isn't automatic. Leaders need to think through how they will apply personalization to their digital learning solutions.

Strategic uses for data-based personalization

Useful strategic approaches for educational organizations that want to introduce customization into their offerings include:  analyzing learner data to divide students up into groups based on progress and skill level, with each of these groups receiving its own tailored materials to help those learners thrive.

Adaptive learning technology that serves customized learning content is a powerful part of a data-driven educational strategy. Personalized learning platforms can quickly use students' assessment results and behavioral signals to determine the content of the next lesson in real time. With these digital tools in place, learners will never waste time on unsuitable lessons.

This technological component of personalized learning should be supported by organizational strategies. Leaders who come up with plans to integrate tech tools deeply into their educational offerings are ideally positioned to serve their students.

Practical personalization examples

While personalization in edtech may seem like the future, it's already arrived for many educators and technology providers. This means there are useful examples of the technology in action. These practical use cases can serve as inspiration on their own or point to even more in-depth applications as capabilities evolve.

Some existing uses for personalized learning include adaptive quiz adjustments that adjust to reflect the current state of learning and provide useful insights on overall success levels. Real-time progress tracking dashboards represent another useful tool type. These give educators up-to-date information on class progress in an easy-to-interpret visual form, making it easier to create targeted support plans for students. Content recommendation engines are also helpful parts of edtech systems, serving up optimized educational journeys for all students.

Powerful tech platforms give educators new ways to administer their courses. They're still in charge, but they now have powerful solutions that provide them with guidance and help them complete their educational objectives.

Use data-driven insights in your next educational technology project

Data is the fuel for powerful, next-generation experiences in education. This isn't a surprising fact considering the general trajectory of business. Equipped with more data than ever before, at a faster pace, companies of all kinds are becoming smarter and more automated. Education is not an exception to this overall trend.

Edtech platform designers and developers can make use of this technological revolution, implementing practical tools and updating their strategies to accommodate the changes. The end result can be engaging, personalized learning experiences that deliver more information while preventing students from falling through the cracks.

Enhance your educational technology with data-driven insights that improve learning and engagement. Collaborate with Transcenda for design and engineering services that create effective, customized solutions for your users. Contact us to learn more or get started on your next project.