Instructional Design and Technology Concepts for Students

I’m often asked what field my doctorate degree is in. When I respond that my area of specialization is instructional design and technology, a puzzled look is a common reaction. “Technology? Maybe you can help me with my computer…” “Yes, I probably can,” I reply. “But it’s more about working to improve the design and delivery of instructional content for improved performance,” which elicits even more bewildered looks. With this in mind, here’s some of the work we do, including contemporary trends that are present in the field. 

The primary goal of instructional design and technology (IDT) is to maximize the effectiveness, efficiency, and appeal of a given learning experience.

>>Read More: What Is Instructional Design and Technology?

As practitioners in the field of instructional design and technology, we recognize that not all students learn at the same pace or in the same way. Increasingly, technology is being leveraged to modify and individualize the traditional methods for instructional delivery.

There are two methods that continue to develop in the IDT profession, which include adaptive learning and personalized learning. Adaptive learning applies user data and analytics to a path of study, while personalized learning allows students increased independence in formulating their learning experience.

This article considers both of these approaches as well as related topics.

Growing Trends in Instructional Design and Technology

Adaptive Learning

Adaptive learning operates under the premise that technology can adjust learning in response to previous performance, which will result in an optimized learning experience. In effect, instructional content is arranged and delivered based on a user’s response to assigned tasks and activities. Performance data is captured throughout instruction, allowing tools to adjust lessons based on the learner’s progress.

In the instructional design and technology programs at Purdue Global, students can explore courses that focus on design and development models relevant to adaptive learning technologies.

Personalized Learning

Closely related to adaptive learning — yet slightly different in scope — is the personalized learning approach, which tailors individual learning in response to a student’s demonstrated skills, areas for further development, and interests.

One distinction between personalized and adaptive learning approaches is that in personalized learning, the direction of instruction is determined more based on personal interests and preferences toward learning. Also, the pace of instruction is more often determined by the learner when compared to adaptive learning.

Adaptive learning can be compared to an app that assists with navigation, allowing users to arrive at their destination by taking the most effective route. Personalized learning, on the other hand, is more akin to creating your own music playlist on an app.

While both respond by constructing individualized learning experiences through the use of technology, one approach creates a path in response to performance, while the other involves students in shaping their own learning experience.

At Purdue Global, students immerse themselves in the design, development, and evaluation of materials and media necessary to meet the needs of individuals in settings including higher education, corporate, military, government, and nonprofit environments.

Learner Analytics

Both of these methods rely heavily on the use of learner analytics, which refers to data that is collected and analyzed based on how users interact in their environments.

Today’s learning management systems (LMS) track individual user movement within the learning environment and the resulting wealth of data that can (and should) be routinely analyzed. Doing so helps one gain an improved understanding of the broader learning landscape and to discover opportunities for improving learning outcomes.

Two of my recently published investigative efforts focused on the usefulness of learner analytics in the higher learning setting, including the examination of whether online learner analytics of asynchronous discussions might be a predictor of final grades and whether pre-term course access correlates with online learner performance.

The Future of Instructional Design and Technology

Going forward, the trends noted above will continue to converge as new generations of learner management systems evolve. The Web CT Campus Edition version from the start of the millennium is long gone, and hundreds of platforms have since emerged. The newest iteration of the systems is the learning experience platform (LXP). LXPs provide elements of adaptive and personalized learning experiences that incorporate AI and learner analytics.

An interest that was once limited to businesses gaining an improved appreciation for consumer behavior, data analytics are now being interpolated to inform instructional design decisions. Instructional designers would be amiss to overlook the value of the rich data in the design and development effort, especially since it is so widely available.

Similarly, students in the instructional design and technology programs have the opportunity to master technical, pedagogical, and project management skills through application-based learning experiences.

Grow Your Instructional Design and Technology Career With Purdue Global

If you’re looking to advance your career, learn about the online Master of Science in Instructional Design and Technology as well as the online Graduate Certificate in Instructional Design and Technology at Purdue Global. Reach out today for more information.