Impact of AI On Instructional Design – Part 2

EKU Online > Impact of AI On Instructional Design – Part 2

Changing ID Roles

Artificial Intelligence is poised to disrupt many professions, including instructional or learning design. As Instructional Designers (ID), we must be ready to face this disruption and quickly adapt to the impending changes already present. 

In this post series, we will dissect and analyze AI’s impacts and disruptions on instructional or learning design. 

The second impact we will examine is the nature of ID roles. There will be a shift in roles as AI will allow for the automation of routine tasks, such as content curation, creating templates, formatting, test creation, and more. 

Enhanced Multimedia Options

Multimedia and e-learning generation will be, and already is, impacted. Tools for creating slide decks, short videos, and podcasts based on a prompt or script already appeared in early 2023. They may be rudimentary now, but they will be much better soon. The simplicity and the output of generative image AI tools, such as Midjourney and DALL·E 2, already do not bode well for the stock image industry, and it will allow IDs to create multimedia products with relative ease. 

New Skills Will Need to be Developed for an Instructional Designer

New AI skills, such as prompt engineering have arisen. As AI becomes more integrated into the workflows, IDs will need to become proficient in describing tasks that the AI is supposed to accomplish and the various systems that would require these tasks. Other AI-related skills include enhanced data analysis and knowing how to process large datasets. 

Increased Access to Personalized and Adaptive Learning Systems

And finally, the holy grail of learning – personalized and adaptive learning agents. These learning systems were historically costly, and only the selected few could afford their design and development. These systems provide students with an individual learning path or experience by letting them progress through content or a course according to their skills, knowledge, or learning needs.

Instructional designers can custom-tailor these AI-powered learning agents with appropriate knowledge data banks to provide learning solutions through dialogues and content adaptation. Imagine a learning solution that any learner could tap into to get answers to various questions in an instant as they progress through the lesson, course, or training. These agents can be embedded in online classes and corporate training portals. They could deliver just-in-time learning for the modern workforce. 

With these changes in mind, we can see IDs move in the direction of performance consultancy or in the roles of learning business analysts, where they get to make more data-based decisions, needs assessments, and accurate measurements of learning impact or returns on learning. They would still design learning solutions, but some media production tasks may move into the media generation direction, and the design itself becomes rapidly iterative.  

In summary, the impact of AI on instructional design as a profession will be substantial, leading to shifts in roles and responsibilities, simplified multimedia creation and generation, new AI-focused skills such as prompt engineering, and the rise of personalized and adaptive learning agents and systems. While AI presents challenges, it also offers opportunities for instructional designers who can adapt and embrace these modern technologies to create effective and engaging learning experiences.


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