
Instructional Design Topic & Learning Gap
Artificial Intelligence and Instructional Design
AI Overview
AI, Artificial Intelligence, has impacted Instructional Design and will continue to do so into the foreseeable future. As such, it is important to understand the nature of AI, and the impact of AI on Instructional Design.
AI can be defined as “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” (Copeland, B.J., 2024). It can be said that AI dates back to the 1940s, with some of the older applications being for discovering mathematical truths and playing chess (Copeland, B.J., 2024). AI uses massive amounts of data, finds patterns and relationship, and in a sense, learns. “Think about it this way: just as we humans learn from our experiences and adapt to new situations, AI can do the same.” (Arnold, 2024).
There are various types of AI. The two broad categories in use today are Reactive Machine AI and Limited Memory AI (IBM Data and AI Team, 2023). Reactive Machine AI includes things like playing games with clear, but complex rules and generating recommendations based on history. Limited Memory AI includes things like chatbots and generative AI that is used to produce text, images, data sets, etc. (IBM Data and AI Team, 2023; Lawton, n.d.). As will be discussed below, several of these types of AI could be leveraged in Instructional Design.
AI and Instructional Design
Using AI in Instructional Design
There are various ways that AI tools can assist with instructional design. A few of these will be highlighted here. One potential way AI could be used is by creating adaptive learning opportunities with Reactive Machine AI generating recommendations for learning paths. Using generative AI to assist with writing content is another way to leverage this technology in instructional design. Additional AI tools could be used like a chatbot or similar technology to serve as a first level virtual tutor within a course.
Choosing Tools to Use
With so many potential applications in Instructional Design, and so many potential uses out there, an instructional designer might logically think, “What’s the best tool?” AI may eventually evolve such that certain tools are better for ID, but for now, perhaps the “best” would be those which we can trust. “Seeing value from analytics and emerging technologies such as AI begins with trust in the data. That trust relies on how data is collected, shared, protected and used.” (Data, Analytics, & AI: How Trust Delivers Value, 2019). While any AI content or other assistance should always be checked (at least at this point in time), the more an Instructional Designer trusts a tool to have accurate data to draw from, the more confidence they will have in the outcome of the AI tool. So, trust in the data, may be a key criteria when deciding what tool(s) to use in Instructional Design.
Citing the Use of AI
Another important area for Instructional Designers to consider is attribution of the AI tool/output. When we use AI as part of our course creation how show that be acknowledged? The guidelines of how to cite AI tools are still evolving. So, an Instructional Designer can look at guidance for several of the main style types like APA and MLA, while others may not yet have much guidance. Regardless, it’s important to remember to check regularly updates on acknowledging the contribution of AI to your work.
Is an Instructional Designer Still Needed?
As is pointed out in the podcast “Why AI Can’t Replace Instructional Designers,” Instructional Designers will still be needed into the “foreseeable future” (Peck, n.d.). AI tools currently aren’t perfect, and a rational experienced individual is needed to oversee the process.
AI also brings a whole new learning gap that ID could help address. As AI tools are constantly evolving, people will need to keep up with the technology that is the best fit. Instructional Designers will be needed to update training for the AI tools.
Arnold, Sunita. (2024, March 27). Artificial Intelligence: What It Is and Why It Matters. https://www.linqto.com/blog/artificial-intelligence-what-is-it-why-it-matters/
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Copeland, B.J. (2024, April 7). Artificial Intelligence. Retrieved 4/8/2024 from Britannica.com
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Data, Analytics, & AI: How Trust Delivers Value. (2019, January 08). MIT SMR Connections. Retrieved 4/8/2024 from https://sloanreview.mit.edu/mitsmr-connections/data-analytics-and-ai-how-trust-delivers-value/
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IBM Data and AI Team. (2023, October 12). Understanding the different types of artificial intelligence. https://www.ibm.com/blog/understanding-the-different-types-of-artificial-intelligence/
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Lawton, G. (n.d.). What is Generative AI? Everything you need to know. Retrieved 4/8/2024 from https://www.techtarget.com/searchenterpriseai/definition/generative-AI
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Peck, D. (n.d.) Why Can’t AI Replace Instructional Designers. Blogpost. Retrieved on 4/7/2024 from YouTube.com.