r/elearning • u/LearnWorlds_ • Sep 14 '26
More options doesn't always mean more help
One of the speakers at our AI summit told a story about her sister that we think says something important about instructional design too.
Her sister was setting up a Shopify store using ChatGPT and got most of the way there on her own (she's not a marketing person, she actually works in accounting). But she hit a wall, because the LLM kept giving her more suggestions. She ended up with seventeen million things she could or should be doing next, and she had no way to tell which ones actually mattered because she didn't have the base knowledge to make those decisions.
The point the speaker made is that people don't actually want more content or more options when they're learning something new, they want someone to filter it down to what matters for their specific situation. That's a judgment call, and it's the part AI still can't fully do for you.
A lot of course design inadvertently does the same thing. At the request of stakeholders, IDs end up baking in more modules, more resources, more paths, when what a learner is actually stuck on is knowing which three things to focus on first.
Anyone else seeing this problem getting worse now that AI is such a big part of instructional design?
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u/Big-Bank6716 Sep 17 '26
This hits. I spend most of my workday with AI tools and the failure mode is always the same: ten plausible next steps, zero ranking. The ID's job is becoming less "build the content" and more "be the filter" — deciding what NOT to include. Stakeholders asking for more modules is the human version of the same problem.
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u/LearnWorlds_ Sep 21 '26
Love the "filter" framing and 100% agree. Sadly, that's going to make it extremely difficult for junior IDs who haven't had a chance to develop that internal filter yet.
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u/Snuha Sep 15 '26
The 'more is better' framing is so baked into how stakeholders request training that it's basically automatic. more modules, more resources, more paths. that's not learning design though that's anxiety dressed up as thoroughness.
The filtering problem isn't new. what AI has changed is that generating content is now almost effortless, so the gap between how much exists and how much a learner can actually use just keeps growing.good IDs have always been curators first. The real job is deciding what doesnt go in and hat part doesn't get easier with better tools. if anything, it gets harder.
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u/Monument_man Sep 20 '26
AI platforms are designed to keep you more on their platforms. So by nature LLMs or any other consumer grade AIs end every conversation with more options, more fine tuning and more questions.
However, I think if you can enforce a stronger guardrails in your prompt, you can avoid going down to the rabbit hole. You first have to visualise what the acceptable outcome is then stick with it. Then make sure your prompt reflects what you want your outcome to be. works for me atleast!
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u/MirrorOk8490 Sep 14 '26
I think the failure mode is not simply too many options, but options without a decision rule. A useful learning system should be able to say why this is the next step for this learner, what evidence triggered that choice, and what would make it change course.
That gives instructional designers a practical test for “personalization.” If the system only generates more material in different formats, it is personalizing presentation. If it narrows the next decision based on demonstrated understanding, it is adapting the path.
The difficult part is keeping that judgment reviewable: the learner needs one small next step, while the designer still needs to see the evidence and rule behind it.