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Artificial intelligence and the environment: Putting the numbers into perspective - Artificial intelligence
Artificial intelligence and the environment: Putting the numbers into perspective - Artificial intelligence
Using AI does use energy, water, and other resources. But when you consider it as part of your decision-making, it's important to put it in perspective. Being on a Zoom call or watching Netflix for an hour uses more electricity and water than prompting ChatGPT numerous times.
·nationalcentreforai.jiscinvolve.org·
Artificial intelligence and the environment: Putting the numbers into perspective - Artificial intelligence
Interactive Activities Done Properly: What the Science Actually Allows Us to Do | Learning Development Accelerator
Interactive Activities Done Properly: What the Science Actually Allows Us to Do | Learning Development Accelerator
Matt Richter dives deep into the science of how to align activities with the goals for learning and what people need to practice or accomplish.
When a metaphorical game succeeds, it succeeds because it creates structurally similar cognitive demands—not because it is fun, novel, or symbolic.
In other words, the brain doesn’t care about your metaphor. It cares about what it has to think about during the activity.
From a cognitive architecture viewpoint, activities are not designed to “create engagement,” “break up the session,” or “get people talking.” Those may be side benefits, but they are never the goal. The purpose of an activity is to create conditions where the learner must activate, retrieve, apply, or integrate the target schema.
When aligned to cognitive architecture, interactive activities can beautifully satisfy SDT’s psychological needs: Autonomy: choosing strategies, making decisions Competence: clear and informational feedback, achievable challenge Relatedness: coordinating, negotiating, helping But motivation is a multiplier, not a substitute
·members.ldaccelerator.com·
Interactive Activities Done Properly: What the Science Actually Allows Us to Do | Learning Development Accelerator
Bias in AI: Examples and 6 Ways to Fix it in 2025
Bias in AI: Examples and 6 Ways to Fix it in 2025
Examples of bias in AI in image generation, recruiting tools, voice recognition, and other areas. The solutions here focus primarily on adjustments of the AI systems and debiasing strategy rather than on the level of individual prompts to improve representation. If you're looking at your overall strategy for AI, how you address bias has to be part of the plan.
·research.aimultiple.com·
Bias in AI: Examples and 6 Ways to Fix it in 2025
Why AI Video Avatars are NOT the Next Big Thing in L&D
Why AI Video Avatars are NOT the Next Big Thing in L&D
Heidi Kirby digs into the research about AI video avatars (excluding the vendor research). The support really isn't there. I've anecdotally seen lots of complaints about how they sit in the uncanny valley. But even as the video avatars get more realistic, is a talking head video really the best instructional method? Of course not! There wasn't a lot of buzz about talking head videos before AI. Why is there so much buzz now? (Interactive video avatars for scenarios are a separate question and not addressed by this article.)
Despite their increasing use, there's limited evidence that AI-generated avatars significantly improve learning outcomes.
·getusefulstuff.com·
Why AI Video Avatars are NOT the Next Big Thing in L&D
Supporting Learning with AI-Generated Images: A Research-Backed Guide - MIT Sloan Teaching & Learning Technologies
Supporting Learning with AI-Generated Images: A Research-Backed Guide - MIT Sloan Teaching & Learning Technologies
Suggestions and examples for using AI-generated images in meaningful ways to support learning, without adding confusing or distracting images. Consider cognitive load and the purpose of your images.
A study by Sung and Mayer (2012) suggests that any graphic in a learning experience will fall into one of these three categories: Instructive images: These visuals directly support learning and facilitate essential cognitive processing of core concepts. For example, a diagram illustrating Porter’s Five Forces can help students better understand this business strategy framework. Decorative images: These graphics enhance aesthetics but don’t influence learning. For example, an image of a business handshake can be visually appealing but won’t support or obstruct students’ understanding of negotiation strategies. Distracting images: Sung and Mayer call this category “seductive” images. While these visuals may relate to the topic, they impede learning because they require extraneous cognitive processing. As an example, consider a complex organizational chart of a full corporation in a lesson on team leadership. The image connects broadly to the lesson but also highlights a lot of irrelevant details, distracting students from the key concepts.
·mitsloanedtech.mit.edu·
Supporting Learning with AI-Generated Images: A Research-Backed Guide - MIT Sloan Teaching & Learning Technologies
Delayed and Immediate Feedback in the Classroom: The Results Aren’t What Students Think!
Delayed and Immediate Feedback in the Classroom: The Results Aren’t What Students Think!
Megan Sumeracki summarizes research on delayed and immediate feedback on homework assignments. The "immediate" condition here means "immediately after the due date" rather than "immediately after completing the work." Students who received delayed feedback did about 1 grade level better on the exams. However, they felt that the delay either didn't help them or hurt their learning. Student perception of what helped them most didn't align with what actually worked.
Logically if we think about feedback as correcting errors, then it makes sense that we would want pretty immediate feedback. But if we think about feedback as another presentation of the information, then a space ought to improve learning.
·learningscientists.org·
Delayed and Immediate Feedback in the Classroom: The Results Aren’t What Students Think!
How People Are Really Using Gen AI in 2025
How People Are Really Using Gen AI in 2025
How do people use generative AI? I was surprised at how much of the use is for interactions like therapy and personal interaction. "Personal and professional support" was the top broad category in this research, which also includes tasks like organizing your life, resolving disputes, building lists, etc. "Content Creation and Editing" was second, followed by "Learning and Education." The popularity of learning on the list was also an interesting finding.
“Personal and Professional Support” is now the largest theme by far, stealing most of its new ground from “Technical Assistance & Troubleshooting.”
·hbr.org·
How People Are Really Using Gen AI in 2025
The power of generative marketing: Can generative AI create superhuman visual marketing content?
The power of generative marketing: Can generative AI create superhuman visual marketing content?
This abstract of a marketing research paper explains how they compared AI-generated images and ads to human-created ads. The AI images were not just comparable, they were better than what people created. While this research is specific to marketing, I think it's relevant to images we use in training and elearning.
First, we prompt seven state-of-the-art generative text-to-image models (DALL-E 3, Midjourney v6, Firefly 2, Imagen 2, Imagine, Realistic Vision, and Stable Diffusion XL Turbo) to create 10,320 synthetic marketing images, using 2,400 real-world, human-made images as input. 254,400 human evaluations of these images show that AI-generated marketing imagery can surpass human-made images in quality, realism, and aesthetics. Second, we give identical creative briefings to commissioned human freelancers and the AI models, showing that the best synthetic images also excel in ad creativity, ad attitudes, and prompt following.
·papers.ssrn.com·
The power of generative marketing: Can generative AI create superhuman visual marketing content?
Inclusive Learning Survey
Inclusive Learning Survey
Will Thalheimer and Ingeborg Kroese have developed survey questions to help measure how inclusive learning experiences are. You can read about the research, development, and pilot process on the website. The survey questions are available for free with a CC license.
·inclusivelearningsurvey.org·
Inclusive Learning Survey
The politeness effect: Pedagogical agents and learning outcomes
The politeness effect: Pedagogical agents and learning outcomes
Using polite language in elearning improves learning outcomes.
The polite version yielded better learning outcomes, and the effect was amplified in learners who expressed a preference for indirect feedback, who had less computer experience, and who lacked engineering backgrounds. These results confirm the hypothesis that learners tend to respond to pedagogical agents as social actors, and suggest that research should focus less on the media in which agents are realized, and place more emphasis on the agent's social intelligence.
·sciencedirect.com·
The politeness effect: Pedagogical agents and learning outcomes
Reflecting on Research and Practice
Reflecting on Research and Practice
How do we put research into practice in L&D? Clark Quinn reflects on the work of the LDA (Learning Development Accelerator) to improve the field of L&D with approaches informed by science and research. Clark discusses how science is always improving, so our understanding can change over time. Research can also be misleading or biased (or shared in misleading ways). Still, we can be more effective in our work with evidence-informed practices.
·linkedin.com·
Reflecting on Research and Practice
(PDF) Storifying Instructional Videos on Online Credibility Evaluation: Examining Engagement and Learning
(PDF) Storifying Instructional Videos on Online Credibility Evaluation: Examining Engagement and Learning

This study researched whether adding story elements to an instructional video affects motivation, emotional engagement, and learning. In the research, they explain that they did not find any difference between a well-produced instructional video and a storified instructional video.

However, the storified video feels very artificial to me. This isn't a story about a relevant character the learners can identify with who uses the concepts in realistic situations (or even slightly exaggerated ones). This is about a fake detective agency. I'd be cautious about assuming this research applies to realistic stories as well.

·researchgate.net·
(PDF) Storifying Instructional Videos on Online Credibility Evaluation: Examining Engagement and Learning
25 Neuroscience Myths
25 Neuroscience Myths
Lots of myths from pop psychology about neuroscience (plus a few from cognitive psychology or other non-neuro fields). While this isn't specific to learning, many of these myths are shared uncritically in L&D circles.
Neuroscience techniques can only reliably answer “how” people behave or process information, but they should never answer “why” people behave the way they do.
·medium.com·
25 Neuroscience Myths
Communities of Inquiry
Communities of Inquiry
<p>The purpose of this project is to support a personally meaningful and educationally worthwhile learning experience. Central to the study introduced here is the <a href="http://communitiesofinquiry.com/sub/coi_model.html">model of a community of inquiry</a> that constitutes four elements essential to an educational experience: </p> <ul> <li><a href="http://communitiesofinquiry.com/sub/cognitive.html">Cognitive Presence</a></li> <li><a href="http://communitiesofinquiry.com/sub/social.html">Social Presence</a></li> <li><a href="http://communitiesofinquiry.com/sub/teaching.html">Teaching Presence</a></li> <li><a href="http://communitiesofinquiry.com/sub/methodology.html">Methodology</a></li></ul>
·communitiesofinquiry.com·
Communities of Inquiry