Competency K: Learning Experiences
Design collaborative or individual learning experiences based on learning principles and theories.
Introduction
I understand this competency as the difference between presenting information and designing for learning. A slide deck, a handout, or a virtual room full of posters can contain everything a learner needs and still teach very little. Learning happens when the experience is built around what the learner already knows, what they need to be able to do, and how they will practice and show it. Learning theory is what lets a designer make those choices on purpose rather than by habit, and the competency asks that the experiences I design rest on it.
Merrill (2002) reviewed a wide range of instructional design theories and found that they share a small set of principles. Learning is promoted when learners are engaged in solving real-world problems, when their existing knowledge is activated as a foundation for new knowledge, when new knowledge is demonstrated to them, when they apply it with feedback, and when they integrate it into their own work and lives. I use these five principles as a check on my own designs. They are especially useful because they are independent of any one technology. A module that skips demonstration or offers no chance to practice with feedback will be weak whether it is delivered in a classroom, a learning management system, or a virtual world.
Immersive environments add their own possibilities and their own risks. Dalgarno and Lee (2010) identified the features that distinguish three-dimensional virtual environments, namely the representational fidelity of the space and the learner’s interaction within it, and proposed five learning affordances that follow from those features: spatial knowledge representation, experiential learning, engagement, contextual learning, and collaborative learning. They were careful to call these potential benefits. A virtual environment only delivers them when the design calls for them, for example when the learner must navigate a space to understand it, or must carry out a task in a realistic context. A virtual room used as a slideshow offers none of these benefits and adds the cost of a new interface.
Learners also differ by age and experience, and many of the learners I design for are adults. Knowles et al. (2020) describe the principles of andragogy: adults need to know why they are learning something, they bring a reservoir of experience that is a resource for learning, they are oriented toward problems they face, and they are motivated more by internal than external rewards. These principles shape how I write objectives and introductions. An adult learner who does not see the purpose of a module in its first minute is likely to disengage, whatever its quality.
This competency matters to me because instructional design is the center of my professional work. I design instruction for virtual and mixed reality environments, I have built training modules in authoring tools such as Articulate 360 and Adobe Captivate, and I am now designing familiarization and volunteer training for an equine-assisted services program. My background in human factors adds a particular habit: I treat a learner’s confusion as evidence about the design and not as a failing of the learner. The competency matters to the profession because libraries are teaching institutions. Information literacy sessions, technology classes, makerspace orientations, and staff training are all learning experiences, and each is better when it is designed rather than improvised. The evidence below shows me designing an immersive learning game on constructivist principles for learners with dyslexia and attention differences, designing an informal AI literacy program for the public, and designing a self-directed research guide that teaches through practice.
Evidence
My preparation for this competency came from INFO 287-19, Design for Teaching and Learning in Social VR, taught by Dr. Marie Vans, where I evaluated social VR platforms and built the STEMvival game; from my work in adult services at a public library, where I designed and ran programs for the public; and from INFO 254, Information Literacy and Learning, where I studied information literacy instruction and built the LibGuide.
Evidence 1: STEMvival: Winter (immersive learning experience, INFO 287-19)
For INFO 287-19 I designed STEMvival: Winter, a survival scenario that teaches applied science and math to middle and high school students, particularly students with dyslexia or attention deficit disorder who are poorly served by textbooks, lectures, and worksheets. Learners play hikers stranded in a backcountry yurt after a winter storm has damaged their gear and blocked the route home. To survive the night and call for help they must solve three problems: repair a damaged radio by completing a circuit, find their location with a map and a compass that must first be calibrated, and stop the yurt from losing heat by applying what they learn about conduction, convection, and insulation. The experience combined a 3D yurt environment that I built in Spatial.io with Unity, a Canvas course that held the instructional materials and the pre-test and post-test, and two 2D games: a radio conversation with a forest ranger, in which learners choose how to respond to an emergency call, and a grid-map navigation game. I planned the experience through hand-drawn storyboards and a floor plan of the yurt. [Add the term. Confirm which parts were fully built and which remained designs, and what tool you used for the 2D games. Attach the presentation, storyboards, screenshots, and the walkthrough video, uploaded unlisted with captions.]
The project demonstrates design based on learning theory. I grounded STEMvival in constructivism, the view that learners build understanding by acting on problems in context and in conversation with peers, and I designed it to be played as a group where possible. Each puzzle puts the problem first and the content second, which is Merrill’s (2002) first principle: a learner discovers why a circuit diagram or an R-value matters because the radio is dead and the room is getting colder. The scenario also uses the affordances Dalgarno and Lee (2010) describe. Learners move through a space that represents the problem, learn by doing in a realistic context, and work together in a shared world. Activation and demonstration were built in as well. A short guided tutorial, in which a character walks the learner through chopping, gathering, and burning firewood, teaches the controls before any puzzle begins, and an in-game survival manual, a guidebook on the learner’s virtual phone, and an AI guide supply information in text, audio, and visual form. Because the intended learners include students with dyslexia, the design called for dyslexia-friendly fonts, text read aloud, and progressive hints that become more direct with each failed attempt. Badges such as Most Observant, Quick Thinker, and Curious Cat rewarded good play, and joking badges for mistakes, such as Most Frequent First Aid, made failure part of the game rather than a penalty. Building it taught me two lessons I now apply to every design. The narrative took as much effort as learning Unity, and it mattered more than visual fidelity. And the platform itself was a risk: Spatial.io used an older version of Unity, its toolkit did not allow collaborative building, and the platform no longer hosts this kind of experience, so the walkthrough video is now the record of the game.
Evidence 2: Spot the Fake (AI literacy passive program, public library)
In August 2024 I designed and ran Spot the Fake, a weekly passive program in the adult services area of a public library in the Phoenix area. Each week patrons saw two versions of the same item, such as two painted portraits of the same celebrity, each paired with a short biography. Some were made by people and some with generative AI, using deliberately misleading prompts. Patrons marked each item as real or fake on an entry ticket and wrote how they could tell. On Saturday I posted an answer sheet and drew a winner for a $5 gift card from the entries. [Add how many weeks it ran, and attach the poster, one pair of cards, a ticket, and an answer sheet.]
The program demonstrates a learning experience designed for individual learners who choose whether to take part at all. A passive program has no instructor present and no captive audience, so the design has to do the teaching. The portraits and biographies posed a real problem, which is Merrill’s (2002) first principle: deciding whether something is AI-generated is a judgment adults now face daily, not an exercise invented for class. The ticket asked patrons to explain how they knew, which turned a guess into reasoning. The answer sheet supplied the demonstration and feedback that Merrill places after application: it named the tools used to make each fake and the prompts given to them, pointed out the error that gave the AI biography away (it gave the wrong number of children, because the model’s information was out of date), identified the sources of the real items, and closed with tips for the future, such as checking names, dates, and other verifiable facts and remembering that AI can state outdated or invented details with confidence. It ended with an invitation to try a generative AI tool on a current event the reader knows well and judge the result, which is Merrill’s principle of integration. The prize gave adults a reason to take part, but the design kept the learning in the reasoning and the answers rather than in the reward. The program reached beyond its intended audience as well. A teen participant told me he loved the game and that it was important work to get the word out about AI. [Add anything else you observed, such as which items fooled the most people.]
Evidence 3: Understanding Extended & Virtual Reality (LibGuide, INFO 254)
I built this LibGuide for INFO 254, Information Literacy and Learning, and it is published on the SJSU School of Information’s LibGuides site (https://ischoolsjsu.libguides.com/c.php?g=1496514), last updated in October 2025. It teaches newcomers how to research extended and virtual reality, a field whose vocabulary is unsettled and whose research is scattered across computer science, education, and health. The guide has seven pages: a home page, Key Words and Search Strategies, Books and Foundational Knowledge, Database Recommendations, Journal Resources, a Citation Guide, and Exercises. I also use it in my volunteer work with the Immersive Learning Research Network. [Say how you use it for iLRN, for example as a starting point you send to new volunteers or members, and whether you changed anything for that audience.]
The guide demonstrates the design of an individual, self-directed learning experience based on learning principles. A LibGuide is easy to treat as a list of links, and a list of links teaches very little. I designed this one as a sequence of instruction, and it follows Merrill’s (2002) principles closely. The home page opens with a short list of what the learner will be able to do, which tells adult learners at once why the guide is worth their time, as Knowles et al. (2020) advise. A poll asks what brought the learner to the topic, and a “Where should I start?” section sends learners down different paths depending on their situation: brand new to the topic, needing current research, struggling to narrow a topic, or needing to cite sources. That is Merrill’s principle of activation, since the guide meets learners where they are instead of assuming one starting point. Demonstration comes through three short videos, on narrowing a topic, exploring databases, and citing sources that do not fit standard formats, and through downloadable infographics: a research cheat sheet, a timeline of extended reality, and a one-page explanation of peer review.
Application is where the guide moves furthest from a list of links. The Exercises page asks learners to work in real research tools rather than read about them. One exercise has them find three recent peer-reviewed articles on virtual reality in education or training in IEEE Xplore and characterize each by venue, platform, and method. Another sends them to arXiv to compare preprints with peer-reviewed articles and trace whether a recent preprint has since been formally published. A third has them navigate the ACM Computing Classification System down to its virtual reality categories to see how the field’s research is organized. A game built in Canva gives practice in constructing Boolean searches. Each exercise ends with questions that require the learner to analyze what they found, which builds the evaluation skills the field needs as much as the search skills.
Conclusion
I will apply this competency by beginning every design with the learner and the task, checking each module against Merrill’s principles, and using immersive features only where they provide an affordance the learning needs. My next application is the equine-assisted services project, where I am designing a virtual familiarization experience and a take-home kit to prepare new volunteers and participants before they reach the barn. I also expect to use this competency in instructional design and training roles in libraries, simulation, and corporate learning. To stay current I will follow the Immersive Learning Research Network and its conference proceedings, Educational Technology Research and Development, and the Association for Talent Development. [Add any instructional design community or newsletter you follow.]
References
Dalgarno, B., & Lee, M. J. W. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10–32. https://doi.org/10.1111/j.1467-8535.2009.01038.x
Knowles, M. S., Holton, E. F., III, Swanson, R. A., & Robinson, P. A. (2020). The adult learner: The definitive classic in adult education and human resource development (9th ed.). Routledge.
Merrill, M. D. (2002). First principles of instruction. Educational Technology Research and Development, 50(3), 43–59. https://doi.org/10.1007/BF02505024