Training projects can move into development before the team has worked through the learning design.
A subject-matter expert may arrive with accurate content and a clear sense of what employees need to know. At that point, the team still has important choices to make. What should learners be able to do when the training is over? What experience will prepare them to do it? Where should they practice, receive feedback, and demonstrate what they have learned?
If those decisions are not made explicitly, they can get lost during development. Topics become modules. Available media influence activities. An assessment may be added after much of the course has already taken shape. This is what we mean by bad design: the course may be polished, accurate, and easy to navigate while the learning decisions underneath it were never fully examined.
Once in production, revisiting those choices becomes more difficult. Decisions about screens, media, navigation, technology, and deadlines now compete for attention. Assumptions that were never discussed may become part of the finished training.
Instructional design involves a series of interconnected choices, and each one affects the others. A design process can help guide those choices, but some may remain unresolved.1 When that happens, the tools, timeline, available resources, and other production constraints can end up determining the outcome.
If the team leaves a design choice unresolved, it will still be settled—by the tools, constraints, timelines, or production decisions that come later.
Consider a manager training program intended to prepare supervisors for difficult performance conversations. The content may cover relevant HR policies, common mistakes, documentation, and the basic steps of the conversation. A learning team could organize those topics into modules, add a demonstration, and finish with a multiple-choice assessment.
That structure may cover the content, but the expected performance is more complex than recalling the steps in a process. The supervisor has to recognize a performance problem, decide how to approach it, communicate clearly, respond to the employee, and adjust as the conversation develops. If the training never gives learners an opportunity to work through those actions, then it doesn’t prepare them for the actual task.
Learning outcomes, learner activity, instruction, and assessment operate as parts of the same system. When they point toward different kinds of performance, improving one component does not necessarily correct the others. Those mismatches may not be obvious until later, when the team has to decide what learners will actually do to demonstrate success. By then, much of the course may already be built around content rather than the performance it was intended to support.
A stronger design starts with what learners are expected to do, then aligns the learning activities and assessment to that outcome.2
Aligning the course to the intended performance means making deliberate choices about how each part of the learning experience supports that performance. Feedback, for example, can take very different forms depending on what learners need to do. Research on formative feedback shows substantial variation in its effects; its usefulness depends on who the learner is, what they are doing, what feedback they receive, and when they receive it.3
In the manager training example, a learner might choose how to respond to a fictional employee and then receive an explanation of why that response could escalate the conversation. The learner could revise the response and try again. In another design, a facilitator might observe a role-play and coach the learner through the exchange.
Both approaches include feedback, but they create different learning experiences and require different resources. The appropriate choice depends on the intended outcome, the learner, and the conditions in which the training will operate.
Practice, information, assessment, interaction, and technology require the same kind of attention. Each element has a function within the learning environment, and each affects the others. Design is the work of deciding how those pieces should operate together.1,2
Making these decisions is only part of the design process. The people involved also need a way to observe and discuss how the pieces fit together.
A subject-matter expert may understand the performance learners need to achieve, while a designer is thinking about practice and feedback and a program manager is considering operational constraints. Even after a productive meeting, each person may leave with a somewhat different picture of the training they agreed to build.
Visual design methods give those ideas a shared place to develop. Visual notation supports planning, communication, testing, and idea generation because designers can document an idea, examine it, change it, and refine it as a design develops.4
Learning Environment Modeling™ (LEM) applies that approach specifically to learning environments. LEM uses a shared visual language to represent how a learning environment is intended to work, giving the people involved a common model they can examine, discuss, and revise.5
A content outline can show topics and sequence, but it may say little about what learners will do with the content. A written description can explain the intent of a course while leaving the relationships among its parts difficult to see. A finished module makes those relationships concrete, but by then the team has already invested time and resources in development.
A model brings those decisions into view earlier, when the team can still discuss and change them without rebuilding the course.
Once the design is visible, the team is able to work through how the learning environment should function.
LEM uses a set of visual building blocks to represent Information, Dialogue, Feedback, Practice, and Evidence. Designers can also show the context in which learning occurs.5
Image alt. text: Five Learning Environment Modeling building blocks: Information, Dialogue, Feedback, Practice, and Evidence.
Together, those building blocks create a model of the learning experience. The team can see where learners encounter information, where they practice, how feedback is provided, where dialogue contributes to learning, and what evidence will demonstrate that learning has occurred. The relationships among those elements are visible on the same canvas, making it easier to examine and revise the design before development is complete.5
Those choices begin to define the learning environment. Modules, videos, activities, job aids, and technologies can then be selected and developed to support it.
Because the design is visible, everyone involved can work from the same model. A subject-matter expert can observe how content contributes to the intended performance. A developer can see why an activity exists and what it is meant to accomplish. Stakeholders can question or revise a choice while it is still part of the design rather than after it has been built.
Learning Environment Modeling is a foundation of LX Studio’s approach to Learning and Development Services. Many of the tools and canvases we use build on the same visual language and design principles, giving our work a consistent way to make learning decisions visible and collaborative.
Clients come to us at different points in their learning projects. Some clients have content that needs to become training. Others have an existing course that is not producing the results they expected. Sometimes the starting point is a performance problem that has not yet been translated into a learning solution.
This visual design process gives the team a way to examine the important choices together. What should learners be able to do? What will help them get there? What information, practice, feedback, dialogue, and evidence belong in the experience?
Once those decisions are clear, the team has a stronger foundation for development. Choices about content, media, technology, accessibility, activities, and other learning resources can now be tied to the way the learning environment is intended to function.
The result is a development process shaped by deliberate design decisions instead of decisions made as the course is being built.
Learn more about LX Studio Learning and Development Services and how we use a collaborative design process to turn learning problems into working solutions.
1 Gibbons, A. S. (2014). An Architectural Approach to Instructional Design. Routledge.
2 Biggs, J. (1996). Enhancing teaching through constructive alignment. Higher Education, 32(3), 347–364.
3 Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153–189.
4 Hokanson, B. (2008). The virtue of paper: Drawing as a means to innovation in instructional design. In L. Botturi & S. T. Stubbs (Eds.), Handbook of Visual Languages for Instructional Design: Theories and Practices. Information Science Reference.
5 Dodd, B., & Gillmore, J. (2018). Learning Environment Modeling™: Redefining Learning Environment Design. University of Central Oklahoma, Institute for Learning Environment Design.
AI Use Disclosure: This article was developed with the assistance of generative AI for drafting, refinement, and editorial support. The author reviewed, revised, and vetted the content and takes responsibility for the accuracy, conclusions, and final published version.