DOGMATIC 1.0: Where Mindful Design Meets Modern Momentum

Dogmatic Fishbone

When it comes to building meaningful learning experiences, the world of instructional design has no shortage of expert blueprints. ADDIE is often the starting port: it guides designers through Analysis, Design, Development, Implementation, and Evaluation. It is a linear progression lauded for its structure and clarity, and mirrors the once-dominant waterfall project management approach. In contrast, UDL (Universal Design for Learning) shifts the spotlight to learner variability, emphasizing accessibility and engagement for every student. Backwards Design flips the planning process by starting with the end in mind, anchoring every activity to clear learning outcomes and assessments. There’s also Dick and Carey, with its systems view, and models by Gagné and Merrill that stress events of instruction and problem-centered learning, respectively. Each of these frameworks offers strengths (discipline, adaptability, personalization, or assessment focus), but as my experience grew, so did my sense that no single approach captured the iterative, stakeholder-driven, and data-informed cycle demanded by today’s online learning landscape.

So, I charted my own course: the DOGMATIC model. Obviously, there is a substantial tongue in cheek nod to the power some of the most prevalent methodologies hold over L&D organizations, but I do think there is some novelty and points to consider. Given the hundreds of design methodologies, a new “DOGMATIC” model pays homage to these trusted methods (ADDIE being the most prevalent), but also helps inject iteration into an agile workflow. What follows is a deep dive into how this methodology not only embraces iteration and agility, but also invites artificial intelligence and project management innovation into the designer’s toolkit.

If ever there was a time for instructional designers to move beyond the old static models and embrace the spirit of real-time adaptation, it is now. Let’s talk candidly about DOGMATIC: a design approach that is as practical as it is comprehensive, and increasingly relevant in a world where agile thinking and machine intelligence are reshaping every facet of learning.

Why DOGMATIC Is the Perfect Fit for Iterative and Agile Practice

One of the real strengths of the DOGMATIC model: Define, Organize, Generate, Measure, Analyze, Translate, Iterate, Continue, is its unapologetic embrace of iteration. Instructional design today cannot be limited to “build once, deploy, and forget.” Instead, DOGMATIC gives structure to the ongoing process of reflection and improvement.

Iteration is woven in: At every phase, there is open invitation and strong encouragement to pause, reassess, and adapt based on clear evidence and student feedback. This is not a prescription that only allows for revision at the end, but instead insists that true quality comes from continued touchpoints and updates, rather than luck or happenstance.

Perfect match for Agile: The DOGMATIC cycle pairs easily with agile project management. Each stage, whether you are organizing content or analyzing results, naturally maps to sprints, boards, check-ins, and rapid prototyping, which are common in Scrum and similar methodologies. Agile means feedback gets acted on when it matters, not after learners have struggled through a less-than-stellar course.

AI: The Accelerator in DOGMATIC’s Engine

Now, sprinkle in a little artificial intelligence and watch what happens. AI is not just a tool for futuristic classrooms. It is here, right now, automating the grunt work and amplifying the best parts of what a designer does.

• Rapid needs and learner analysis: AI sifts through surveys, learning records, and feedback at lightning speed, giving designers immediate insights into student needs, readiness, and preferences. The “define” stage happens smarter and faster with richer profiles and more precise objectives from the get-go.

• Personalized content generation: AI can help organize modules with learner variability in mind, suggesting structures and content blends that reflect what works best for a range of student backgrounds. In “generate,” AI-powered tools craft case studies, generate quizzes, or create multimedia assets in minutes, not weeks.

• Continuous measurement and analysis: Algorithms continually monitor learner performance and interaction patterns. Instead of post-mortem reviews, you get real-time alerts when learners disengage or misinterpret content. Measurement becomes a living process, feeding directly to the next analysis and translation stages.

• Translation for action: Instead of slogging through data tables, AI transforms analytics into plain-language summaries: “Module 2 needs clearer examples,” or “30 percent of learners need a review activity before the quiz.” Suddenly, reporting is faster and more persuasive with stakeholders.

• Iteration is instant: When problems emerge, AI assists with immediate fixes or new versions. No more long delays between identifying a problem and applying the solution. Iterative improvement becomes a rhythm, not a rescue operation.

• Sustained course evolution: The “continue” phase, too, gets a supercharge from AI. Automated monitoring and suggestion engines flag outdated content or propose enhancements as new technologies or research emerge. This helps the course stay accurate, engaging, and aligned with both learner needs and organizational priorities.

Project Management for the Modern Designer

DOGMATIC fits perfectly with project management tools used in agile teams. Boards and trackers can capture each stage as a backlog item, while AI can help populate tasks by detecting problem areas and automating parts of the workflow. Stand-ups and stakeholder reviews become moments of reflection and shared direction, guided by transparent evidence from continuous analytics.

With the right combination of structured process and smart technology, the once daunting task of providing truly adaptive, learner-centric experiences becomes not just achievable, but expected.

So, What Does This Mean for Instructional Designers?

DOGMATIC is just a goofy name to get a chuckle, but the concepts it is based upon are more relevant than ever. Embrace the cycle. Use AI for everything from needs analysis to personalized content, to feedback capture and reporting. Rely on agile principles to keep teams moving forward efficiently, adjusting quickly, and keeping the course aligned with real needs, not static checklists.

Learners get experiences that actually fit their lives and contexts. Designers reclaim time from repetitive busywork and invest their energy in creative strategy and solving complex learning challenges.

By blending DOGMATIC’s structured flexibility, agile project management, and AI’s catalytic speed, instructional design finally closes the gap between good intentions and great outcomes.