LDTC 605 · Unit 5 · Instructional Design Models

Rapid Instructional Design

Building Decoding the Code fast and right — a structured-literacy PD minicourse for Grades 6–12 content-area teachers.

Tenneh C. Freeman · Learning Design & Technology · UMGC
The approach

What Rapid Instructional Design is

Rapid Instructional Design (RID) is the fast lane version of the design work I already do. It keeps the bones of ADDIE — analysis, design, development, implementation, evaluation — but stops treating them as five doors you walk through one at a time. The phases overlap. You read the problem and the audience quickly, design and build at the same time, lean hard on templates and material you already have, and put a rough working version in front of learners early so you can fix it while it runs (Piskurich, 2015).

The stages, the way I think about them

Why it matters

Implications for instructional design

Speed changes the goal. The win is a usable course in learners' hands quickly, not a flawless one much later.

Existing material becomes an asset. A designer's back catalog of lessons and tools is fuel, not a starting-over problem.

Feedback moves to the front. Evaluation stops being the last step and becomes a running conversation with learners.

Quality has to hold while moving fast. Rapid does not mean careless — it means disciplined shortcuts, templates, and clear priorities so speed never costs accuracy.

It shifts risk earlier. You find out fast what does not work, which is cheaper than discovering it after a full build.

Applied to my minicourse

Strengths and limitations for Decoding the Code

Where Rapid helps

  • The need is urgent. Secondary content teachers are sitting with struggling and dyslexic readers right now. Rapid ID lets me get Module 1 into their hands this term instead of next year.
  • I already own the content. Years of structured-literacy materials, Orton-Gillingham routines, and morphology word studies are ready to repurpose — exactly what Rapid rewards.
  • Self-paced and async fits prototyping. I can release one module, watch how Marcus and Rosa move through it, and tighten the next one from what I see.
  • Short builds match short attention. My teachers work in the cracks between classes; small, modular builds match how they will actually use the course.

Where Rapid challenges my design

  • Thin analysis hurts my three tracks. Differentiation for Marcus, Rosa, and David only works because I did real front-end analysis. Rapid's quick-look analysis could flatten those differences.
  • The science has to be right. Structured literacy is technical. A too-fast build risks putting a shaky rule in front of a science or math teacher who will trust it — a place I cannot cut corners.
  • My feedback loop may be slow. Rapid prototyping assumes fast responses. Async, self-paced teachers may take weeks to finish a module, slowing the very iteration Rapid depends on.
  • Alignment can slip. UbD kept my outcomes, evidence, and activities locked together. Moving fast, I have to guard that CLO-to-activity alignment myself.
Instructional Design Document · Draft

Learning Activities

Six activities that close the learning gap and support the course learning outcomes. Each is tagged to the CLO it carries.

ACTIVITY 01

Escape the 6: Six Components of Structured Literacy

Short explainer segments introduce the six components of structured literacy — phonology, sound–symbol association, syllable instruction, morphology, syntax, and semantics — and the tell that gives each one away. Teachers then enter a timed escape room where six locks each hold a piece of real student evidence; naming the component behind the breakdown is what opens the lock. Mastery gates and guided hints mean a wrong call earns coaching, not a score. This builds the shared vocabulary every later activity depends on.

CLO 1
Launch the escape room ↗
ACTIVITY 02

Readers of the Ark: Diagnostic Lab

Teachers work through de-identified samples of adolescent reading and writing and decide whether the breakdown is decoding, fluency, or comprehension. Each choice opens a short feedback branch that explains what the evidence shows. Teachers are enabled to spot where a reader is actually stuck instead of guessing.

CLO 2
ACTIVITY 03

Area Code: Morphology in My Subject Area

Each teacher pulls five to eight academic terms from their own content area and breaks them into roots, prefixes, and suffixes. They then draft a short word-study routine they could run in their own class next week. The activity turns morphology from a reading-teacher idea into a content-area vocabulary tool.

CLO 3
ACTIVITY 04

Lit Bit: Literacy-Embedded Lesson Build

Working from a template and a worked example, teachers design one lesson component that carries explicit, multisensory literacy support without lowering the rigor of the content. This is the course's culminating artifact — proof a teacher can build the thing, not just name it.

CLO 4 · draws on CLO 1, 3
ACTIVITY 05

Tech Elect: Assistive Tech Match

Teachers move through three student profiles and match assistive technologies and accommodations — text-to-speech, decodable digital text, specialized fonts, audio scaffolds — to each learner's specific need. A case-based decision path gives feedback at each fork, keeping tool choice tied to a real student rather than a generic checklist.

CLO 5
ACTIVITY 06

Self-Audit and One Goal

Teachers use a structured-literacy self-audit checklist to look honestly at their own instruction, then set one measurable classroom goal. It connects to the three tracks — Marcus sets a foundation goal, Rosa a framework goal, David an intervention goal — closing the course on the teacher's own next step.

CLO 6 · draws on CLO 2
Sources

References

CAST. (2018). Universal design for learning guidelines version 2.2. https://udlguidelines.cast.org

Knowles, M. S. (1980). The modern practice of adult education: From pedagogy to andragogy (2nd ed.). Cambridge Books.

Piskurich, G. M. (2015). Rapid instructional design: Learning ID fast and right (3rd ed.). Wiley.

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.

Wiggins, G., & McTighe, J. (2005). Understanding by design (2nd ed.). ASCD.