Introduction
The Rapid Learning Analysis Taxonomy (RLAT) was developed by Nathan Pienkowski, Ph.D., in the early 2000s to address a persistent challenge faced by corporate instructional designers: how to quickly and accurately identify the type of learning required without relying on complex academic models. While most instructional taxonomies were created in academic settings and later adapted for practice, RLAT was developed by adapting insights from many of those existing models for use in fast-paced, real-world environments.
Drawing on decades of experience in the learning sciences and corporate learning, Pienkowski distilled core instructional insights into a framework that is conceptually sound, easy to apply, and immediately useful in the field. RLAT does not aim to replace Bloom, Gagné, or CDT. Instead, it synthesizes their strengths into six essential types of learning outcomes, each with practical instructional and assessment strategies. This approach ensures instructional designers can classify, design, and assess learning experiences with speed and clarity.
Declarative Learning
What it is:
Declarative learning is about remembering factual information. It is the most basic form of learning, concerned with isolated pieces of knowledge. Learners may be required to recall specific facts or recognize pieces of information without needing to understand broader concepts or applications.
Example:
“Tuesdays are work-from-home days.”
Instructional Implication:
Declarative learning calls for repetition, exposure, and recall. This learning does not require abstraction, generalization, or application, making it a straightforward process for instructional designers to address. Often, it is foundational and necessary for building more complex cognitive structures.
Assessment Method:
The assessment for declarative learning focuses on recall or recognition. Multiple choice, fill-in-the-blank, or verbal quizzes are appropriate methods for measuring this type of learning outcome.
Concept Learning
What it is:
Concept learning involves recognizing members of a category. Most concepts have definitions, but what matters instructionally is the learner’s ability to identify examples and non-examples. Concept learning also enables learners to classify items according to certain criteria, helping them build a conceptual framework for understanding the world.
Example:
Understanding what qualifies as a “safety violation.”
Instructional Implication:
Concepts are best taught through contrast. Learners are shown varied examples and non-examples until the defining attributes become clear. By making distinctions between examples that fit the concept and those that do not, learners deepen their understanding and become proficient in recognizing new examples as they encounter them.
Assessment Method:
Classification tasks are the most suitable assessment method. Learners can be asked to sort, label, or recognize instances of the concept under new conditions. This allows designers to measure their ability to apply the concept in different contexts.
Principle Learning
What it is:
Principle learning is about knowing how to respond to specific types of situations. Principles are cause-and-effect or if-then relationships that guide judgment and behavior. Learners at this stage must internalize principles that inform their responses to common scenarios they may encounter in their work or personal lives.
Example:
“If an employee appears disengaged during a one-on-one, then the manager should ask open-ended questions.”
Instructional Implication:
Teaching principles requires situational practice. Learners encounter a scenario, respond to it, receive feedback, and then extract or reinforce the underlying principle. This experiential approach helps learners recognize when and how to apply principles in real-world settings.
Assessment Method:
Scenario-based judgment tasks are used for principle learning. Learners are presented with new situations and must choose or justify appropriate responses. The goal is to assess whether they can identify the guiding principle and apply it correctly in novel scenarios.
Procedural Learning
What it is:
Procedural learning involves performing a sequence of steps to achieve a defined result. It is mechanical or operational in nature, requiring learners to perform a specific task or series of actions with accuracy and consistency. This type of learning focuses on “how to” do something, such as mastering a technical skill or following a prescribed process.
Example:
“How to enter a new sales opportunity into the CRM.”
Instructional Implication:
Procedures are taught through demonstration and practice. Learners must see the steps modeled and then perform them with decreasing guidance. This type of learning is hands-on, often requiring repetition and practice to build fluency and automaticity.
Assessment Method:
Performance checklists or task completion assessments are ideal for procedural learning. The emphasis is on accurate and complete execution, ensuring that learners can follow the steps correctly and consistently.
Systems Learning
What it is:
Systems learning is about understanding dynamic relationships between independent elements that interact to produce outcomes. Systems have nodes (elements) and connectors (relationships), and understanding these interconnections is crucial for problem-solving and decision-making.
Example:
Understanding how regulatory changes affect the specialty pharmaceutical market.
Instructional Implication:
Systems are best taught through modeling, mapping, and simulation. Instruction should help learners see structure, flow, and interdependence. This requires a more holistic approach to teaching, where learners gain an understanding of the larger context in which components interact.
Assessment Method:
Prediction and diagnosis are appropriate for assessing systems knowledge. Learners demonstrate their understanding by either being told an input and predicting the output or being given an outcome and tracing the probable causal chain. These assessments ensure learners understand how elements within a system are connected and how changes can lead to different results.
Affective Learning
What it is:
Affective learning deals with attitudes, values, and emotional dispositions. The goal is not just awareness but empathy and internalization. Affective learning often involves personal transformation, where learners change how they feel or behave in relation to a certain subject.
Example:
Encouraging employees to take ownership of inclusion and belonging.
Instructional Implication:
Affective outcomes are best supported through perspective-taking. Storytelling, roleplay, and guided reflection help learners imagine themselves in unfamiliar situations and internalize the emotional aspects of the content. This encourages deep, meaningful connections with the material, often shifting how learners approach their personal and professional lives.
Assessment Method:
While affective outcomes are difficult to measure directly, proxy assessments such as written reflections, empathy mapping, commitment pledges, or observed behavior changes over time can provide valuable insight into learners’ emotional development. These methods offer indirect evidence of how well learners have internalized the attitudes, values, or emotional dispositions being taught.
Summary Table
| Learning Type | What It Is | Instructional Focus | Assessment Approach |
|---|---|---|---|
| Declarative | Remembering factual information | Exposure, repetition, recall | Recall or recognition tasks |
| Concept | Recognizing members of a category | Contrast with examples and non-examples | Classification tasks |
| Principle | Knowing how to respond to specific situations | Scenario-based practice and generalization | Scenario-based judgment |
| Procedural | Performing a sequence of defined steps | Demonstration and guided practice | Task performance or checklists |
| Systems | Understanding dynamic relationships among elements | Modeling, mapping, simulation | Diagnosis or prediction of system behavior |
| Affective | Developing empathy, values, or emotional dispositions | Perspective-taking, reflection | Reflections, pledges, behavioral observation proxies |
Conclusion
The Rapid Learning Analysis Taxonomy (RLAT) is designed for speed, clarity, and fidelity to the instructional needs most commonly encountered in corporate environments. By categorizing learning into six clear types—declarative, concept, procedural, principle, systems, and affective—it enables instructional designers to quickly:
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Classify learning outcomes
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Choose appropriate methods
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Communicate design decisions clearly to stakeholders
It simplifies without dumbing down. And most importantly, it works in the real world.
RLAT bridges the gap between theory and the daily demands of instructional design. It provides a framework that respects cognitive complexity while acknowledging real-world constraints—a tool built by and for practitioners.