Frayer Model¶

Strategy · All strategies
Evidence · 3 claims (3 for) · 9 studies (5 causal, 2 quant-synthesis, 2 review), q2–q4 · 2 of 9 report an effect size

Description¶

The Frayer Model is a four-quadrant graphic organizer used to teach a concept: learners complete sections for (1) a definition, (2) essential characteristics or facts, (3) examples, and (4) non-examples. Because learners must supply the content themselves rather than copy a glossary entry, the organizer functions as a structured generative activity rather than a passive note-taking frame. It was developed by Frayer, Frederick, and Klausmeier (1969) at the Wisconsin Research and Development Center for Cognitive Learning as part of work on concept acquisition.

Design Implications¶

The Frayer Model operationalizes concept learning by forcing discrimination between instances and non-instances, which is the core of concept attainment [~M]. Requiring learners to generate their own definition and examples makes the activity generative, which strengthens encoding relative to reading a definition alone elaborative-interrogation-improves-learning [+M]. The four quadrants also distribute processing across verbal and visual/structural channels, consistent with dual coding benefits dual-coding-improves-recall [+M].

Context¶

Requirements¶

• A well-chosen target concept — the model works best for concepts with clear boundaries, not for terms that are purely arbitrary labels
• Learner access to resources (texts, discussion, prior knowledge) for generating characteristics and examples
• Teacher or peer feedback on the quality of definitions and especially of non-examples, since a wrong non-example can entrench a misconception
• Time for completion; the model is substantially more effortful than copying a definition
• A concept rich enough to have genuine boundaries — not a simple fact or a single vocabulary word with no near-neighbors
• A teacher- or curriculum-supplied definition anchor, so learners do not entrench misconceptions before feedback
• Time for learners to generate their own quadrants, followed by comparison or feedback against a completed version
• A concept with genuine definitional structure — a category with criteria, not a proper noun or an arbitrary label
• A teacher who has clarified the concept's boundaries first; the model exposes fuzzy teacher understanding immediately
• At least two examples and two near-miss non-examples that differ on a defining attribute, not on surface features
• Time for learners to generate and defend entries, ideally through class discussion of disputed cases

Constraints¶

• Inefficient for high-volume vocabulary coverage; completing one organizer per term takes far longer than other vocabulary routines [-W]
• Weak for arbitrary or technical labels with no underlying concept (e.g., proper nouns, unit names), where "non-examples" are ill-defined [-W]
• If the definition quadrant is completed by copying a dictionary, the generative benefit largely disappears [~M]
• Poorly chosen non-examples (near-misses that are actually examples) can create confusion rather than sharpen boundaries [-M]
• Inefficient for concepts with fuzzy or contested boundaries (e.g., "democracy," "energy") — learners may produce arbitrary examples and non-examples without expert feedback [-W]
• Low value when the target is procedural skill or strategy use rather than conceptual understanding [-M]
• If the definition quadrant is completed first and treated as authoritative, learners may copy it verbatim and skip the discriminating work that drives learning [-W]
• Poorly chosen non-examples (too obviously wrong) fail to sharpen boundaries; near-miss non-examples are required for the contrast to do work [-M]
• Ineffective for concepts without clear defining attributes (e.g., "democracy," "energy" in early grades) — forcing a definition produces pseudo-precision [-W]
• Non-examples chosen for surface similarity are essential; using obviously different non-examples makes the task trivial and produces no discrimination learning [~M]
• Copying teacher-completed models yields shallow encoding; the generative effort is where learning occurs [-M]
• One model per concept is slow; it does not scale to high-volume vocabulary demands, where it should be reserved for high-utility tier-two words or core disciplinary concepts [-W]

Implementation Variability¶

• Blank organizer completed from reading vs. partially completed organizer with examples given and non-examples to be generated (the latter is easier for novices)
• Individual, pair, or whole-class completion; whole-class completion allows class-discussion around contested non-examples
• Extended variants add a fifth quadrant (e.g., "visual representation" or "personal connection") or an "essential vs. non-essential characteristics" split
• Pre-filled vs. generated: teacher-completed organizers support advance organizer use before reading; student-completed versions function as generative processing during or after instruction
• Mathematical adaptation: quadrants re-cast as definition, characteristics/facts, examples, non-examples for concepts like "prime number" or "function"
• Collaborative completion: pairs or groups negotiate quadrants, surfacing disagreements about boundaries for whole-class discussion
• Digital versions: shared slides or whiteboard tools allow asynchronous completion and comparison across learners
• Blank vs. partially completed: give novices the definition and one example, letting them derive the rest; fade support as expertise grows
• Student-generated non-examples: asking learners to invent near-misses is a harder, more generative variant
• Disciplinary adaptations: in mathematics, quadrants become "what it is / what it is not / examples / counterexamples"; in science, characteristics split into necessary vs. sufficient
• Digital versions: shared slides or whiteboard tools allow collaborative completion and comparison across groups

Target Learners¶

• Elementary and secondary learners acquiring discipline-specific concepts and academic vocabulary [+M]
• Struggling readers and learners with language-based difficulties benefit from the explicit structure, which reduces the demands of open-ended note-taking [~M]
• Advanced learners with strong prior knowledge may find the fixed structure redundant; they benefit more from comparing multiple concepts than from deep-processing a single term [~W]
• Elementary through secondary learners acquiring discipline-specific vocabulary and concepts [+M]
• Multilingual learners, for whom the visual structure and explicit non-examples reduce reliance on nuanced definitional language [+W]
• Less beneficial for advanced learners who already discriminate the concept reliably — the organizer becomes busywork [~W]
• Novices encountering a new disciplinary concept for the first time, who otherwise anchor on surface features Multiple contrasting cases support abstraction of the underlying principle. [+M]
• English language learners, when paired with accessible vocabulary and syntax and visual examples — the structure makes implicit expectations explicit
• Less beneficial for advanced learners who already hold well-differentiated concepts; the organizer becomes redundant busywork [~W]

Target Learning Goals¶

• Concept acquisition: building accurate boundaries around what a term does and does not include
• Academic vocabulary depth beyond definitional recall
• Discrimination and classification: distinguishing instances from non-instances, which supports transfer to new cases
• Concept acquisition: building accurate, bounded schemas for vocabulary and category terms
• Discrimination learning: distinguishing near-neighbors (e.g., mass vs. weight, weathering vs. erosion)
• Retrieval and retention: the generative completion acts as elaborative encoding supporting later recall [+M]
• Concept formation: learning what a term includes, excludes, and why
• Discrimination learning: distinguishing superficially similar concepts (e.g., mass vs. weight, prime vs. odd)
• Vocabulary depth: moving from definitional knowledge to flexible, criterion-based word use

Instructions¶

1. Select the target concept and present the term in context (a text, problem, or phenomenon), activating prior knowledge activation
2. Learners write or draft a definition in their own words — not copied — in the definition quadrant
3. Learners list essential characteristics or facts in the second quadrant
4. Learners generate 2–3 examples, ideally drawn from the instructional context
5. Learners generate 2–3 non-examples, choosing near-misses that test the concept's boundary rather than obviously unrelated items
6. Review and refine: compare organizers across peers, resolve disagreements about non-examples, and revise definitions — the discussion phase is where much of the learning occurs

Related Strategies¶

• Concept Attainment — the broader instructional pattern the Frayer Model serves; both hinge on example/non-example contrast
• Analogies — an alternative route to conceptual understanding via relational mapping rather than boundary discrimination
• Advance Organizers — a complementary structure presented before learning rather than during consolidation of a single concept
• Activating Prior Knowledge — front-loads the experiences learners draw on when generating examples
• Semantic feature analysis — a matrix-based sibling that compares multiple concepts across attributes rather than deepening one
• Word walls — a lower-intensity vocabulary routine; the Frayer Model supplies the depth that walls alone lack
• Twelve-step teacher-led concept-diagram vocabulary lesson routine
• Develop mathematical concepts and working definitions before teaching formal terms, replacing vocabulary preteaching

Examples¶

• Science: Students complete a Frayer Model for "mammal" with non-examples of dolphin-adjacent confusions (shark, tuna) and boundary cases (platypus), then defend their non-example choices in discussion.
• Mathematics: A Frayer Model for "function" with non-examples such as relations that assign two outputs to one input; the non-example quadrant does the diagnostic work.
• Vocabulary programs: Word Generation (https://www.serpinstitute.org/word-generation), SERP Institute's free academic vocabulary curriculum, uses structured word analysis routines of this kind for middle-school discussion-based vocabulary instruction.
• Vocabulary instruction in science: students complete Frayer organizers for conductor and insulator, then classify ambiguous materials (e.g., graphite) using their characteristics quadrant.
• Mathematics: Illustrative Mathematics style concept lessons use example/non-example sorting consistent with the Frayer structure when introducing definitions such as "polygon."
• Reading intervention programs: several commercial vocabulary supplements (e.g., within Reading A–Z vocabulary materials) include Frayer templates as standard practice for academic vocabulary.
• Mathematics: a Frayer Model for prime number — definition ("a whole number greater than 1 with exactly two factors"), characteristics (exactly two factors, greater than 1), examples (2, 7, 13), non-examples (1, which fails the "greater than 1" criterion; 9, which has three factors). The non-example 1 is the critical case that corrects the most common misconception.
• Science: mammal with the non-example dolphin-as-fish reasoning surfaced, forcing learners to use reproduction and warm-bloodedness rather than habitat as criteria.
• Literacy/vocabulary programs: widely embedded in tiered vocabulary routines such as those in Marzano's six-step academic vocabulary process (Marzano & Pickering, 2005), where the Frayer Model serves as the "represent and deepen" step.

Key Sources¶

• Frayer, D. A., Frederick, W. C., & Klausmeier, H. J. (1969). A schema for testing the level of concept mastery (Working Paper No. 16). Wisconsin Research and Development Center for Cognitive Learning, University of Wisconsin.
• Schwartz, R. M., & Raphael, T. E. (1985). Concept of definition: A key to improving students' vocabulary. The Reading Teacher, 39(2), 198–205.
• Bos, C. S., & Anders, P. L. (1990). Effects of interactive vocabulary instruction on the vocabulary learning and reading comprehension of junior-high learning-disabled students. Learning Disability Quarterly, 13(1), 31–42. doi:10.2307/1510390
• Marzano, R. J. (2004). Building background knowledge for academic achievement: Research on what works in schools. ASCD.
• Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16(4), 475–522. doi:10.1207/s1532690xci1604_4
• Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4–58. doi:10.1177/1529100612453266
• Marzano, R. J., & Pickering, D. J. (2005). Building academic vocabulary: Teacher's manual. ASCD.
• Stahl, S. A., & Fairbanks, M. M. (1986). The effects of vocabulary instruction: A model-based meta-analysis. Review of Educational Research, 56(1), 72–110. doi:10.3102/00346543056001072