{
  "schema": "vedokrok.public-item.v1",
  "release_id": "MHC-RPUB-20260920-75ad787a",
  "url": "/knowledge/use-near-neighbour-cases-to-train-discrimination",
  "id": "MHC-D-RESEARCH-9010",
  "version": "0.1.0",
  "title": "Use near-neighbour cases to train discrimination",
  "summary": "Some errors are not missing knowledge; they are missing contrast.",
  "kind": "protocol",
  "body": "Put easily confused cases close enough that the learner must notice the feature that changes the decision. Compare one case where option A fits with a near neighbour where B fits, then ask for the discriminating cue before revealing the answer.",
  "limits": [
    "Interleaving is not uniformly beneficial. Use this design when categories must be discriminated and the comparison clarifies rather than overloads."
  ],
  "topics": [
    "union-skill-acquisition-career-dominant-focus"
  ],
  "intents": [],
  "source_ids": [
    "RS-B82676FFC4E6D020"
  ],
  "evidence": [
    {
      "claim": "A meta-analysis of interleaving found a moderate overall benefit (g = 0.42) but strong moderation by material type and category similarity, including conditions where blocking performed better.",
      "source_id": "RS-B82676FFC4E6D020",
      "role": "supports",
      "note": "Interleaving should be selected for a discrimination problem rather than used as a universal mixing rule.",
      "locator": "Abstract"
    }
  ],
  "use_when": [
    "When two plausible methods, categories or diagnoses are repeatedly confused."
  ],
  "avoid_when": [
    "Interleaving is not uniformly beneficial. Use this design when categories must be discriminated and the comparison clarifies rather than overloads."
  ],
  "example": "Two customer-master scenarios look similar, but only one has the organizational data needed for a particular process. The practice pair makes that cue explicit.",
  "check": "The learner can classify fresh near-neighbour cases and explain the feature that flips the decision.",
  "steps": [
    "Choose two commonly confused options.",
    "Create or select near-neighbour cases that differ on the decisive feature.",
    "Ask the learner to name the cue before choosing.",
    "Mix fresh near neighbours until the distinction survives."
  ],
  "sources": [
    {
      "id": "RS-B82676FFC4E6D020",
      "title": "Similarity matters: A meta-analysis of interleaved learning and its moderators",
      "url": "https://pubmed.ncbi.nlm.nih.gov/31556629/"
    }
  ],
  "relations": [
    {
      "from": "MHC-D-RESEARCH-9010",
      "to": "MHC-D-RESEARCH-9011",
      "type": "useful_with",
      "url": "/knowledge/interleave-only-where-choosing-matters"
    }
  ],
  "collections": [
    {
      "id": "RC-EA04F47374E04549",
      "title": "Learn new skills, turn them into career evidence, and protect the main development edge",
      "url": "/collections/learn-new-skills-turn-them-into-career-evidence-and-protect-the-main-development-edge"
    }
  ]
}