Hattie Visible Learning Top Effect Sizes Bar Lookup

Rank independently edition/review/comparison-matched reported instructional-effects, competition ties retained; not a universal causal teaching ranking, meta-analysis quality or cross outcome standardization. Caller independently verifies learner/context/evidence and reference edition; not causal learning efficacy, disability eligibility or educational certification.

Description

Reported instructional effect sizes describe a particular review, outcome and comparison.

Reported instructional effect sizes describe a particular review, outcome and comparison.1

This tool ranks your matched records with competition ties rather than establishing a universal teaching hierarchy.

When to use Hattie Visible Learning Top Effect Sizes Bar Lookup

Use this tool to calculate or review the supplied observations under the stated rules. Establish the learning task, observed evidence and applicable framework or policy edition.

How to use Hattie Visible Learning Top Effect Sizes Bar Lookup and understand its results

  1. Establish the learning task, observed evidence and applicable framework or policy edition.
  2. Enter callerSameReviewVisibleLearningEffectsIds, callerSameReviewVisibleLearningEffectsEstimates, using the field meanings and rules below, then run the tool.
  3. Read callerDescendingCompetitionRanks. Inspect nested result fields where present, and review unknown records separately from known matches.
  4. Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.
Input fieldMeaningValue typeRequirement
callerSameReviewVisibleLearningEffectsIdsCaller same review visible learning effects idslist of stringRequired
callerSameReviewVisibleLearningEffectsEstimatesCaller same review visible learning effects estimateslist of numberRequired

Use unique nonblank strategy IDs and aligned finite signed effect sizes. Sort descending; equal values receive the first matching sorted position plus one. Return ranks aligned to the original input order; sorted IDs are not returned. Ties consume positions: two joint firsts are followed by third place.

rank_i=1+count(effect_j>effect_i)

Use the matching field units and the exact boundary, ordering and reference rules above.

Output fieldMeaningValue type
callerDescendingCompetitionRanksCaller descending competition rankslist of number
json
{
  "input": {
    "callerSameReviewVisibleLearningEffectsIds": [
      "a",
      "b",
      "c"
    ],
    "callerSameReviewVisibleLearningEffectsEstimates": [
      0.2,
      0.6,
      0.6
    ]
  },
  "output": {
    "callerDescendingCompetitionRanks": [
      3,
      1,
      1
    ]
  }
}

Limitations and assumptions

Effect sizes need matched definitions and comparable review conditions. Ranking does not assess study quality, calculate a meta-analysis or demonstrate that a strategy causes better learning in your context.

Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above.

Alternative or Complementary methods

For a related step, use Marzano Nine Instructional Strategies Rankings Lookup: Reported instructional effect sizes describe a particular review, outcome and comparison. For a complementary comparison, use Audio Video Feedback Rich Media Efficiency Lookup: Written and audio or video feedback production can be compared using matched assignment records.

References

  1. Hattie Visible Learning Top Effect Sizes Bar Lookup — tool.io

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