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Reliability

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Reliability Using instruments of unknown reliability is analogous to running an instrumental analysis without creating a working curve with known standards. – PowerPoint PPT presentation

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Title: Reliability


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Reliability
  • Using instruments of unknown reliability is
    analogous to running an instrumental analysis
    without creating a working curve with known
    standards. You get numbers you might even be
    able to generate some pattern from low to high.
  • Beyond that, you just have a lot of numbers that
    you wont know the meaning of.

3
Reliability
  • Lets say you have a reliable analytical
    instrument. You run a sample that you know is 50
    ppb Mn. It reads 50 ppb. You run another split
    from that same sample. It reads 49 ppb. You have
    a good idea how consistent the measures are that
    the instrument is furnishing.

4
Reliability
  • Lets say you have an unreliable analytical
    instrument. You run a sample that you know is 50
    ppb Mn. It reads 76 ppb. You run another split
    from that same sample. It reads 28 ppb. You have
    a good idea that the measures that the instrument
    is furnishing wont be able to resolve any
    differences smaller than about 50 ppb.

5
Reliability is Fundamental
  • Spearman-Brown reliability(R) measure (Jacobs and
    Chase, 1992)
  • derives from the correlation coefficient (r)
    obtained from individuals' scores on two halves
    of a single test
  • and is applicable to tests, properly constructed
    student ratings instruments, and knowledge
    surveys.

6
Reliability from split halves
  • Treats the instrument like an analytical
    instrument
  • Treats a single student or faculty as a sample
  • Treats a score on half the item bank and a score
    on the other half of the bank as two splits from
    the same sample.
  • The line-fit for split halves of all students
    provides a working curve, which is related
    closely to reliability of your survey or test.

7
Use Excel to estimate reliability. Split test
into two halfs even items and odd items
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Next, compute the average score from each half.
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Use Excels stat package to calculate the Pearson
Correlation Coefficient for pairs of scores for
odds evens This is r (lower case)
From r calculate the Pearson-Brown Reliability
Coefficient This is R (upper case) R 2r/(1r)

(20.969)/(10.969)
R 0.98
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Reliability of 40 pt Formative Survey
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You might think that you would get this
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"Hey! My tests and grades don't correlate with
student ratings. That means student ratings are
worthless--right?"
  • Wrong.

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Horror show 1
  • Most faculty-made tests have horrid reliability.

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On a really good test you will get this
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But it is more likely youll get something like
this
Most faculty tests have reliabilities of 0.2 to
0.3.
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Horror show 2
  • About the only thing worse than faculty made
    tests are grades derived from scores on multiple
    faculty-made tests.

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Grade reliability is even lower than test
reliability.
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Why We Need Knowledge Surveys! Faculty place too
much faith in the unexamined reliability of
faculty-made Tests Note r-values from a class
below
To estimate grade reliability, use tests and
quizzes as split halves
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Validity
  • Measures what the instrument is supposed to
    measure

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Classic Validity
  • Multisection
  • Multisource
  • Multibias
  • Experimenter controlled
  • Conceptual structure

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New Validation Framework
  • Content aspects
  • Relationship relevance of form to construct
  • Substantive aspects
  • Relationships of process to construct
  • Structural aspects
  • Relationships of items to construct
  • External aspects
  • Relationships of achievement to construct
  • Generalizability aspects
  • Relationships hold true in general for construct
  • Consequential aspects
  • Relationships of consequences of use to construct
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