...
| Info | ||
|---|---|---|
| ||
Related termsCronbach’s Alpha Standard Error of Measurement The Standard Error of Measurement (not to be confused with the Standard Error of the Mean) gives an indication of the spread of the measurement errors, when estimating candidates' true scores from the observed scores. It is calculated from the reliability coefficient (Practique uses Chronbach's alpha). It is assumed that the sampling errors are normally distributed. The SEM is calculated as SEM = S(1 – rxx)0.5 where S is the standard deviation of the exam, and rxx is the reliability coefficient (Chronbach's alpha). The key application of SEM in Practique is to apply a confidence interval to the cut score. For example, if you would like to be 68% sure of the pass/fail decision, the SEM indicates that the candidates within 1 SEM of the cut score may fluctuate to the other side of the cut score should they take the exam again. For example, if you wanted to be 95% sure of your decision on outcomes, an SEM multiplier of 1.96 can be applied. These figures are based on the Normal Distribution. Practique applies this on the positive side for most Standard Setting methods, as we are dealing with competency exams. In practice, what this means is that you are 95% certain that the passing candidates scores represent their true scores. |
Score Normalisation
It is possible to normalise the marks for each item in an exam to a consistent number. You may want to do this so that each item in an exam is equally weighted, despite having an inconsistent number of marks for each item. Note that the normalisation is on an item basis, and not on an exam basis. It is possible to revert to non-normalised scores.
Minimum Items to pass
When you are on the standard setting page you can set the minimum number of stations to pass an exam. Enter the number and click "apply" this will recalculate the number of passes and fails based on this additional criteria and the total score. If you wish to only pass on stations then you should set the "passing score" to zero.
Notes
*It is important that the assessment function has a clear definition of what a borderline or minimally competent candidate is, and whether these are equivalent
...