What results are available for custom tasks?
For custom tasks rather than national tasks for subscribers, you can download the results of your candidates in CSV format.
Go to the particular task, click the "Refresh Scores" button then Check results.
You will be directed to this page, click the "Candidates Results" button.
The results downloaded in csv format will look like this:
QR Code - The 6-figure Code assigned to that candidate for the judging process.
First Name - The candidate's first name.
Last Name - The candidate's last name.
DOB - The candidate's date of birth.
Gender - The candidate's gender.
Group - The class or group where the candidate belong.
Pupil Premium - The Pupil Premium status of the candidate.
Year Group - The year group of the candidate.
Scaled Score - The scaled scale for the candidate, a higher score being better. The scale limits are determined by the Scaled Score Min and the Scaled Score Range as defined in the Settings for the task.
Scaled Score SE - The standard error of the scaled score.
True Score - The actual score before scaling used by the statistical calculations involved in comparative judgement.
True Score SE - The standard error of the estimate of the true score.
Infit - The infit statistic for the candidate is a reflection of the degree of disagreement between judges on the quality of the scripts. A low value means low disagreement and a higher value means more disagreement. A value of 1.3 or greater means there was significant disagreement regarding this candidate’s script, and it may be of interest to look in more detail at scripts with these higher values.
Score - All the judgements and the ‘wins’ and ‘losses’ for each script against other scripts are placed into a mathematical model and the resulting ‘quality’ of each script is calculated. The mathematical model is a theoretical model of how the wins and losses of scripts should be, given their varying quality. From this model, we obtain the theoretical number of wins that a script should have if the data were to fit the mathematical model perfectly - this is the Score.
Prop Score - The theoretical proportion of wins we would expect (Score divided by number of comparisons).
Level and Level Value - If the candidates have Levels associated with their scores, they will appear here.
Link - If you want to look in detail at a candidate's script then you can copy and paste this link into your browser to take you to an image of that script.
Local Comparisons - How many local comparisons were made for this script.
Mod Comparisons - How many moderation comparisons were made for this script.
Anchor - Anchor script flag.
Moderated - Moderated script flag.
Task Name - The name of the specific task that judgements were made.
Observed Score - The number of 'wins' for the script
Losses - The number of 'losses' for the script
Go to the particular task, click the "Refresh Scores" button then Check results.
You will be directed to this page, click the "Candidates Results" button.
The results downloaded in csv format will look like this:
QR Code - The 6-figure Code assigned to that candidate for the judging process.
First Name - The candidate's first name.
Last Name - The candidate's last name.
DOB - The candidate's date of birth.
Gender - The candidate's gender.
Group - The class or group where the candidate belong.
Pupil Premium - The Pupil Premium status of the candidate.
Year Group - The year group of the candidate.
Scaled Score - The scaled scale for the candidate, a higher score being better. The scale limits are determined by the Scaled Score Min and the Scaled Score Range as defined in the Settings for the task.
Scaled Score SE - The standard error of the scaled score.
True Score - The actual score before scaling used by the statistical calculations involved in comparative judgement.
True Score SE - The standard error of the estimate of the true score.
Infit - The infit statistic for the candidate is a reflection of the degree of disagreement between judges on the quality of the scripts. A low value means low disagreement and a higher value means more disagreement. A value of 1.3 or greater means there was significant disagreement regarding this candidate’s script, and it may be of interest to look in more detail at scripts with these higher values.
Score - All the judgements and the ‘wins’ and ‘losses’ for each script against other scripts are placed into a mathematical model and the resulting ‘quality’ of each script is calculated. The mathematical model is a theoretical model of how the wins and losses of scripts should be, given their varying quality. From this model, we obtain the theoretical number of wins that a script should have if the data were to fit the mathematical model perfectly - this is the Score.
Prop Score - The theoretical proportion of wins we would expect (Score divided by number of comparisons).
Level and Level Value - If the candidates have Levels associated with their scores, they will appear here.
Link - If you want to look in detail at a candidate's script then you can copy and paste this link into your browser to take you to an image of that script.
Local Comparisons - How many local comparisons were made for this script.
Mod Comparisons - How many moderation comparisons were made for this script.
Anchor - Anchor script flag.
Moderated - Moderated script flag.
Task Name - The name of the specific task that judgements were made.
Observed Score - The number of 'wins' for the script
Losses - The number of 'losses' for the script
Updated on: 04/09/2024
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