Defines the computation login of the grading evaluation subplugin.
More...
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| assessments_distance (stdclass $assessment, stdclass $referential, array $diminfo, stdclass $settings) |
| Measures the distance of the assessment from a referential one. More...
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| average_assessment (array $assessments) |
| Given a set of a submission's assessments, returns a hypothetical average assessment. More...
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| normalize_grades (array $assessments, array $diminfo) |
| Normalizes the dimension grades to the interval 0.00000 - 100.00000. More...
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| prepare_data_from_recordset ($assessments) |
| Prepares a structure of assessments and given grades. More...
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| process_assessments (array $assessments, array $diminfo, stdclass $settings) |
| Given a list of all assessments of a single submission, updates the grading grades in database. More...
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| weighted_variance (array $assessments) |
| Given a set of a submission's assessments, returns standard deviations of all their dimensions. More...
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the | $settings |
| recently used settings in this workshop
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workshop | $workshop |
| the parent workshop instance
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Defines the computation login of the grading evaluation subplugin.
◆ __construct()
workshop_best_evaluation::__construct |
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workshop |
$workshop | ) |
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Constructor.
- Parameters
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workshop | $workshop | The workshop api instance |
- Return values
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◆ assessments_distance()
workshop_best_evaluation::assessments_distance |
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stdclass |
$assessment, |
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stdclass |
$referential, |
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array |
$diminfo, |
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stdclass |
$settings |
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protected |
Measures the distance of the assessment from a referential one.
The passed data structures must contain ->dimgrades property. The referential assessment is supposed to be close to the average assessment. All dimension grades are supposed to be normalized to the interval 0 - 100. Returned value is rounded to 4 valid decimals to prevent some rounding issues - see the unit test for an example.
- Parameters
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stdClass | $assessment | the assessment being measured |
stdClass | $referential | assessment |
array | $diminfo | of stdclass(->weight ->min ->max ->variance) indexed by dimension id |
stdClass | $settings | |
- Return values
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float|null | rounded to 4 valid decimals |
◆ average_assessment()
workshop_best_evaluation::average_assessment |
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array |
$assessments | ) |
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protected |
Given a set of a submission's assessments, returns a hypothetical average assessment.
The passed structure must be array of assessments objects with ->weight and ->dimgrades properties. Returns null if all passed assessments have zero weight as there is nothing to choose from then.
- Parameters
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- Return values
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◆ delete_instance()
static workshop_best_evaluation::delete_instance |
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$workshopid | ) |
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static |
◆ get_settings_form()
workshop_best_evaluation::get_settings_form |
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moodle_url |
$actionurl = null | ) |
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Returns an instance of the form to provide evaluation settings.
- Return values
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Reimplemented from workshop_evaluation.
◆ normalize_grades()
workshop_best_evaluation::normalize_grades |
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array |
$assessments, |
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array |
$diminfo |
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) |
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protected |
Normalizes the dimension grades to the interval 0.00000 - 100.00000.
Note: this heavily relies on PHP5 way of handling references in array of stdclasses. Hopefully it will not change again soon.
- Parameters
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array | $assessments | of stdclass as returned by { |
- See also
- self::prepare_data_from_recordset()}
- Parameters
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- Return values
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array | of stdclass with the same structure as $assessments |
◆ prepare_data_from_recordset()
workshop_best_evaluation::prepare_data_from_recordset |
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$assessments | ) |
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protected |
Prepares a structure of assessments and given grades.
- Parameters
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array | $assessments | batch of recordset items as returned by the grading strategy |
- Return values
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◆ process_assessments()
workshop_best_evaluation::process_assessments |
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array |
$assessments, |
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array |
$diminfo, |
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stdclass |
$settings |
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) |
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protected |
Given a list of all assessments of a single submission, updates the grading grades in database.
- Parameters
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array | $assessments | of stdclass (->assessmentid ->assessmentweight ->reviewerid ->gradinggrade ->submissionid ->dimensionid ->grade) |
array | $diminfo | of stdclass (->id ->weight ->max ->min) |
| stdClass | grading evaluation settings |
- Return values
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◆ update_grading_grades() [1/2]
workshop_best_evaluation::update_grading_grades |
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stdclass |
$settings, |
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$restrict = null |
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Calculates the grades for assessment and updates 'gradinggrade' fields in 'workshop_assessments' table.
This function relies on the grading strategy subplugin providing get_assessments_recordset() method. {
- See also
- self::process_assessments()} for the required structure of the recordset.
- Parameters
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stdClass | $settings | The settings for this round of evaluation |
null | int | array | $restrict | If null, update all reviewers, otherwise update just grades for the given reviewers(s) |
- Return values
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◆ update_grading_grades() [2/2]
workshop_evaluation::update_grading_grades |
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stdClass |
$settings, |
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$restrict = null |
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abstractinherited |
Calculates grades for assessment and updates 'gradinggrade' fields in 'workshop_assessments' table.
- Parameters
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stdClass | $settings | settings for this round of evaluation |
null | int | array | $restrict | if null, update all reviewers, otherwise update just grades for the given reviewers(s) |
◆ weighted_variance()
workshop_best_evaluation::weighted_variance |
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array |
$assessments | ) |
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protected |
Given a set of a submission's assessments, returns standard deviations of all their dimensions.
The passed structure must be array of assessments objects with at least ->weight and ->dimgrades properties. This implementation uses weighted incremental algorithm as suggested in "D. H. D. West (1979). Communications of the ACM, 22, 9, 532-535:
Updating Mean and Variance Estimates: An Improved Method"
- Parameters
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- Return values
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null|array | indexed by dimension id |
The documentation for this class was generated from the following file: