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Add scales to framework. Change calculations to first group and then
average those groupings and the way up the framework. Likert scores for a survey_item are averaged. Then all the survey_items in a scale are averaged. Then student scales in a measure are averaged. And teacher scales in a measure are averaged. Then the average of those two calculations becomes the score for a measure. Then the measures in a subcategory are averaged.
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44 changed files with 1053 additions and 856 deletions
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@ -3,7 +3,7 @@ require 'csv'
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class Seeder
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def seed_academic_years(*academic_year_ranges)
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academic_year_ranges.each do |range|
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AcademicYear.find_or_create_by! range: range
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AcademicYear.find_or_create_by! range:
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end
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end
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@ -89,8 +89,11 @@ class Seeder
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measure.save!
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data_item_id = row['Survey Item ID'].strip
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scale_id = data_item_id.split('-')[0..1].join('-')
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scale = Scale.find_or_create_by! scale_id: scale_id, measure: measure
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if %w[Teachers Students].include? row['Source']
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survey_item = SurveyItem.find_or_create_by! survey_item_id: data_item_id, measure: measure
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survey_item = SurveyItem.where(survey_item_id: data_item_id, scale:).first_or_create
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survey_item.watch_low_benchmark = watch_low if watch_low
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survey_item.growth_low_benchmark = growth_low if growth_low
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survey_item.approval_low_benchmark = approval_low if approval_low
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@ -99,7 +102,7 @@ class Seeder
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end
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if row['Source'] == 'Admin Data'
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admin_data_item = AdminDataItem.find_or_create_by! admin_data_item_id: data_item_id, measure: measure
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admin_data_item = AdminDataItem.where(admin_data_item_id: data_item_id, scale:).first_or_create
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admin_data_item.watch_low_benchmark = watch_low if watch_low
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admin_data_item.growth_low_benchmark = growth_low if growth_low
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admin_data_item.approval_low_benchmark = approval_low if approval_low
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