212 lines
9.5 KiB
Ruby
212 lines
9.5 KiB
Ruby
class ProxyExercise < ActiveRecord::Base
|
|
|
|
after_initialize :generate_token
|
|
|
|
has_and_belongs_to_many :exercises
|
|
has_many :user_proxy_exercise_exercises
|
|
|
|
def count_files
|
|
exercises.count
|
|
end
|
|
|
|
def generate_token
|
|
self.token ||= SecureRandom.hex(4)
|
|
end
|
|
private :generate_token
|
|
|
|
def duplicate(attributes = {})
|
|
proxy_exercise = dup
|
|
proxy_exercise.attributes = attributes
|
|
proxy_exercise
|
|
end
|
|
|
|
def to_s
|
|
title
|
|
end
|
|
|
|
def get_matching_exercise(user)
|
|
assigned_user_proxy_exercise = user_proxy_exercise_exercises.where(user: user).first
|
|
recommended_exercise =
|
|
if (assigned_user_proxy_exercise)
|
|
Rails.logger.info("retrieved assigned exercise for user #{user.id}: Exercise #{assigned_user_proxy_exercise.exercise}" )
|
|
assigned_user_proxy_exercise.exercise
|
|
else
|
|
Rails.logger.info("find new matching exercise for user #{user.id}" )
|
|
matching_exercise =
|
|
begin
|
|
find_matching_exercise(user)
|
|
rescue #fallback
|
|
Rails.logger.error("finding matching exercise failed. Fall back to random exercise! Error: #{$!}" )
|
|
exercises.shuffle.first
|
|
end
|
|
user.user_proxy_exercise_exercises << UserProxyExerciseExercise.create(user: user, exercise: matching_exercise, proxy_exercise: self)
|
|
matching_exercise
|
|
end
|
|
recommended_exercise
|
|
end
|
|
|
|
def find_matching_exercise(user)
|
|
exercises_user_has_accessed = user.submissions.where("cause IN ('submit','assess')").map{|s| s.exercise}.uniq
|
|
tags_user_has_seen = exercises_user_has_accessed.map{|ex| ex.tags}.uniq.flatten
|
|
Rails.logger.info("exercises_user_has_accessed #{exercises_user_has_accessed.map{|e|e.id}.join(",")}")
|
|
|
|
# find execises
|
|
potential_recommended_exercises = []
|
|
exercises.each do |ex|
|
|
## find exercises which have only tags the user has already seen
|
|
if (ex.tags - tags_user_has_seen).empty?
|
|
potential_recommended_exercises << ex
|
|
end
|
|
end
|
|
Rails.logger.info("potential_recommended_exercises: #{potential_recommended_exercises.map{|e|e.id}}")
|
|
# if all exercises contain tags which the user has never seen, recommend easiest exercise
|
|
if potential_recommended_exercises.empty?
|
|
select_easiest_exercise(exercises)
|
|
else
|
|
recommended_exercise = select_best_matching_exercise(user, exercises_user_has_accessed, potential_recommended_exercises)
|
|
recommended_exercise
|
|
end
|
|
end
|
|
private :find_matching_exercise
|
|
|
|
def select_best_matching_exercise(user, exercises_user_has_accessed, potential_recommended_exercises)
|
|
topic_knowledge_user_and_max = get_user_knowledge_and_max_knowledge(user, exercises_user_has_accessed)
|
|
puts "topic_knowledge_user_and_max: #{topic_knowledge_user_and_max}"
|
|
puts "potential_recommended_exercises: #{potential_recommended_exercises.size}: #{potential_recommended_exercises.map{|p| p.id}}"
|
|
topic_knowledge_user = topic_knowledge_user_and_max[:user_topic_knowledge]
|
|
topic_knowledge_max = topic_knowledge_user_and_max[:max_topic_knowledge]
|
|
current_users_knowledge_lack = {}
|
|
topic_knowledge_max.keys.each do |tag|
|
|
current_users_knowledge_lack[tag] = topic_knowledge_user[tag] / topic_knowledge_max[tag]
|
|
end
|
|
|
|
relative_knowledge_improvement = {}
|
|
potential_recommended_exercises.each do |potex|
|
|
tags = potex.tags
|
|
relative_knowledge_improvement[potex] = 0.0
|
|
Rails.logger.info("review potential exercise #{potex.id}")
|
|
tags.each do |tag|
|
|
tag_ratio = potex.exercise_tags.where(tag: tag).first.factor.to_f / potex.exercise_tags.inject(0){|sum, et| sum += et.factor }.to_f
|
|
max_topic_knowledge_ratio = potex.expected_difficulty * tag_ratio
|
|
old_relative_loss_tag = topic_knowledge_user[tag] / topic_knowledge_max[tag]
|
|
new_relative_loss_tag = topic_knowledge_user[tag] / (topic_knowledge_max[tag] + max_topic_knowledge_ratio)
|
|
puts "tag #{tag} old_relative_loss_tag #{old_relative_loss_tag}, new_relative_loss_tag #{new_relative_loss_tag}, tag_ratio #{tag_ratio}"
|
|
relative_knowledge_improvement[potex] += old_relative_loss_tag - new_relative_loss_tag
|
|
end
|
|
end
|
|
highest_difficulty_user_has_accessed = exercises_user_has_accessed.map{|e| e.expected_difficulty}.sort.last || 0
|
|
best_matching_exercise = find_best_exercise(relative_knowledge_improvement, highest_difficulty_user_has_accessed)
|
|
Rails.logger.info("current users knowledge loss: " + current_users_knowledge_lack.map{|k,v| "#{k} => #{v}"}.to_s)
|
|
Rails.logger.info("relative improvements #{relative_knowledge_improvement.map{|k,v| k.id.to_s + ':' + v.to_s}}")
|
|
best_matching_exercise
|
|
end
|
|
private :select_best_matching_exercise
|
|
|
|
def find_best_exercise(relative_knowledge_improvement, highest_difficulty_user_has_accessed)
|
|
Rails.logger.info("select most appropiate exercise for user. his highest difficulty was #{highest_difficulty_user_has_accessed}")
|
|
sorted_exercises = relative_knowledge_improvement.sort_by{|k,v| v}.reverse
|
|
|
|
sorted_exercises.each do |ex,diff|
|
|
Rails.logger.info("review exercise #{ex.id} diff: #{ex.expected_difficulty}")
|
|
if (ex.expected_difficulty - highest_difficulty_user_has_accessed) <= 1
|
|
Rails.logger.info("matched exercise #{ex.id}")
|
|
return ex
|
|
else
|
|
Rails.logger.info("exercise #{ex.id} is too difficult")
|
|
end
|
|
end
|
|
easiest_exercise = sorted_exercises.min_by{|k,v| v}.first
|
|
Rails.logger.info("no match, select easiest exercise as fallback #{easiest_exercise.id}")
|
|
easiest_exercise
|
|
end
|
|
private :find_best_exercise
|
|
|
|
# [score][quantile]
|
|
def scoring_matrix
|
|
[
|
|
[0 ,0 ,0 ,0 ,0 ],
|
|
[0.2,0.2,0.2,0.2,0.1],
|
|
[0.5,0.5,0.4,0.4,0.3],
|
|
[0.6,0.6,0.5,0.5,0.4],
|
|
[1 ,1 ,0.9,0.8,0.7],
|
|
]
|
|
end
|
|
|
|
def scoring_matrix_quantiles
|
|
[0.2,0.4,0.6,0.8]
|
|
end
|
|
private :scoring_matrix_quantiles
|
|
|
|
def score(user, ex)
|
|
points_ratio = ex.maximum_score(user) / ex.maximum_score.to_f
|
|
if points_ratio == 0.0
|
|
Rails.logger.debug("scoring user #{user.id} for exercise #{ex.id}: points_ratio=#{points_ratio} score: 0" )
|
|
return 0.0
|
|
end
|
|
points_ratio_index = ((scoring_matrix.size - 1) * points_ratio).to_i
|
|
working_time_user = ex.accumulated_working_time_for_only(user)
|
|
quantiles_working_time = ex.get_quantiles(scoring_matrix_quantiles)
|
|
quantile_index = quantiles_working_time.size
|
|
quantiles_working_time.each_with_index do |quantile_time, i|
|
|
if working_time_user <= quantile_time
|
|
quantile_index = i
|
|
break
|
|
end
|
|
end
|
|
Rails.logger.debug(
|
|
"scoring user #{user.id} exercise #{ex.id}: worktime #{working_time_user}, points: #{points_ratio}" \
|
|
"(index #{points_ratio_index}) quantiles #{quantiles_working_time} placed into quantile index #{quantile_index} " \
|
|
"score: #{scoring_matrix[points_ratio_index][quantile_index]}")
|
|
scoring_matrix[points_ratio_index][quantile_index]
|
|
end
|
|
private :score
|
|
|
|
def get_relative_knowledge_loss(user, exercises)
|
|
# initialize knowledge for each tag with 0
|
|
all_used_tags = exercises.inject(Set.new){|tagset, ex| tagset.merge(ex.tags)}
|
|
topic_knowledge_loss_user = all_used_tags.map{|t| [t, 0]}.to_h
|
|
topic_knowledge_max = all_used_tags.map{|t| [t, 0]}.to_h
|
|
exercises.each do |ex|
|
|
user_score_factor = score(user, ex)
|
|
ex.tags.each do |t|
|
|
tag_ratio = ex.exercise_tags.where(tag: t).first.factor / ex.exercise_tags.inject(0){|sum, et| sum += et.factor }
|
|
max_topic_knowledge_ratio = ex.expected_difficulty * tag_ratio
|
|
topic_knowledge_loss_user[t] += (1 - user_score_factor) * max_topic_knowledge_ratio
|
|
topic_knowledge_max[t] += max_topic_knowledge_ratio
|
|
end
|
|
end
|
|
relative_loss = {}
|
|
all_used_tags.each do |t|
|
|
relative_loss[t] = topic_knowledge_loss_user[t] / topic_knowledge_max[t]
|
|
end
|
|
relative_loss
|
|
end
|
|
private :get_relative_knowledge_loss
|
|
|
|
def get_user_knowledge_and_max_knowledge(user, exercises)
|
|
# initialize knowledge for each tag with 0
|
|
all_used_tags = exercises.inject(Set.new){|tagset, ex| tagset.merge(ex.tags)}
|
|
topic_knowledge_loss_user = all_used_tags.map{|t| [t, 0]}.to_h
|
|
topic_knowledge_max = all_used_tags.map{|t| [t, 0]}.to_h
|
|
exercises.each do |ex|
|
|
Rails.logger.info("exercise: #{ex.id}: #{ex}")
|
|
user_score_factor = score(user, ex)
|
|
ex.tags.each do |t|
|
|
tag_ratio = ex.exercise_tags.where(tag: t).first.factor.to_f / ex.exercise_tags.inject(0){|sum, et| sum += et.factor }.to_f
|
|
Rails.logger.info("tag: #{t}, factor: #{ex.exercise_tags.where(tag: t).first.factor}, sumall: #{ex.exercise_tags.inject(0){|sum, et| sum += et.factor }}")
|
|
Rails.logger.info("tag_ratio #{tag_ratio}")
|
|
topic_knowledge_ratio = ex.expected_difficulty * tag_ratio
|
|
Rails.logger.info("topic_knowledge_ratio #{topic_knowledge_ratio}")
|
|
topic_knowledge_loss_user[t] += (1 - user_score_factor) * topic_knowledge_ratio
|
|
topic_knowledge_max[t] += topic_knowledge_ratio
|
|
end
|
|
end
|
|
{user_topic_knowledge: topic_knowledge_loss_user, max_topic_knowledge: topic_knowledge_max}
|
|
end
|
|
private :get_user_knowledge_and_max_knowledge
|
|
|
|
def select_easiest_exercise(exercises)
|
|
exercises.order(:expected_difficulty).first
|
|
end
|
|
|
|
end |