change assessment code for BSOC 2024
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@ -1,6 +1,6 @@
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## load in the data
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#################################
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myuw <- read.csv("../data/2022_winter_COM_481_A_students.csv", stringsAsFactors=FALSE)
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myuw <- read.csv("../data/2024_autumn_COMMLD_570_A_joint_students.csv", stringsAsFactors=FALSE)
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current.dir <- getwd()
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source("../assessment_and_tracking/track_participation.R")
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@ -11,20 +11,20 @@ call.list$timestamp <- as.Date(call.list$timestamp)
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## class-level variables
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gpa.point.value <- 50/(4 - 0.7)
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question.grades <- c("PLUS"=100, "CHECK"=100-gpa.point.value, "MINUS"=100-(gpa.point.value*2))
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## question.grades <- c("GOOD"=100, "FAIR"=100-gpa.point.value, "BAD"=100-(gpa.point.value*2))
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question.grades <- c("GOOD"=100, "SATISFACTORY"=100-gpa.point.value, "POOR"=100-(gpa.point.value*2), "NO MEANINGFUL ANSWER"=0)
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missed.question.penalty <- gpa.point.value * 0.2 ## 1/5 of a full point on the GPA scale
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## inspect set the absence threashold
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ggplot(d) + aes(x=absences) + geom_histogram(binwidth=1, fill="white",color="black")
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absence.threshold <- median(d$absences)
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## inspect and set the questions cutoff
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## questions.cutoff <- median(d$num.calls)
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## median(d$num.calls)
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## questions.cutoff <- nrow(call.list) / nrow(d) ## TODO talk about this
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## this is the 95% percentile based on simulation in simulation.R
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questions.cutoff <- 4
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questions.cutoff <- 15
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## show the distribution of assessments
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table(call.list$assessment)
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@ -78,6 +78,7 @@ median(d$num.calls)
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## helper function to generate average grade minus number of missing
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gen.part.grade <- function (x.unique.name) {
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q.scores <- question.grades[call.list$assessment[call.list$unique.name == x.unique.name]]
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print(q.scores)
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base.score <- mean(q.scores, na.rm=TRUE)
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## number of missing days
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@ -89,7 +90,6 @@ gen.part.grade <- function (x.unique.name) {
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missing.in.class.days=missing.in.class.days)
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}
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## create the base grades which do NOT include missing questions
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tmp <- do.call("rbind", lapply(d$unique.name, gen.part.grade))
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d <- merge(d, tmp)
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