From: Benjamin Mako Hill Date: Tue, 1 Jun 2021 00:06:09 +0000 (-0700) Subject: updated grade code X-Git-Url: https://code.communitydata.science/coldcallbot-discord.git/commitdiff_plain/3bd4c9c2a60797346868989dd63341e48e87da70?hp=da8f47aa270b563087b6ceddf349b7fe70e4f03b updated grade code - COMMLD570A did not penalize/track absences at all so i cut this completely --- diff --git a/assessment_and_tracking/compute_final_case_grades.R b/assessment_and_tracking/compute_final_case_grades.R index 60a60f3..b26270b 100644 --- a/assessment_and_tracking/compute_final_case_grades.R +++ b/assessment_and_tracking/compute_final_case_grades.R @@ -1,36 +1,23 @@ ## load in the data ################################# -case.sessions <- 15 -myuw <- read.csv("myuw-COM_482_A_autumn_2020_students.csv", stringsAsFactors=FALSE) +myuw <- read.csv("myuw-COMMLD_570_A_spring_2021_students.csv", stringsAsFactors=FALSE) ## class-level variables -question.grades <- c("GOOD"=100, "FAIR"=100-(50/3.3), "BAD"=100-(50/(3.3)*2)) -missed.question.penalty <- (50/3.3) * 0.2 ## 1/5 of a full point on the GPA scale +question.grades <- c("GOOD"=100, "FAIR"=100-(50/3.3), "WEAK"=100-(50/(3.3)*2)) source("../assessment_and_tracking/track_participation.R") setwd("case_grades") -rownames(d) <- d$discord.name +rownames(d) <- d$unique.name ## show the distribution of assessments -table(call.list.full$assessment) -prop.table(table(call.list.full$assessment)) -table(call.list.full$answered) -prop.table(table(call.list.full$answered)) +table(call.list$assessment) +prop.table(table(call.list$assessment)) +table(call.list$answered) +prop.table(table(call.list$answered)) -total.questions.asked <- nrow(call.list.full) - -## create new column with number of questions present -d$prop.asked <- d$num.calls / d$num.present - -## generate statistics using these new variables -prop.asks.quantiles <- quantile(d$prop.asked, probs=seq(0,1, 0.01)) -prop.asks.quantiles <- prop.asks.quantiles[!duplicated(prop.asks.quantiles)] - -## this is generating broken stuff but it's not used for anything -d$prop.asked.quant <- cut(d$prop.asked, breaks=prop.asks.quantiles, - labels=names(prop.asks.quantiles)[1:(length(prop.asks.quantiles)-1)]) +total.questions.asked <- nrow(call.list) ## generate grades ########################################################## @@ -39,81 +26,47 @@ d$part.grade <- NA ## print the median number of questions for (a) everybody and (b) ## people that have been present 75% of the time -median(d$num.calls[d$days.absent < 0.25*case.sessions]) median(d$num.calls) questions.cutoff <- median(d$num.calls) ## helper function to generate average grade minus number of missing -gen.part.grade <- function (x.discord.name) { - q.scores <- question.grades[call.list$assessment[call.list$discord.name == x.discord.name]] +gen.part.grade <- function (x.unique.name) { + q.scores <- question.grades[call.list$assessment[call.list$unique.name == x.unique.name]] base.score <- mean(q.scores, na.rm=TRUE) ## number of missing days - missing.days <- nrow(missing.in.class[missing.in.class$discord.name == x.discord.name,]) + # missing.days <- nrow(missing.in.class[missing.in.class$unique.name == x.unique.name,]) ## return the final score - data.frame(discord.name=x.discord.name, - part.grade=(base.score - missing.days * missed.question.penalty)) + data.frame(unique.name=x.unique.name, + part.grade=(base.score)) } -tmp <- do.call("rbind", lapply(d$discord.name[d$num.calls >= questions.cutoff], gen.part.grade)) - -d[as.character(tmp$discord.name), "part.grade"] <- tmp$part.grade - -## next handle the folks *under* the median - -## first we handle the zeros -## step 1: first double check the people who have zeros and ensure that they didn't "just" get unlucky" -d[d$num.calls == 0,] -## set those people to 0 :( -d$part.grade[d$num.calls == 0] <- 0 +tmp <- do.call("rbind", lapply(d$unique.name, gen.part.grade)) -## step 2 is to handle folks who got unlucky in the normal way -tmp <- do.call("rbind", lapply(d$discord.name[is.na(d$part.grade) & d$prop.asked <= median(d$prop.asked)], gen.part.grade)) -d[as.character(tmp$discord.name), "part.grade"] <- tmp$part.grade - -## the people who are left are lucky and still undercounted so we'll penalize them -d[is.na(d$part.grade),] -penalized.discord.names <- d$discord.name[is.na(d$part.grade)] +d[as.character(tmp$unique.name), "part.grade"] <- tmp$part.grade ## generate the baseline participation grades as per the process above -tmp <- do.call("rbind", lapply(penalized.discord.names, gen.part.grade)) -d[as.character(tmp$discord.name), "part.grade"] <- tmp$part.grade - -## now add "zeros" for every questions that is below the normal -d[as.character(penalized.discord.names),"part.grade"] <- (( - (questions.cutoff - d[as.character(penalized.discord.names),"num.calls"] * 0) + - (d[as.character(penalized.discord.names),"num.calls"] * d[as.character(penalized.discord.names),"part.grade"]) ) - / questions.cutoff) - -d[as.character(penalized.discord.names),] ## map part grades back to 4.0 letter scale and points d$part.4point <-round((d$part.grade / (50/3.3)) - 2.6, 2) -d[sort.list(d$prop.asked), c("discord.name", "num.calls", "num.present", - "prop.asked", "prop.asked.quant", "part.grade", "part.4point", - "days.absent")] - -d[sort.list(d$part.4point), c("discord.name", "num.calls", "num.present", - "prop.asked", "prop.asked.quant", "part.grade", "part.4point", - "days.absent")] +d[sort.list(d$part.4point),] ## writing out data -quantile(d$num.calls, probs=(0:100*0.01)) d.print <- merge(d, myuw[,c("StudentNo", "FirstName", "LastName", "UWNetID")], by.x="student.num", by.y="StudentNo") write.csv(d.print, file="final_participation_grades.csv") -library(rmarkdown) +## library(rmarkdown) -for (x.discord.name in d$discord.name) { - render(input="../../assessment_and_tracking/student_report_template.Rmd", - output_format="html_document", - output_file=paste("../data/case_grades/student_reports/", - d.print$UWNetID[d.print$discord.name == x.discord.name], - sep="")) -} +## for (x.unique.name in d$unique.name) { +## render(input="../../assessment_and_tracking/student_report_template.Rmd", +## output_format="html_document", +## output_file=paste("../data/case_grades/student_reports/", +## d.print$UWNetID[d.print$unique.name == x.unique.name], +## sep="")) +## } diff --git a/assessment_and_tracking/track_participation.R b/assessment_and_tracking/track_participation.R index 698041c..28b8a4e 100644 --- a/assessment_and_tracking/track_participation.R +++ b/assessment_and_tracking/track_participation.R @@ -5,7 +5,7 @@ library(data.table) gs <- read.delim("student_information.tsv") d <- gs[,c(2,4)] -colnames(d) <- c("student.num", "teams.name") +colnames(d) <- c("student.num", "unique.name") call.list <- do.call("rbind", lapply(list.files(".", pattern="^call_list-.*tsv$"), function (x) {read.delim(x, stringsAsFactors=FALSE)[,1:4]})) @@ -13,104 +13,13 @@ colnames(call.list) <- gsub("_", ".", colnames(call.list)) table(call.list$unique_name[call.list$answered]) -exit() - -call.list$day <- as.Date(call.list$timestamp) - ## drop calls where the person wasn't present call.list.full <- call.list call.list[!call.list$answered,] call.list <- call.list[call.list$answered,] -call.counts <- data.frame(table(call.list$discord.name)) -colnames(call.counts) <- c("discord.name", "num.calls") - -d <- merge(d, call.counts, all.x=TRUE, all.y=TRUE, by="discord.name"); d - -## set anything that's missing to zero -d$num.calls[is.na(d$num.calls)] <- 0 - -attendance <- unlist(lapply(list.files(".", pattern="^attendance-.*tsv$"), function (x) {d <- read.delim(x); strsplit(d[[2]], ",")})) - -file.to.attendance.list <- function (x) { - tmp <- read.delim(x) - d.out <- data.frame(discord.name=unlist(strsplit(tmp[[2]], ","))) - d.out$day <- rep(as.Date(tmp[[1]][1]), nrow(d.out)) - return(d.out) -} - -attendance <- do.call("rbind", - lapply(list.files(".", pattern="^attendance-.*tsv$"), - file.to.attendance.list)) - -## create list of folks who are missing in class -missing.in.class <- call.list.full[is.na(call.list.full$answered) | - (!is.na(call.list.full$answered) & !call.list.full$answered), - c("discord.name", "day")] - -missing.in.class <- unique(missing.in.class) - -setDT(attendance) -setkey(attendance, discord.name, day) -setDT(missing.in.class) -setkey(missing.in.class, discord.name, day) - -## drop presence for people on missing days -attendance[missing.in.class,] -attendance <- as.data.frame(attendance[!missing.in.class,]) - -attendance.counts <- data.frame(table(attendance$discord.name)) -colnames(attendance.counts) <- c("discord.name", "num.present") - -d <- merge(d, attendance.counts, - all.x=TRUE, all.y=TRUE, - by="discord.name") - -days.list <- lapply(unique(attendance$day), function (day) { - day.total <- table(call.list.full$day == day)[["TRUE"]] - lapply(d$discord.name, function (discord.name) { - num.present <- nrow(attendance[attendance$day == day & attendance$discord.name == discord.name,]) - if (num.present/day.total > 1) {print(day)} - data.frame(discord.name=discord.name, - days.present=(num.present/day.total)) - }) -}) - -days.tmp <- do.call("rbind", lapply(days.list, function (x) do.call("rbind", x))) - -days.tbl <- tapply(days.tmp$days.present, days.tmp$discord.name, sum) - -attendance.days <- data.frame(discord.name=names(days.tbl), - days.present=days.tbl, - days.absent=length(list.files(".", pattern="^attendance-.*tsv$"))-days.tbl) - -d <- merge(d, attendance.days, - all.x=TRUE, all.y=TRUE, by="discord.name") - -d[sort.list(d$days.absent), c("discord.name", "num.calls", "days.absent")] - -## make some visualizations of whose here/not here -####################################################### - -png("questions_absence_histogram_combined.png", units="px", width=800, height=600) - -ggplot(d) + - aes(x=as.factor(num.calls), fill=days.absent, group=days.absent) + - geom_bar(color="black") + - scale_x_discrete("Number of questions asked") + - scale_y_continuous("Number of students") + - scale_fill_continuous("Days absent", low="red", high="blue")+ - theme_bw() - -dev.off() - -png("questions_absenses_boxplots.png", units="px", width=800, height=600) - -ggplot(data=d) + - aes(x=as.factor(num.calls), y=days.absent) + - geom_boxplot() + - scale_x_discrete("Number of questions asked") + - scale_y_continuous("Days absent") +call.counts <- data.frame(table(call.list$unique.name)) +colnames(call.counts) <- c("unique.name", "num.calls") -dev.off() +d <- merge(d, call.counts, all.x=TRUE, all.y=TRUE, by="unique.name"); d