From f7270293f2febd56d1570fef67085223d5d91d33 Mon Sep 17 00:00:00 2001 From: Benjamin Mako Hill Date: Sun, 27 Oct 2024 15:59:14 -0700 Subject: [PATCH 1/2] updated cold call script to do a pure shuffle - this will just just produce the students present for the day, in random order --- coldcallbot-manual.py | 39 +++++++++++++++++++++++++++++++++++---- 1 file changed, 35 insertions(+), 4 deletions(-) diff --git a/coldcallbot-manual.py b/coldcallbot-manual.py index 61c2010..985ada0 100755 --- a/coldcallbot-manual.py +++ b/coldcallbot-manual.py @@ -3,7 +3,19 @@ from coldcall import ColdCall from datetime import datetime from csv import DictReader +from random import sample import json +import argparse + +parser = argparse.ArgumentParser(description='run the coldcall bot manually to create a coldcall list') + +parser.add_argument('-n', '--num', dest="num_calls", default=100, const=100, type=int, nargs='?', + help="how many students should be called") + +parser.add_argument('-s', '--shuffle', dest="shuffle_roster", action="store_true", + help="select without replacement (i.e., call each person once with n equal to the group size)") + +args = parser.parse_args() current_time = datetime.today() with open("configuration.json") as config_file: @@ -44,8 +56,12 @@ preferred_names = cc.get_preferred_names() students_present = [s for s in registered_students if s not in missing_today] # print("Students present:", students_present) # useful for debug -for i in range(100): - selected_student = cc.select_student_from_list(students_present) +def print_selected(selected_student): + if "print_index" in globals(): + global print_index + else: + global print_index + print_index = 1 try: preferred_name = preferred_names[selected_student] @@ -56,8 +72,23 @@ for i in range(100): pronouns = preferred_pronouns[selected_student] else: pronouns = "[unknown pronouns]" - - print(f"{i + 1}. {preferred_name} :: {pronouns} :: {full_names[selected_student]} :: {selected_student}") + + print(f"{print_index}. {preferred_name} :: {pronouns} :: {full_names[selected_student]} :: {selected_student}") cc.record_coldcall(selected_student) + print_index += 1 ## increase the index + +# if we're in suffle mode +shuffle = args.shuffle_roster + +print_index = 1 + +if shuffle: + for selected_student in sample(students_present, len(students_present)): + print_selected(selected_student) +else: + num_calls = args.num_calls + for i in range(num_calls): + selected_student = cc.select_student_from_list(students_present) + print_selected(selected_student) -- 2.39.5 From f6e45044919f1a80cc2ce90257d7f129e5f693d3 Mon Sep 17 00:00:00 2001 From: Benjamin Mako Hill Date: Tue, 7 Oct 2025 15:37:08 -0700 Subject: [PATCH 2/2] change assessment code for BSOC 2024 --- assessment_and_tracking/compute_final_case_grades.R | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/assessment_and_tracking/compute_final_case_grades.R b/assessment_and_tracking/compute_final_case_grades.R index 93d6d1f..e355052 100644 --- a/assessment_and_tracking/compute_final_case_grades.R +++ b/assessment_and_tracking/compute_final_case_grades.R @@ -1,6 +1,6 @@ ## load in the data ################################# -myuw <- read.csv("../data/2022_winter_COM_481_A_students.csv", stringsAsFactors=FALSE) +myuw <- read.csv("../data/2024_autumn_COMMLD_570_A_joint_students.csv", stringsAsFactors=FALSE) current.dir <- getwd() source("../assessment_and_tracking/track_participation.R") @@ -11,20 +11,20 @@ call.list$timestamp <- as.Date(call.list$timestamp) ## class-level variables gpa.point.value <- 50/(4 - 0.7) -question.grades <- c("PLUS"=100, "CHECK"=100-gpa.point.value, "MINUS"=100-(gpa.point.value*2)) +## question.grades <- c("GOOD"=100, "FAIR"=100-gpa.point.value, "BAD"=100-(gpa.point.value*2)) +question.grades <- c("GOOD"=100, "SATISFACTORY"=100-gpa.point.value, "POOR"=100-(gpa.point.value*2), "NO MEANINGFUL ANSWER"=0) missed.question.penalty <- gpa.point.value * 0.2 ## 1/5 of a full point on the GPA scale ## inspect set the absence threashold ggplot(d) + aes(x=absences) + geom_histogram(binwidth=1, fill="white",color="black") absence.threshold <- median(d$absences) - ## inspect and set the questions cutoff ## questions.cutoff <- median(d$num.calls) ## median(d$num.calls) ## questions.cutoff <- nrow(call.list) / nrow(d) ## TODO talk about this ## this is the 95% percentile based on simulation in simulation.R -questions.cutoff <- 4 +questions.cutoff <- 15 ## show the distribution of assessments table(call.list$assessment) @@ -78,6 +78,7 @@ median(d$num.calls) ## helper function to generate average grade minus number of missing gen.part.grade <- function (x.unique.name) { q.scores <- question.grades[call.list$assessment[call.list$unique.name == x.unique.name]] + print(q.scores) base.score <- mean(q.scores, na.rm=TRUE) ## number of missing days @@ -89,7 +90,6 @@ gen.part.grade <- function (x.unique.name) { missing.in.class.days=missing.in.class.days) } - ## create the base grades which do NOT include missing questions tmp <- do.call("rbind", lapply(d$unique.name, gen.part.grade)) d <- merge(d, tmp) -- 2.39.5