Aanaluse autumn 2025

Author: richelbilderbeek

evaluations/202511_course/README.md

@@ -1 +1,9 @@
 # Evaluation 2025-11
+
+- [analysis.R](analyse.R)
+
+## [Analysis](analyse.R)
+
+- The same data as a table: [confidences_course.csv](confidences_course.csv)
+
+![Confidences per question](confidences_per_question.png)

evaluations/202511_course/analyse.R

@@ -0,0 +1,83 @@
+#!/bin/env Rscript
+
+read_day_1_confidences <- function() {
+  readr::read_csv("../../../naiss_intro_python/docs/evaluations/20251127//average_confidences.csv", show_col_types = FALSE)
+}
+read_day_2_confidences <- function() {
+  readr::read_csv("../20251128_day_2/average_confidences.csv", show_col_types = FALSE)
+}
+read_day_3_confidences <- function() {
+  readr::read_csv("../20251201_day_3/average_confidences.csv", show_col_types = FALSE)
+}
+read_day_4_confidences <- function() {
+  readr::read_csv("../20251202_day_4/average_confidences.csv", show_col_types = FALSE)
+}
+
+get_day_1_condidences <- function() {
+  t <- read_day_1_confidences()
+  names(t) <- c("learning_outcomes", "average_confidence")
+  t$day <- 1
+  t
+}
+get_day_2_condidences <- function() {
+  t <- read_day_2_confidences()
+  names(t) <- c("learning_outcomes", "average_confidence")
+  t$day <- 2
+  t
+}
+get_day_3_condidences <- function() {
+  t <- read_day_3_confidences()
+  names(t) <- c("learning_outcomes", "average_confidence")
+  t$day <- 3
+  t
+}
+get_day_4_condidences <- function() {
+  t <- read_day_4_confidences()
+  names(t) <- c("learning_outcomes", "average_confidence")
+  t$day <- 4
+  t
+}
+get_condidences <- function() {
+  dplyr::bind_rows(
+    get_day_1_condidences(),
+    get_day_2_condidences(),
+    get_day_3_condidences(),
+    get_day_4_condidences()
+  )
+}
+
+t <- get_condidences()
+t$day <- as.factor(t$day)
+t <- t |> dplyr::arrange(average_confidence)
+t$learning_outcomes <- as.factor(t$learning_outcomes)
+t$learning_outcomes <- reorder(
+  x = t$learning_outcomes,
+  X = order(t$average_confidence),
+  decreasing = TRUE
+)
+readr::write_csv(t, "confidences_course.csv")
+
+average_average_confidence <- mean(t$average_confidence)
+
+ggplot2::ggplot(t,
+  ggplot2::aes(
+    x = average_confidence,
+    y = learning_outcomes,
+    fill = day
+  )
+) +
+  ggplot2::geom_col() +
+  ggplot2::geom_vline(xintercept = average_average_confidence, lty = "dashed") +
+  ggplot2::theme(
+    strip.text.y = ggplot2::element_text(angle = 0),
+    legend.position = "bottom",
+    axis.text = ggplot2::element_text(size = 7)
+  ) +
+  ggplot2::labs(
+    title = "Confidences per question",
+    caption = paste0(
+      " Dashed line denotes the average at ", round(average_average_confidence, digits = 2)
+    )
+  )
+
+ggplot2::ggsave(filename = "confidences_per_question.png", width = 7, height = 7)

evaluations/202511_course/confidences_course.csv

@@ -0,0 +1,36 @@
+learning_outcomes,average_confidence,day
+I can determine which ML and DL modules are installed at a center,2,4
+I can run a Python code that uses PyTorch,2.25,4
+I can run a Python code that uses TensorFlow,2.5,4
+I am comfortable using a Python book,2.6666666666666665,1
+I can write a batch script that uses GPUs,2.75,4
+I know the basics of using the different parallelization tools in Python,2.75,4
+I can make a plot with Seaborn,2.8,3
+"I can use Pandas (basic operations - statistics, binary operators, vectorized math, string methods)",2.8,3
+"I can use Pandas (inspect, clean, and sort data for later operations)",2.8,3
+I can load a Python (machine learning) module,3,4
+I know how a simple for loop can be parallelized with Multiprocessing and how it can run on multiple cores,3,4
+I can use Pandas (input/output Pandas data),3.2,3
+I can write a batch script,3.4,3
+I can check that I am in an interactive session,3.5,2
+I can decide on useful file formats for big data,3.6,3
+I can use a text editor on my HPC cluster,3.6666666666666665,1
+I can use the compute nodes interactively,3.75,2
+I can submit a script to the job scheduler,3.8,3
+I am comfortable using the documentation of my HPC center,4,1
+"I can work (create, activate, work, deactivate) with a venv virtual environment",4,2
+I can create plots in matplotlib,4,3
+I can determine if a Python package is installed,4.25,2
+I can use a Python IDE,4.25,2
+I can describe what the Python interpreter is,4.333333333333333,1
+I can run a Python script that uses a graphical library on an HPC cluster,4.333333333333333,1
+I can find and load a Python package module,4.5,2
+I can install Python packages,4.5,2
+I can read and write to/from a file in Python,4.666666666666667,1
+I am comfortable learning Python,5,1
+I can convert a simple equation to Python code,5,1
+I can convert a simple text question to Python code,5,1
+I can create a Python script,5,1
+I can create and use a variable in Python,5,1
+I can load a Python version on my HPC cluster,5,1
+I can run a Python script,5,1