Winter 2024 All Workshops Survey Responses

Number of responses

Code

library(tidyverse)
library(bslib)
library(shiny)
library(bsicons)
source("scripts/helper_functions.R")

# list of workshop IDs to filter results
workshops <- c("2024-02-27-ucsb-webscraping", "2024-01-30-ucsb-git")

results <- read_csv("data-joined/all_workshops.csv") %>% 
  filter(workshop %in% workshops)
  
# Fix comma separator
results <- results %>% 
  mutate(findout_select.pre = str_replace_all(
  findout_select.pre, 
  "Twitter, Facebook, etc.", 
  "Twitter; Facebook; etc."))

pre_survey <- results %>%
  select(ends_with(".pre"))

post_survey <- results %>%
  select(ends_with(".post"))

n_pre <- sum(apply(post_survey, 1, function(row) all(is.na(row))))
n_post <- sum(apply(pre_survey, 1, function(row) all(is.na(row))))
n_total <- nrow(results)
n_both <- nrow(results) - n_pre - n_post

layout_columns(
  value_box(
    title = "Total responses", value = n_total, ,
    theme = NULL, showcase = bs_icon("people-fill"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  ),
  value_box(
    title = "Both pre- and post-", value = n_both, , theme = NULL,
    showcase = bs_icon("arrows-expand-vertical"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  ),
  value_box(
    title = "Only pre-workshop", value = n_pre, ,
    theme = NULL, showcase = bs_icon("arrow-left-short"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  ),
  value_box(
    title = "Only post-workshop", value = n_post, , theme = NULL,
    showcase = bs_icon("arrow-right-short"), showcase_layout = "left center",
    full_screen = FALSE, fill = TRUE, height = NULL
  )
)

Total responses

25

Both pre- and post-

11

Only pre-workshop

13

Only post-workshop

1

Departments

Code

depts <- results %>% select(dept_select.pre) %>% 
  separate_rows(dept_select.pre, sep=",") %>%
  mutate(dept_select.pre = str_trim(dept_select.pre)) %>%
  count(dept_select.pre, name = "count") %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(depts, aes(y=reorder(dept_select.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) +  
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(depts$count)*1.1))

“Other” Departments

Code

other_depts <- results %>% 
  count(dept_other.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(other_depts, aes(y=reorder(dept_other.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(other_depts$count)*1.1))

Current occupation / Career stage

Code

ocup <- results %>% select(occupation.pre) %>% 
  separate_rows(occupation.pre, sep=",") %>%
  mutate(occupation.pre = str_trim(occupation.pre)) %>%
  count(occupation.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(ocup, aes(y=reorder(occupation.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(ocup$count)*1.2))

Motivation - Why are you participating in this workshop?

Code

motiv <- results %>% select(motivation_select.pre) %>% 
  separate_rows(motivation_select.pre, sep=",")  %>% 
  mutate(motivation_select.pre = str_trim(motivation_select.pre)) %>%
  count(motivation_select.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(motiv, aes(y=reorder(motivation_select.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(motiv$count)*1.2))

How did you find out about this workshop?

Code

findw <- results %>% select(findout_select.pre) %>% 
  separate_rows(findout_select.pre, sep=",")  %>% 
  mutate(findout_select.pre = str_trim(findout_select.pre)) %>%
  count(findout_select.pre, name = "count") %>% 
  drop_na() %>% 
  mutate(percent = (count / (n_total - n_post)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(findw, aes(y=reorder(findout_select.pre, count), x=count)) +
    geom_col() +
    geom_label(aes(label = text, hjust = -0.1),
               size = 3) +
    labs(x = "# respondents", y = element_blank()) + 
    theme_minimal() +
    theme(
      panel.grid.minor = element_blank(),
      panel.grid.major.y = element_blank()
      ) +
    expand_limits(x = c(0,max(findw$count)*1.2))

What you most hope to learn?

Code

results %>% group_by(workshop) %>% 
  select(workshop, hopes.pre) %>% 
  drop_na()

workshop	hopes.pre
2024-01-30-ucsb-git	how to set up Git
2024-01-30-ucsb-git	I hope to improve my command line skills with version control. I use GitHub Desktop on a daily basis, but my knowledge of git is pretty much limited to point and click commands on GitHub Desktop.
2024-01-30-ucsb-git	GitHub functioning and commands
2024-01-30-ucsb-git	I’d like to learn how to set up a website using GitHub and also generally learn more about Git and GitHub.
2024-01-30-ucsb-git	Learning GIT to integrate with Terraform
2024-01-30-ucsb-git	How to add git version control to my existing workflow;
2024-02-27-ucsb-webscraping	More comfortable writing scripts for data mining and better data and file management.
2024-02-27-ucsb-webscraping	webscraping tools
2024-02-27-ucsb-webscraping	Learning some basic data analysis techniques
2024-02-27-ucsb-webscraping	How scraping can be done, easily
2024-02-27-ucsb-webscraping	how to do it!
2024-02-27-ucsb-webscraping	It’s been a while since I took my first R workshop and I don’t have a chance to use it much. For now I want to get a handle on the basics and enough vocabulary that when I run into trouble I can find answers on how to fix things in a forum or ask for help.
2024-02-27-ucsb-webscraping	Techniques for gathering, organizing, and analyzing materials from NGO websites
2024-02-27-ucsb-webscraping	How to use Scraper and begin to understand R and Python
2024-02-27-ucsb-webscraping	How to apply webscraping to get jobs in the future
2024-02-27-ucsb-webscraping	Quantitative analysis for online forums (keywords etc)
2024-02-27-ucsb-webscraping	Would like to learn how to use APIs

Learning environment in the workshop

Code

orderedq <- c("Strongly Disagree", "Somewhat Disagree", "Neither Agree or Disagree","Somewhat Agree", "Strongly Agree")
addNA(orderedq)

Code

agree_questions <- results %>% 
  select(join_key, agree_apply.post,    agree_comfortable.post, agree_clearanswers.post,
         agree_instr_enthusiasm.post, agree_instr_interaction.post, agree_instr_knowledge.post
) %>% 
  filter(!if_all(-join_key, is.na))

n_agree_questions <- nrow(agree_questions)
  
agree_questions <- agree_questions %>%
  pivot_longer(cols = -join_key, names_to = "Question", values_to = "Response") %>% 
  mutate(Response = factor(Response, levels = orderedq),
         Question = recode(Question,
                     "agree_apply.post" = "Can immediatly apply 
 what they learned",
                     "agree_comfortable.post" = "Comfortable learning in 
 the workshop environment",
                     "agree_clearanswers.post" = "Got clear answers 
 from instructors",
                     "agree_instr_enthusiasm.post" = "Instructors were enthusiastic",
                     "agree_instr_interaction.post" = "Comfortable interacting 
 with instructors",
                     "agree_instr_knowledge.post" = "Instructors were knowledgeable 
 about the material"
      ))

summary_data <- agree_questions %>%
  count(Question, Response, name = "count") %>% 
  mutate(percent = (count / n_agree_questions) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

ggplot(summary_data, aes(x = Question, y = count, fill = Response)) +
  geom_col(position = "fill", color = "black", show.legend = TRUE) +
  scale_y_continuous(labels = scales::percent_format()) + 
  scale_fill_manual(values = c("Strongly Disagree" = "#d01c8b", 
                               "Somewhat Disagree" = "#f1b6da", 
                               "Neither Agree or Disagree" = "#f7f7f7", 
                               "Somewhat Agree" = "#b8e186", 
                               "Strongly Agree" = "#4dac26"), 
                    na.translate = TRUE, na.value = "#cccccc", 
                    breaks = orderedq, drop = FALSE) +
  geom_text(aes(label = text), size = 3,
             position = position_fill(vjust = 0.5)) +
  labs(y = "# respondents (Percentage)", x = element_blank(), fill = "Responses",
       subtitle = paste0("Number of responses: ", n_agree_questions)) +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1),
        plot.subtitle = element_text(hjust = 0.5, size = 12))

How an instructor or helper affected your learning experience

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, instructor_example.post) %>%
  drop_na()

workshop	instructor_example.post
2024-01-30-ucsb-git	They took the time to thoroughly answer any questions.
2024-01-30-ucsb-git	Seth was very knowledgeable in answering my questions
2024-01-30-ucsb-git	I asked several specific questions during the workshop and the instructors really took the time to give clear helpful answers.
2024-02-27-ucsb-webscraping	providing time to research ourselves and provide answers after
2024-02-27-ucsb-webscraping	Very knowledgeable, keenly mindful of learners’ needs
2024-02-27-ucsb-webscraping	both instructors seemed to me to move really fast; they were doing things on the screen that students were supposed to be also doing on their own screens, but I found it hard to follow their actions. Plus, they really assumed people already knew the Xpath terms and such. This is what an early blurb said: “introducing tools for turning web pages into analyzable data. We will explore common web scraping scenarios and learn how to use a web browser to extract data from websites without needing to write code.” Huh.
2024-02-27-ucsb-webscraping	Answered my question throughly and explained it in a second way
2024-02-27-ucsb-webscraping	The workshop was ok, I don’t feel like I learned 3 hours worth of material. The information provided seemed to be by rote and I didn’t get much of a sense of expertise or a way to understand underlying theory from the instructors.

Skills and perception comparison

Code

# Calculate mean scores and make graph for all respondents (only_matched=FALSE)
tryCatch(
  {
mean_nresp <- get_mean_scores_nresp(results, only_matched=FALSE)
graph_pre_post(mean_nresp$mean_scores, mean_nresp$n_resp_pre, mean_nresp$n_resp_post, mean_nresp$n_resp_pre_post, only_matched=FALSE)
},
error = function(cond) {
message("Could not do the plots as there are no pre or post results to show")
}
)

Code

# Calculate mean scores and make graph for only matched respondents in pre and post (only_matched=TRUE)
tryCatch(
  {
mean_nresp <- get_mean_scores_nresp(results, only_matched=TRUE)
graph_pre_post(mean_nresp$mean_scores, mean_nresp$n_resp_pre, mean_nresp$n_resp_post, mean_nresp$n_resp_pre_post, only_matched=TRUE)
},
error = function(cond) {
message("Could not do the plots as there are no pre or post results to show")
}
)

Workshop Strengths

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, workshop_strengths.post) %>% 
  drop_na()

workshop	workshop_strengths.post
2024-01-30-ucsb-git	small group, organized
2024-01-30-ucsb-git	I think that there was plenty of opportunities to ask questions and get answers
2024-01-30-ucsb-git	This was a good first entry to git.
2024-01-30-ucsb-git	Learning git and git bash
2024-01-30-ucsb-git	It’s well planned, hands-on, and practical.
2024-02-27-ucsb-webscraping	good baseline understanding of how to do webscraping;
2024-02-27-ucsb-webscraping	Practicality
2024-02-27-ucsb-webscraping	the first bit, the kind of intense introduction to XPath and its use in exploring HTML pages was probably good for people well prepared in advance. Tough if you don’t really know the HTML terminology.
2024-02-27-ucsb-webscraping	Learned a lot of new information, taught in a way that was easy and accessible.
2024-02-27-ucsb-webscraping	I’m sorry I can’t think of any right now - I feel like I would have been just as well served with a link to the tool and a web tutorial.

Ways to improve the workshop

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, workshop_improved.post) %>% 
  drop_na()

workshop	workshop_improved.post
2024-01-30-ucsb-git	none, it was great
2024-01-30-ucsb-git	I think it would have also been helpful to show how to start a new respository on Github first
2024-01-30-ucsb-git	I was already quite familiar with git, but I was unfamiliar with git on the command line. I mention this because I think the topic of version control can be very confusing to newcomers. For people who are brand new to the whole topic, who I believe would be the target audience, I think it might be helpful to spend more time at the beginning going over what version control is about and the benefits of using it. You already do this, but I would expand out on it.
2024-01-30-ucsb-git	Make it more clear what programs need to be downloaded and installed prior to the workshop.
2024-02-27-ucsb-webscraping	Maybe go over more examples of how webscraping can be used in research settings.
2024-02-27-ucsb-webscraping	make it really introductory? Persuade me that scraping a web site is quicker and faster than just copying it and pasting it into excel or word and then extracting what I want. Don’t assume I know what you mean by an “anchor.”
2024-02-27-ucsb-webscraping	Better explanation of possible uses for these tools
2024-02-27-ucsb-webscraping	It felt like the XPath instructor didn’t know much about the Scraper tool, but I think that doesn’t necessarily need to be resolved more even knowledge of the entire workshop maybe
2024-02-27-ucsb-webscraping	I understand starting us with the basics but talking us through or referring us to how it could be built into something more complex is a loop I was expecting to see completed but never came about. Even if there’s no time to demo starting with something that we’d actually want to apply, then walking the more complex topic back would have been more useful.

How likely are you to recommend this workshop? Scale 0 - 10

Code

orderedq <- c("Detractor", "Passive", "Promoter")

nps <- results %>% 
  count(recommend_group.post, recommende_score.post, name = "count") %>% 
  drop_na() %>% 
  mutate(recommend_group.post = factor(recommend_group.post, levels = orderedq),
         percent = (count/sum(count)) * 100,
         text = sprintf("%.0f (%.0f%%)", count, percent))

nps %>% 
ggplot(aes(x=recommende_score.post, y=count, fill=recommend_group.post)) +
  geom_col(color="black", show.legend = TRUE) +
  scale_fill_manual(values = c("Detractor" = "#af8dc3", "Passive" = "#f7f7f7", "Promoter" = "#7fbf7b"), breaks = c("Detractor", "Passive", "Promoter"), drop = FALSE) +
  geom_label(aes(label = text, vjust = -0.5), fill = "white", size= 3) +
  scale_x_continuous(breaks = 1:10) +
  labs(x = "NPS Score", y = "# respondents", subtitle = paste0("Number of responses: ", sum(nps$count), "
 Mean score: ", format(weighted.mean(nps$recommende_score.post, nps$count), digits = 3))) +
  theme_minimal() +
  theme(
    panel.grid.minor = element_blank(),
    panel.grid.major.x = element_blank(),
    plot.subtitle = element_text(hjust = 0.5, size = 12)
  ) +
  expand_limits(x = c(1,10),
                y = c(0, max(nps$count)*1.1))

Topic Suggestions

Code

results %>% 
  group_by(workshop) %>% 
  select(workshop, suggest_topics.post) %>% 
  drop_na()

workshop	suggest_topics.post
2024-01-30-ucsb-git	python gis libraries (e.g., shapely, rasterio)
2024-01-30-ucsb-git	Already gave suggestions.
2024-02-27-ucsb-webscraping	R studio and git
2024-02-27-ucsb-webscraping	hard to say. I think there was a very wide range of skills and backgrounds in the room. So you quite likely hit the sweet spot. But I would need more background and slower pace.
2024-02-27-ucsb-webscraping	Second session on scraping?
2024-02-27-ucsb-webscraping	I’d be interested in the second part of Web scraping workshop
2024-02-27-ucsb-webscraping	Text analysis tools