Summer 2022 R Workshop 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("2022-07-26-ucsb-R")

results <- read_csv("data-joined/all_workshops.csv") %>% 
  filter(workshop %in% workshops)

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

28

Both pre- and post-

6

Only pre-workshop

20

Only post-workshop

2

Departments

Code

depts <- results %>% select(dept_select.pre) %>% 
  separate_rows(dept_select.pre, sep=",") %>% 
  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=",") %>% 
  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=",")  %>% 
  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=",")  %>% 
  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
2022-07-26-ucsb-R	’-learn new skills to apply to schoolwork or jobs or internships; -gain experience and knowledge
2022-07-26-ucsb-R	How to efficiently analyze data
2022-07-26-ucsb-R	how to use R for future research data analysis
2022-07-26-ucsb-R	I hope to grasp a better understanding of coding with R and how I can apply it in my career or research (be more comopetitive).
2022-07-26-ucsb-R	The basics of R and how to use it for research
2022-07-26-ucsb-R	New skills for data analysis in R
2022-07-26-ucsb-R	Technical skills and problem solving
2022-07-26-ucsb-R	I want to gain new skills for a potential career in data analysis or data science
2022-07-26-ucsb-R	I hope to learn how to use R more efficiently so that I can organize and analyze my research data better/quicker.
2022-07-26-ucsb-R	Be more comfortable using R.
2022-07-26-ucsb-R	I am hoping to learn background on how to use r studio so that I can analyze my own data
2022-07-26-ucsb-R	Leanr the basics
2022-07-26-ucsb-R	I hope to improve my data management and analysis skillset by learning beginner code in R. I already know and use Stata but would love to learn another data manipulation tool for my research and career.
2022-07-26-ucsb-R	Gain some skills with R and data analysis that I can apply to a job in the future hopefully in some field of biology. If not maybe this workshop will inspire me to look in other directions.
2022-07-26-ucsb-R	I’d like to learn if investing time into learning R is better than continuing to use MS Access, excel, jmp, and other programs for data management and analysis
2022-07-26-ucsb-R	Anything

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
2022-07-26-ucsb-R	Chris was particularly helpful in answering my nuanced questions and kindly provided additional resources upon request.
2022-07-26-ucsb-R	I attended the workshop via zoom and the instructors and helpers online made sure that we were able to access any of the material presented in the physical classroom.
2022-07-26-ucsb-R	How the workshop was led and managed was very organized and prepared. The instructors/helpers dealt with students’ questions immediately in various ways during the session (i.e., chat room, workshop room. I appreciate the prepared commends and codes bc I was able to revisit what I missed later and will do so later again. I greatly appreciate them all.
2022-07-26-ucsb-R	I had a question about a violin graph and one of the instructors gave an explanation how it was similar to a histogram and it made sense.
2022-07-26-ucsb-R	they answered my question thoroughly and with examples

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
2022-07-26-ucsb-R	It was super helpful to have so many different instructors/helpers, because I was able to find individuals with whom I felt comfortable asking for assistance from and who had different knowledge/expertise to share.
2022-07-26-ucsb-R	’- Workshop covered a wide range of topics; - Provided detailed answers to questions and instructors were honest when they were unsure of the answer; - Workshop material was very digestible and seems applicable to many fields
2022-07-26-ucsb-R	‘-provided the core and essential contents with an actual data. ; -dealt with the survey feedback and students’ questions ; -various teachers helped to share more information with students;
2022-07-26-ucsb-R	Having remote instruction as an option was perfect for me. I think everyone did a good job balancing between the remote and in-person attendees.
2022-07-26-ucsb-R	The pacing was just right
2022-07-26-ucsb-R	Having a day in between workshop days
2022-07-26-ucsb-R	I like that the copy of the code was supplied with lesson. Instructors were very helpful.
2022-07-26-ucsb-R	interactive, friendly learning place

Ways to improve the workshop

Code

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

workshop	workshop_improved.post
2022-07-26-ucsb-R	It would be super helpful if there was an additional day allotted to this workshop as we were unable to cover everything as planned.
2022-07-26-ucsb-R	’- There were a few uncertainties in the material taught on the 2nd day; - Some parts of the workshop were a bit fast paced; - There were a few technical difficulties on zoom in the beginning (but they were resolved in the end);
2022-07-26-ucsb-R	Everything was good. thank you.
2022-07-26-ucsb-R	Perhaps providing the scripts ahead or time or afterward so that we can re-do the lessons at our leisure after the workshop.
2022-07-26-ucsb-R	would have liked to learn how to import data (e.g., from csv files, etc) to work with.
2022-07-26-ucsb-R	I think some of the instructors that are not teaching at the moment should be monitoring the room a bit more. I was stuck and put up my pink sticky note, but didn’t get help until the break.
2022-07-26-ucsb-R	n/a;

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
2022-07-26-ucsb-R	More R workshops please and thank you! :D
2022-07-26-ucsb-R	Data cleaning and how to process raw data into a form where we could apply the analysis and visualization techniques from this workshop to
2022-07-26-ucsb-R	Perhaps additional workshops for practicing with R, especially using examples from environmental science. Working through more examples would help strengthen the techniques I learned.
2022-07-26-ucsb-R	Multivariate analysis in R!!! (e.g., regression, two-way tables with t-tests/chi2, etc); Importing data (from csv, etc) and cleaning it. For example, if we conduct a survey and the responses are all in a file and we want to analyze them in R
2022-07-26-ucsb-R	Data Cleaning and Analysis in R or Python