library(readr)
motivation <- read_csv("~/Downloads/motivation.csv")
## Rows: 9 Columns: 30
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (6): Gender, Afdeling_coschap, Previous_Ed, Failed, relevance_coschap, ...
## dbl (24): User ID, Intrinsic Motivation_Med, Identified Regulation_Med, Intr...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ purrr 1.0.2
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
# Load necessary libraries
library(dplyr)
library(tidyr)
library(ggplot2)
# Check the column names
names(motivation)
## [1] "User ID" "Intrinsic Motivation_Med"
## [3] "Identified Regulation_Med" "Introjected Regulation_Med"
## [5] "External Regulation_Med" "Amotivation_Med"
## [7] "AM_Med" "CM_Med"
## [9] "RAM_Med" "Intrinsic Motivation_KNO"
## [11] "Identified Regulation KNO" "Introjected Regulation_KNO"
## [13] "External Regulation_KNO" "Amotivation_KNO"
## [15] "AM_KNO" "CM_KNO"
## [17] "RAM_KNO" "Level_Completed"
## [19] "Questions_Attemped" "Gender"
## [21] "Block" "Afdeling_coschap"
## [23] "Previous_Ed" "Failed"
## [25] "relevance_coschap" "relevance_career"
## [27] "Both" "Questionaire_only"
## [29] "Questions_only" "None"
# Summarize the data to count the number of 1s in each category
counts <- motivation %>%
summarise(
Questionnaire = sum(Questionaire_only == 1, na.rm = TRUE),
Both = sum(Both == 1, na.rm = TRUE),
Questions = sum(Questions_only == 1, na.rm = TRUE),
None = sum(None == 1, na.rm = TRUE)
)
# Convert the summary to a long format for ggplot2
counts_long <- counts %>%
pivot_longer(cols = everything(), names_to = "Category", values_to = "Count")
# Create a custom color palette
custom_colors <- c("Questionnaire" = "#FFB6C1", # Baby Pink
"Questions" = "#89CFF0", # Baby Blue
"None" = "#98FB98", # Baby Green
"Both" = "#FFFFE0") # Light Yellow
# Create the bar graph with custom colors
ggplot(counts_long, aes(x = Category, y = Count, fill = Category)) +
geom_bar(stat = "identity", position = position_dodge(width = 10)) +
scale_fill_manual(values = custom_colors) + # Apply custom colors
labs(title = "Participant Response Distribution", x = "Category", y = "Count") +
theme_minimal()
# Load necessary libraries
library(ggplot2)
# Create the histogram
ggplot(motivation, aes(x = Gender, fill = Gender)) +
geom_bar() +
labs(title = "Number of Women and Men", x = "Gender", y = "Count") +
scale_fill_manual(values = c("vrouw" = "pink", "man" = "#89CFF0")) + # Custom colors for genders
theme_minimal() +
scale_x_discrete(labels = c("vrouw" = "Female", "man" = "Male"))
library(scales)
##
## Attaching package: 'scales'
## The following object is masked from 'package:purrr':
##
## discard
## The following object is masked from 'package:readr':
##
## col_factor
ggplot(motivation, aes(x = RAM_Med, y = RAM_KNO, color = as.factor(row.names(motivation)))) +
geom_point(size = 5) +
scale_color_discrete() +
labs(title = "Scatterplot of RAM Medicine vs RAM KNO",
x = "RAM Medicine",
y = "RAM KNO") +
xlim(-1, 15) +
ylim(-1, 15) +
theme_minimal() +
theme(legend.position = "none")
motivation$Group <- ifelse(motivation$Afdeling_coschap == "KNO", "KNO", "non-KNO")
ggplot(motivation, aes(x = Group)) +
geom_bar(fill = c("yellow", "pink")) +
labs(x = "Group", y = "Count", title = "Distribution of KNO and non-KNO") +
theme_minimal()
motivation$Group <- ifelse(motivation$Afdeling_coschap == "KNO", "KNO", "non-KNO")
ggplot(data= motivation, aes(x = Group, fill=relevance_coschap)) +
geom_bar(position='fill') +
labs(x = "Group", y = "Proportion", fill= 'relevance coschap', title='Distribution of relevance by afdeling coschap') +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
install.packages("ggmosaic", repos = "https://cloud.r-project.org/")
##
## The downloaded binary packages are in
## /var/folders/3g/ln4t2cvs3250dv7p12p13c_c0000gn/T//RtmpwltFw6/downloaded_packages
library(ggmosaic)
library(ggplot2)
# Assuming your data frame is named motivation
motivation$Afdeling_coschap <- as.factor(motivation$Afdeling_coschap)
motivation$relevance_coschap <- as.factor(motivation$relevance_coschap)
ggplot(data = motivation) +
geom_mosaic(aes(x = product(Afdeling_coschap), fill = relevance_coschap), na.rm = TRUE) +
labs(x = "Afdeling_coschap", fill = "Relevance_coschap") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplot(data = motivation, aes(x = Afdeling_coschap, fill = relevance_coschap)) +
geom_bar(position = "fill") +
labs(y = "Proportion", x = "Afdeling_coschap", fill = "Relevance_coschap") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplot(data = motivation, aes(x = Afdeling_coschap, fill = relevance_coschap)) +
geom_bar() +
labs(y = "Count", x = "Afdeling_coschap", fill = "Relevance_coschap") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
library(ggplot2)
# Exclude rows with NA values in Afdeling_coschap or relevance_coschap
motivation_clean <- na.omit(motivation[, c("Afdeling_coschap", "relevance_coschap")])
# Create the plot
ggplot(data = motivation_clean, aes(x = Afdeling_coschap, fill = relevance_coschap)) +
geom_bar(position = "fill") +
labs(y = "Proportion", x = "Afdeling_coschap", fill = "Relevance_coschap", title='Distribution of relevance by afdeling coschap') +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplot(data = motivation, aes(x = relevance_coschap, y = RAM_KNO)) +
geom_boxplot() +
labs(
title = "Effect of Relevance Coschap on Motivation to Study KNO",
x = "Relevance Coschap",
y = "Motivation to Study KNO (RAM)"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplot(data = motivation, aes(x = relevance_coschap, y = RAM_KNO)) +
geom_violin() +
labs(
title = "Effect of Relevance Coschap on Motivation to Study KNO",
x = "Relevance Coschap",
y = "Motivation to Study KNO (RAM)"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
ggplot(data = motivation, aes(x = relevance_coschap, y = RAM_KNO)) +
geom_violin(trim = FALSE) + # Violin plot without trimming the tails
geom_boxplot(width = 0.1, fill = "white") + # Box plot inside the violin plot
labs(
title = "Effect of Relevance Coschap on Motivation to Study KNO",
x = "Relevance Coschap",
y = "Motivation to Study KNO (RAM)"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
library(ggplot2)
motivation$relevance_coschap <- as.factor(motivation$relevance_coschap)
# Box plot for AM_KNO
p1 <- ggplot(data = motivation, aes(x = relevance_coschap, y = AM_KNO)) +
geom_boxplot() +
labs(
title = "Effect of Relevance Coschap on AM_KNO",
x = "Relevance Coschap",
y = "Autonomous Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0,7)
# Box plot for CM_KNO
p2 <- ggplot(data = motivation, aes(x = relevance_coschap, y = CM_KNO)) +
geom_boxplot() +
labs(
title = "Effect of Relevance Coschap on CM_KNO",
x = "Relevance Coschap",
y = "Controlled Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0,7)
# Display plots side by side
install.packages("gridExtra", repos = "https://cloud.r-project.org/")
##
## The downloaded binary packages are in
## /var/folders/3g/ln4t2cvs3250dv7p12p13c_c0000gn/T//RtmpwltFw6/downloaded_packages
library(gridExtra)
##
## Attaching package: 'gridExtra'
## The following object is masked from 'package:dplyr':
##
## combine
grid.arrange(p1, p2, ncol = 2)
library(ggplot2)
motivation$relevance_career <- as.factor(motivation$relevance_career)
# Box plot for AM_KNO
p1 <- ggplot(data = motivation, aes(x = relevance_career, y = AM_KNO)) +
geom_boxplot() +
labs(
title = "Effect of Relevance Career on AM_KNO",
x = "Relevance Career",
y = "Autonomous Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0,7)
# Box plot for CM_KNO
p2 <- ggplot(data = motivation, aes(x = relevance_career, y = CM_KNO)) +
geom_boxplot() +
labs(
title = "Effect of Relevance Career on CM_KNO",
x = "Relevance Career",
y = "Controlled Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0,7)
# Display plots side by side
library(gridExtra)
grid.arrange(p1, p2, ncol = 2)
install.packages("ggbeeswarm", repos = "https://cloud.r-project.org/")
##
## The downloaded binary packages are in
## /var/folders/3g/ln4t2cvs3250dv7p12p13c_c0000gn/T//RtmpwltFw6/downloaded_packages
library(ggbeeswarm)
# Bee swarm plot for AM_KNO
p1 <- ggplot(data = motivation, aes(x = relevance_career, y = AM_KNO)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Career on AM_KNO",
x = "Relevance Career",
y = "Autonomous Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Bee swarm plot for CM_KNO
p2 <- ggplot(data = motivation, aes(x = relevance_career, y = CM_KNO)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Career on CM_KNO",
x = "Relevance Career",
y = "Controlled Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Display plots side by side
library(gridExtra)
grid.arrange(p1, p2, ncol = 2)
library(ggbeeswarm)
motivation$relevance_coschap <- as.factor(motivation$relevance_coschap)
library(ggplot2)
# Bee swarm plot for AM_KNO
p1 <- ggplot(data = motivation, aes(x = relevance_coschap, y = AM_KNO)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Coschap on AM_KNO",
x = "Relevance Coschap",
y = "Autonomous Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Bee swarm plot for CM_KNO
p2 <- ggplot(data = motivation, aes(x = relevance_coschap, y = CM_KNO)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Coschap on CM_KNO",
x = "Relevance Coschap",
y = "Controlled Motivation for KNO"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Display plots side by side
library(gridExtra)
grid.arrange(p1, p2, ncol = 2)
library(ggbeeswarm)
library(ggplot2)
library(gridExtra)
motivation$RowID <- as.factor(seq_len(nrow(motivation)))
motivation$relevance_coschap <- as.factor(motivation$relevance_coschap)
motivation$relevance_career <- as.factor(motivation$relevance_career)
# Bee swarm plot for AM_KNO with relevance_coschap
p1 <- ggplot(data = motivation, aes(x = relevance_coschap, y = AM_KNO, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Coschap on AM_KNO",
x = "Relevance Coschap",
y = "Autonomous Motivation for KNO",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Bee swarm plot for CM_KNO with relevance_coschap
p2 <- ggplot(data = motivation, aes(x = relevance_coschap, y = CM_KNO, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Coschap on CM_KNO",
x = "Relevance Coschap",
y = "Controlled Motivation for KNO",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Display plots side by side
grid.arrange(p1, p2, ncol = 2)
# Bee swarm plot for AM_KNO with relevance_career
p3 <- ggplot(data = motivation, aes(x = relevance_career, y = AM_KNO, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Career on AM_KNO",
x = "Relevance Career",
y = "Autonomous Motivation for KNO",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Bee swarm plot for CM_KNO with relevance_career
p4 <- ggplot(data = motivation, aes(x = relevance_career, y = CM_KNO, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Career on CM_KNO",
x = "Relevance Career",
y = "Controlled Motivation for KNO",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
ylim(0, 7)
# Display plots side by side
grid.arrange(p3, p4, ncol = 2)
library(ggbeeswarm)
library(ggplot2)
library(gridExtra)
motivation$RowID <- as.factor(seq_len(nrow(motivation)))
motivation$relevance_coschap <- as.factor(motivation$relevance_coschap)
motivation$relevance_career <- as.factor(motivation$relevance_career)
# Bee swarm plot for AM_KNO with relevance_coschap
p1 <- ggplot(data = motivation, aes(x = relevance_coschap, y = Questions_Attemped, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Coschap App Engagement",
x = "Relevance Coschap",
y = "Questions Attempted",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
# Bee swarm plot for CM_KNO with relevance_coschap
p2 <- ggplot(data = motivation, aes(x = relevance_coschap, y = Level_Completed, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Coschap on App Engagement",
x = "Relevance Coschap",
y = "Levels Completed",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
# Display plots side by side
grid.arrange(p1, p2, ncol = 2)
# Bee swarm plot for AM_KNO with relevance_career
p3 <- ggplot(data = motivation, aes(x = relevance_career, y = Questions_Attemped, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Career on App Engagement",
x = "Relevance Career",
y = "Questions Attempted",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
# Bee swarm plot for CM_KNO with relevance_career
p4 <- ggplot(data = motivation, aes(x = relevance_career, y = Level_Completed, color = RowID)) +
geom_quasirandom(width = 0.2) +
labs(
title = "Effect of Relevance Career on App Engagement",
x = "Relevance Career",
y = "Levels Completed",
color = "User ID"
) +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
# Display plots side by side
grid.arrange(p3, p4, ncol = 2)
# Replace 'YourUsername' with your actual username
setwd("~/Desktop/bachelor project")
# Verify the working directory
getwd()
## [1] "/Users/annathemistokleous/Desktop/bachelor project"