MAET Technology Survey - Results

Just comparing pre-post survey results

Loading data

library(googlesheets)
library(tidyverse)
d <- read_csv("2017-10-27-MAET-tech-survey-all-data.csv")
sd <- read_csv("2017-10-27-MAET-tech-survey-key.csv")

With all variables

d %>%
  group_by(time) %>% 
  summarize_at(.vars = vars(`Overall Confidence`:`Navigate a Firewall`), mean) %>% 
  gather(key, val, -time) %>% 
  ggplot(aes(x = reorder(key, val), y = val, fill = time)) +
  geom_col(position = "dodge") +
  coord_flip() +
  xlab(NULL) +
  ylab("Value") +
  scale_fill_brewer("Survey Timepoint",  type = "qual") +
  theme_bw() +
  ggtitle("MAET Technology Survey Responses From 2013-2017 (n = 74)")

By grouping variables

Variable definitions:

• Overall: represents overall confidence and overall confidence for teaching and learning

• 1: represents don’t do it / haven’t done it over the past five years
• 2: represents may do it / have possibly done it over the past five years

• 3: represents definitely do it / have used it over the past five years

x <- sd[1, ] %>% 
  select(-Timestamp, -date, -year, -`Want to Learn More`) %>% 
  gather(key, var_type, -time) %>% 
  mutate(var_type = case_when(
    var_type == "Overall" ~ "Overall",
    var_type == 1 ~ "Low Alignment",
    var_type == 2 ~ "Medium Alignment",
    var_type == 3 ~ "High Alignment"
  ))

d %>%
  select(-Timestamp, -date, -year, -`Most Important`) %>% 
  gather(key, val, -time) %>% 
  left_join(x, by = "key") %>% 
  rename(time = time.x) %>% 
  group_by(time, var_type) %>% 
  mutate(val= as.numeric(val)) %>% 
  summarize(mean_val = mean(val, na.rm = T)) %>% 
  ggplot(aes(x = reorder(var_type, mean_val), y = mean_val, fill = time)) +
  geom_col(position = "dodge") +
  coord_flip() +
  xlab(NULL) +
  ylab("Value") +
  scale_fill_brewer("Survey Timepoint",  type = "qual") +
  theme_bw() +
  ggtitle("MAET Technology Survey Responses From 2013-2017 (n = 74)")

d %>% 
  select(-Timestamp, -year, -date, -`Most Important`) %>% 
  gather(key, val, -time) %>% 
  left_join(x, by = "key") %>% 
  select(time = time.x, everything(), -time.y) %>% 
  filter(var_type == "Overall") %>% 
  tidyttest::t_test(val, time)

## [1] "mean in group post  is  4.152"
## [1] "mean in group pre  is  3.791"
## [1] "Test statistic is  4.718"
## [1] "P-value is  0"
## [1] "Effect size is  0.56"

d %>% 
  select(-Timestamp, -year, -date, -`Most Important`) %>% 
  gather(key, val, -time) %>% 
  left_join(x, by = "key") %>% 
  select(time = time.x, everything(), -time.y) %>% 
  filter(var_type == "Low Alignment") %>% 
  tidyttest::t_test(val, time)

## [1] "mean in group post  is  3.766"
## [1] "mean in group pre  is  3.251"
## [1] "Test statistic is  11.645"
## [1] "P-value is  0"
## [1] "Effect size is  0.38"

d %>% 
  select(-Timestamp, -year, -date, -`Most Important`) %>% 
  gather(key, val, -time) %>% 
  left_join(x, by = "key") %>% 
  select(time = time.x, everything(), -time.y) %>% 
  filter(var_type == "Medium Alignment") %>% 
  tidyttest::t_test(val, time)

## [1] "mean in group post  is  4.459"
## [1] "mean in group pre  is  4.143"
## [1] "Test statistic is  6.001"
## [1] "P-value is  0"
## [1] "Effect size is  0.29"

d %>% 
  select(-Timestamp, -year, -date, -`Most Important`) %>% 
  gather(key, val, -time) %>% 
  left_join(x, by = "key") %>% 
  select(time = time.x, everything(), -time.y) %>% 
  filter(var_type == "High Alignment") %>% 
  tidyttest::t_test(val, time)

## [1] "mean in group post  is  4.489"
## [1] "mean in group pre  is  3.943"
## [1] "Test statistic is  8.812"
## [1] "P-value is  0"
## [1] "Effect size is  0.52"