Recalling Words

Background

Many teachers and other educators are interested in understanding how to best deliver new content to students. In general, they have two choices of how to do this.

1. The Meshed Approach
   • Deliver new content while simultaneously reviewing previously understood content.
2. The Before Approach
   • Deliver new content after fully reviewing previously understood content.

A study was performed to determine whether the Meshed or Before approaches to delivering content had any positive benefits on memory recall.

datatable(Friendly, options=list(lengthMenu = c(3,10,30)))

Questions and Hypotheses

What type of learning is a better method, Meshed or Before? I think that Meshed learning is better compared to Before learning.

H0:Before=0

Ha:Meshed>0

Data Analysis

friendly <- dplyr::filter(Friendly, condition %in% c("Meshed", "Before"))

friendly %>% 
    group_by(condition) %>% 
    summarise(minimum = min(correct),
              average = mean(correct),
              median = median(correct),
              maximum = max(correct)) %>% 
    pander()

First step in analysis is analyzing number. This is done by Numerical Summaries. First filter to the condition of learning. Then create a table with the minimum, average, median, and maximum. These numbers help figure out the values for recalling information.

Graphical Summaries

ggplot(friendly, aes(x = condition, y = correct)) + geom_boxplot() + theme_bw()

The graph shows us that the recall rate is higher with before method then meshed. Although there are more outliers when using the Before method.

Interpretation

wilcox.test(correct ~ condition, data = friendly, mu = 0, alternative = "greater", paired = TRUE, conf.level = 0.95) %>% 
    pander()

According to the Wilcoxon test my hypothesis was correct that using the meshed method is better compared to the before method. My P-value is 0.528 which is greater than the confidence interval which is .05. So We will fail to reject the null hypothesis.

We can conclude that meshed learning can be proven more useful compared to before learning. The Numerical and Graphical Summaries conclude that the methods are closely related that statistical tests have to determine the better learning method.