Experiment 1A: Amazon Turk Master’s Participants

Authors

Matt Crump

Shifa Maqsood

Abstract

This is a reproducible analysis script for Experiment 1A.

Data collected 4/19/23

Data were not usable due to most participants not completing the task. Participants were recruited from Amazon’s Mechanical Turk with minimal restrictions. The data are not included here or analysed further. This script also a generates a prediction graph.

Load libraries

library(dplyr)
library(tidyverse)
library(jsonlite)
library(xtable)
library(data.table)

Predictions

prediction_graph <- tibble(
  `Hypothesis` = rep(c("H1: Retrieval Practice \n Improves Recall \n for Case and Semantic","H2: Retrieval Practice \n Improves Recall \n For All"),each=6),
  `Study Instruction` = factor(rep(c("Case","Semantic","Self","Case","Semantic","Self"),2),
                                  levels= c("Case","Semantic","Self")),
  `Retrieval Practice` = rep(rep(c("No Retrieval Practice \n during study \n", "Retrieval Practice \n during study \n"),each =3),2),
  `Predicted Recall` = c(1,2,3,3,3,3,1,2,3,2,3,4)
  )


ggplot(prediction_graph,aes(x=`Study Instruction`, 
                            y = `Predicted Recall`, 
                            fill = `Retrieval Practice`)) +
  geom_bar(stat="identity", position="dodge", color="black") +
  facet_wrap(~`Hypothesis`) +
  ylab("Predicted # Words Recalled") +
  theme_classic(base_size = 15)

save data

save.image("data/E1_A.RData")