lecture_learning: Lecture Delivery Method and Learning Outcomes

In OpenIntroStat/openintro: Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

Lecture Delivery Method and Learning Outcomes

Description

Data was collected from 276 students in a university psychology course to determine the effect of lecture delivery method on learning. Students were presented a live lecture by the professor on one day and a pre-recorded lecture on a different topic by the same professor on a different day. Survey data was collected during the lectures to determine mind wandering, interest, and motivation. Students were also ultimately asked about the preferred lecture delivery method. Finally, students completed an assessment at the end of the lecture to determine memory recall.

Usage

lecture_learning

Format

A data frame with 552 rows and 8 variables.

student

Identification number of a specific student. Each identification appears twice because same student heard both lecture delivery methods.

gender

Gender of student. Recored a binary variable with levels Male and Female in the study.

method

Delivery method of lecture was either in-person(Live) or pre-recorded(Video).

mindwander

An indicator of distraction during the lecture. It is a proportion of six mind wandering probes during the lecture when a student answered yes that mind wandering had just occurred.

memory

An indicator of recall of information provided during the lecture. It is the proportion of correct answers in a six question assessment given at the end of the lecture presentation.

interest

A Likert scale that gauged student interest level concerning the lecture.

motivation_both

After experiencing both lecture delivery methods, students were asked about which method they were most motivated to remain attentive.

motivation_single

After a single lecture delivery experience, this Likert scale was used to gauge motivation to remain attentive during the lecture.

Source

PLOS One

Examples

library(dplyr)
library(ggplot2)

# Calculate the average memory test proportion by lecture delivery method
# and gender.
lecture_learning |>
  group_by(method, gender) |>
  summarize(average_memory = mean(memory), count = n(), .groups = "drop")

# Compare visually the differences in memory test proportions by delivery
# method and gender.
ggplot(lecture_learning, aes(x = method, y = memory, fill = gender)) +
  geom_boxplot() +
  theme_minimal() +
  labs(
    title = "Difference in memory test proportions",
    x = "Method",
    y = "Memory",
    fill = "Gender"
  )

# Use a paired t-test to determine whether memory test proportion score
# differed by delivery method. Note that paired t-tests are identical
# to one sample t-test on the difference between the Live and Video methods.
learning_diff <- lecture_learning |>
  tidyr::pivot_wider(id_cols = student, names_from = method, values_from = memory) |>
  mutate(time_diff = Live - Video)
t.test(time_diff ~ 1, data = learning_diff)

# Calculating the proportion of students who were most motivated to remain
# attentive in each delivery method.
lecture_learning |>
  count(motivation_both) |>
  mutate(proportion = n / sum(n))

OpenIntroStat/openintro documentation built on June 4, 2024, 4:19 a.m.