No description, website, or topics provided.
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
aws-mturk-clt-1.3.1
img
turk_stuff
.DS_Store
.gitignore
GameSummaries.tex
KenHoffSurvey.pdf
KenHoffThesis.bbl
KenHoffThesis.blg
KenHoffThesis.lof
KenHoffThesis.log
KenHoffThesis.pdf
KenHoffThesis.tex
Makefile
MechanicalTurk.tex
README.md
Rubric.tex
adaptive_difficulty_scores.png
aggregated.png
aggregated_tdist.png
analysis.py
analysis.tex
baseball_comments_on_game.txt
baseball_likert.png
baseball_scores.png
baseball_whatilearned.txt
biblio.bib
botlogic_comments_on_game.txt
botlogic_likert.png
botlogic_scores.png
botlogic_whatilearned.txt
checkpoint_frequency_scores.png
comments_on_survey.txt
contextual_tutorials_scores.png
convert_json_to_turkxml.py
create_latex.py
current_stats.txt
darfur questions
darfur.png
darfur.tex
darfur_comments_on_game.txt
darfur_likert.png
darfur_post.png
darfur_pre.png
darfur_results.png
darfur_scores.png
darfur_tdist.png
darfur_whatilearned.txt
educational_quiz.tex
edugames.txt
encyclopedia_content_scores.png
encyclopedia_location_scores.png
exploration_freedom_scores.png
full_five_stats.png
fungames.tex
fungames.txt
game_summaries
game_summaries.json
games.py
general_post.png
general_pre.png
general_results.png
generate_surveytex.py
getBalance.sh
inner_3_stats.png
interrater.py
iterative_feedback_scores.png
json_xml_converter.py
lemmings_comments_on_game.txt
lemmings_likert.png
lemmings_scores.png
lemmings_whatilearned.txt
light-bot questions
lightbot.png
lightbot.tex
lightbot_comments_on_game.txt
lightbot_likert.png
lightbot_post.png
lightbot_pre.png
lightbot_results.png
lightbot_scores.png
lightbot_tdist.png
lightbot_whatilearned.txt
machine_comments_on_game.txt
machine_likert.png
machine_scores.png
machine_whatilearned.txt
munchers.png
munchers.tex
munchers_comments_on_game.txt
munchers_likert.png
munchers_post.png
munchers_pre.png
munchers_results.png
munchers_scores.png
munchers_tdist.png
munchers_whatilearned.txt
notpron_comments_on_game.txt
notpron_likert.png
notpron_scores.png
notpron_whatilearned.txt
number munchers questions
oregon trail questions
oregon.png
oregon.tex
oregon_comments_on_game.txt
oregon_likert.png
oregon_post.png
oregon_pre.png
oregon_results.png
oregon_scores.png
oregon_tdist.png
oregon_whatilearned.txt
outer_3_stats.png
pandemic_comments_on_game.txt
pandemic_likert.png
pandemic_scores.png
pandemic_whatilearned.txt
plottest.py
problem_solving_scores.png
quiz ideas
quizresults.png
referential_amount_scores.png
referential_popularity_scores.png
referential_rewards_scores.png
reset_penalty_scores.png
resource_penalty_scores.png
results.tex
rubric.py
rubric_information
rubric_information.json
sample_latex
sendHIT.sh
significance.py
survey.tex
survey2.tex
survey_likert.png
survey_rubric.tex
surveygen_lightbot.py
surveygen_munchers.py
test.png
time_analysis.py
times.txt

README.md

Senior Thesis

This is the entirety of the code written for my Senior Thesis, completed Fall 2013. It's documented here for official purposes, as well as for anyone who's interested in the implementation.

It's a little bit of a mess - that's what happens when you're up against a deadline! If you'd like to find out more, feel free to reach out to me at thekenhoff@gmail.com.

Abstract

Existing educational games lack the combination of education and engagement. The objective of this thesis was to research, synthesize, and test a more effective educational design method. First, an educational game design rubric was synthesized from current literature and existing educational games. Then, players applied this rubric to known educational games. In addition, players completed a quiz on game material that accompanied some of the games, to test if the game had improved their content knowledge or skills.

Amazon's Mechanical Turk was used to find players to complete this survey. It produced a significantly large number of responses at a very small cost. Afterwards, the quizzes were scored and analyzed for statistical significance using a two-tailed t-distribution method. The game design rubric responses were analyzed for consistency using an inter-rater reliability metric.

Only one of the games (The Oregon Trail) had a statistically significant improvement in the quiz scores (~5%), and only a few of the rubric items placed in the ``Slight Agreement'' category as measured by inter-rater reliability. There are no statistically significant conclusions that can be drawn from this research, but it provides an effective first step for future research using similar content or procedures.

Implementation

There's two main purposes of this code. The first is to generate the final LaTeX file, including graphs and up-to-date results. The second part loads, retrieves, and analyzes the data.

Just about everything is written in Python, except for the provided Mechanical Turk shell scripts. PyPlot was used for generating all of the graphs.