Player-Computer Interaction 

USER STUDIES

UNIT 5:

Prof. Dr. Eike Langbehn

Department of Media Technology

Faculty of Design, Media and Information

Hamburg University of Applied Sciences

SECTION NAME

EXAMPLES

UNIT 2:

AGENDA

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

1. INTRO

2. REQUIREMENT
ANALYSIS

3. GAME
DESIGN

0. ORGANIZATION

4. GETTING STARTED
WITH GODOT

5. USER
STUDIES

6. ANALYSIS OF
HUMAN FACTORS

7. INTERACTION
DESIGN

8. ADVANCED PROGRAMMING
WITH GODOT

9. EVALUATION
MODELS

10. MARKET
ANALYSIS

11. NARRATIVE
DESIGN

12. GAME ENGINE
ARCHITECTURE

LEARNING outcomes

  • Knowledge about different methods of evaluation
  • Understanding how to design and analyze user studies

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

Usability

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

Usability refers to the effectiveness, efficiency and satisfaction with which specified users achieve specified goals in particular environments.  
  • Learnability: How fast can users learn working with a certain interface and how easy is it for them to do more or less complex tasks when working with the interface for the very first time?
  • Efficiency: How fast are users in accomplishing different tasks once they have internalized the functionality of the interface design?
  • Errors: Do users make many errors when working with the interface? Are those severe errors and can they easily cope with them?
  • Satisfaction: How satisfied are users after working with the interface concerning the time they had to invest? Was the interface pleasant to use?   

Hewett et al.: ACM SIGCHI Curricula for Human-Computer Interaction, 2009

usability evaluation

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

definition

"Evaluation is the analysis, assessment, and testing of...

  • entire UI
  • input/output device
  • interaction technique" 

methods

  • Analytical vs Empirical Methods
  • Cognitive Walkthrough
  • Heuristic Evaluation
  • Formative Evaluation
  • Summative Evaluation
  • Questionnaires
  • Interviews and Demos  

usability metrics

  • System Performance
    • frame rate
    • latency
    • network delay
  • Task performance
    • speed
    • accuracy
    • errors
  • Subjective Response
    • ease of use/learning
    • satisfaction
    • comfort

categories

  • Expert tests
  • User tests
  • Quantitative tests
  • Qualitative tests

J.J. LaViola et al.: 3D User Interfaces: Theory and Practice (Usability and HCI), 2017

decide framework

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

  • Determine Goals
    • Who wants the evaluation?
    • Why should the evaluation be conducted?
    • What should be investigated? 
  • Explore the Question
    • What is the question that the evaluation should answer
    • Big questions need to be separated in several smaller ones
  • Choose Evaluation Method
    • Which method should be chosen?
    • Depends on goals and question
    • Often combination of several methods
  • Identify Practical Issues
    • Which aspects influence the evaluation?
    • Equipment, time, budget, expertise
    • Pilot studies essential for correct procedure
  • Decide on Ethical Issues
    • Certification of ethics committee necessary?
  • Evaluate
    • Analyzing and interpretation of collected data

Y. Rogers et al.: Interaction Design, 2012

classification

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

  • Field Study:
    scientific observation under natural conditions
  • Laboratory study:
    scientific method to test hypotheses via experiments

 

When among a set of observations, any single observation is a word, or a sentence, or a description, or a code that represents a category then the data is qualitative.

When among a set of observations, any single observation is a number that represents an amount or a count, then the data are qualitative,

Witte & Witte: Statistics, 2009

J.J. LaViola et al.: 3D User Interfaces: Theory and Practice (Usability and HCI), 2017

evaluation approach

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

Joseph L. Gabbard, Deborah Hix, and J. Edward Swan, 1999, User-Centered Design and Evaluation of Virtual Environments, IEEE Comput. Graph. Appl. 19, 6(November 1999), 51-59

evaluation guidelines

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

General Guidelines

  • Begin with informal evaluation
  • Choose an evaluation approach that meets your requirements
  • Use a wide range of metrics 

J.J. LaViola et al.: 3D User Interfaces: Theory and Practice (Usability and HCI), 2017

guidelines for formal experimentation 

  • Design experiments with general applicability
  • Use pilot studies to determine which variables should be tested in the main experiment
  • Use automated data collection for system performance and task performance metrics
  • Look for interactions between variables - rarely will a single technique be the best in all situations  

quantitative analysis

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

  • Descriptive Statistics
    • Minimum, Maximum
    • Mean (Sum divided by #responses)
    • Standard deviation
    • Median (mean value in ordered list)
    • Modus (value that occurs most often)
  • Example: 0, 1, 1, 1, 3, 4, 4, 6, 10, 10
  • Types:
    • Explorative study to find hypotheses
    • Hypothesis-based study to numerically verify/falsify hypothesis
  • There are at least 2 hypotheses in each test:
    • (Alternative) Hypothesis: An expected effect of the conditions on the measured values
    • Null Hypothesis: Conditions do not have the effect on the measured values
  • Goal: Prove hypothesis, reject null hypothesis
  • Example:
    • Hypothesis: The means of the measured values differ between the conditions
    • Null hypothesis: The means are equal
    • Statistical test: comparison of means

Statistical Test

  1. Choose the correct statistical test
  2. Perform test
  3. Interpret & present results

https://pxhere.com/en/photo/544817

Question 1 Question 2 Question 3
Participant 1 ... ... ...
Participant 2 ... ... ...
Participant 3 ... ... ...
Participant 4 ... ... ...
Participant 5 ... ... ...

variables

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

  • Independent variable
    • what is being compared (conditions A,B,C ...)
  • Dependent variables
    • what is being measured
  • Scale level describes applicable statistical tests
  • 4 scale levels
    • Nominal
      • no natural order
      • Examples: Gender, Profession, dichotomous answers of type "yes/no"
    • Ordinal
      • with natural order
      • Examples: usage ("every day", "once a week", "once a month", ...)
    • Interval
      • with natural order, equal distances between values, no absolute zero
      • Examples: Temperature in degrees celsius
    • Ratio
      • with natural order, equal distances between values, no absolute zero
      • Examples: Income (in Euro), Age (in years), weight, size, length

choose correct statistical test

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

Participants in experiment either do all conditions (within-subjects design) or only a part of the conditions (between-subjects design) or a bit of both (mixed design) 

Scale level of variable

Normal distribution

Statistical test

Choose correct statistical test

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

Type of dependent variable

Interval/Ratio

(normality assumed)

Interval/Ratio

(normality assumed)

Dichotome (Bi-
Nomial)

Within-/ between subjects design

Comparison of means between 2 groups

Comparison of means between 3 or more groups

Find correlation between variables

Predict value based on independent variable

Predict value based on multiple independent variables or binomial variables

between

within

Unpaired t test

Paired t test

Mann-Whitney test

Wilcoxon test

Fisher's test

McNemar's test

between

within

ANOVA

Kruskal-Wallis test

Chi-square test

Repeated-measures ANOVA

Friedman test

Cochran's Q test

within/

between

Pearson correlation

Spearman correlation

Cramer's V

Linear/Non-linear
regression

Non-parametric
regression

Logistic regression

Multiple linear/non-linear regression

Multiple logistic
regression

Example: experiment

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

  • Do people interact in 3D faster/slower than in 2D?
    • Independent variable: UI (3D interaction or 2D interaction)
    • Dependent variable: Time to complete task (in seconds)
    • Hypothesis: Mean time to complete task differs between 2D and 3D interaction
    • Null hypothesis: Mean time between 2D and 3D is equal
  • Within-subjects design: All participants do all conditions

Participant 1

Participant 2

Participant 3

3D

2D

17 sec

12 sec

19 sec

15 sec

13 sec

10 sec

Example: experiment

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

> t.test(my_data_3D,my_data_2D,
  paired=TRUE,...)
 Paired t-test
 data: my_data_3D and my_data_2D
 t = 2.4575, df = 9, p-value = 0.01815

Statistics in R

p<.05 then
significant

  • Reported as..
    "A paired-samples t-test was conducted to compare task completion time between conditions with 3D interaction and 2D interaction. We found a significant difference in the results for 3D interaction (M=16.1,SD=2.1) and 2D interaction (M=12.2,SD=2.2) at the 5% significance level; t(9)=2.4575, p=.018. The results suggest that 2D interaction is faster than 3D interaction."

results

PLAYER-COMPUTER INTERACTION

UNIT 5: USER STUDIES

  • Statistical tests say whether significant differences were shown and hypothesis can be accepted (p<.05)
  • When p>.05 then no differences were shown (does not mean that there are none, just that we didn't show any)
  • Significant differences do not mean "big" or "important"
  • Even small and unimportant differences can be (statistically) significant
  • Effect size (in [0,1] shows how strong the conditions have an effect on the measured values (% of variance that can be explained by differences in conditions)
  • Expected effect size implies how many participants we need
    • 0 (will never get significant)
    • small effect size (many)
    • large effect size (few)

effect size

repetitions

Necessary number of participants depending on repetitions and effect size (p = 0.05)

Player-Computer Interaction 

The contents of this Open Educational Resource are licensed under the Creative-Commons Attribution 4.0 International license (CC BY 4.0)
Attribution: Eike Langbehn, Anh Sang Tran, Peter Wood

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