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Introduction. Experiments in HCI. We do experiments in Human-Computer Interaction because we want to know ... Is product A better than product B? What is good and bad about X? Testing design principles and methods Etc. etc. . Experiments in HCI. Experimentation in HCI is all about - PowerPoint PPT Presentation

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Page 1: Introduction

Introduction

Page 2: Introduction

Experiments in HCI

We do experiments in Human-Computer Interaction because we want to know ...

Is product A better than product B?

What is good and bad about X?

Testing design principles and methods

Etc. etc.

Page 3: Introduction

Experiments in HCI Experimentation in HCI is all about

people

As they will use the products we develop

But we also – less often - do experiments without human involvement e.g. testing software capabilities Strictly speaking this is not HCI, but

usually a people-oriented aim

http://upload.wikimedia.org/wikipedia/commons/5/50/Spanish_people_-_mosaic.PNG
Page 4: Introduction

Experiments in HCI

Raw materials for experiments:

People On their own horribly complex and

varied things to test ... And we usually run tests with groups

of people!

Computer interfaces And software, experiences, designs, art,

etc. etc.

Page 5: Introduction

Experiments in HCIPeople as objects of study:

People are different Skills, knowledge, expertise Tiredness, illness, motivation They think and learn

=> high variability in experimental results

=> hard to obtain significant results

http://upload.wikimedia.org/wikipedia/commons/5/50/Spanish_people_-_mosaic.PNG
Page 6: Introduction

Experiments in HCI

People are also subject to complex effects, that are hard to control for (measure the effect of) in experiments

Time of day effects Tiredness, post-lunch dip, etc.

Transfer effects Learning and interference

Page 7: Introduction

Experiments in HCI

Other problem is that of context: Experiments can be done in the field or the laboratory Each their own strengths and

weaknesses

Since we usually involve groups of people, we have problems with accounting for the effect of social dynamics ... and group relationships – how do

they impact on what we want to measure?

Page 8: Introduction

Experiments in HCI Finding subjects for experiments is (also)

challenging

Nearly always, we have specific criteria that we would like participants to fulfill Females, age 30+, driving a powder-blue prius, who

likes liqourice

Often we do not have the money to pay people, so

hard to get the right ones

This leads to the problem of most Psychology and HCI experimental research being done with Psychology and Computer Science undergraduate students But how representative are they of the target

population we are interested in?

Page 9: Introduction

”Statistics is the least

of your problems!”

Alan Dix, ”Avoiding Damned Lies”

Page 10: Introduction

Statistics

Statistics is a tool for analyzing data from experiments and deriving meaning from them

Statistics is a logical process – each type of problem has one or more statistical methods that can be employed

If you can identify the problem, you can find the statistical test to use

Finding help/guides for statistical tests is pretty easy

Page 11: Introduction

Statistics

Statistics is primarily used when we are looking for ”broad and shallow” results Using surveys, data logging, large

experiments When using quantitative methods (i.e.

Getting numbers as data) If we want meaning – in-debt

knowledge about just a few subjects, we use qualitative methods (numbers as data) Video logs, not post-task walkthroughs,

anecdotal evidence, etc.

Page 12: Introduction

Statistics

If we want to conclude...

”95% of users had problem X” - we use statistics

”Problem X happens for this reason ...” - we use

qualitative methods

Ideally both! Backup the quantitative data with

qualitative – give meaning to the numbers!

When I grow up, I

want to be a HMW

Page 13: Introduction

Statistics

Statistics are an incredibly powerful tool for an HCI person (interaction design, usability, whatever ...)

In this course, focus on applying statistical methods to analyze experimental data

Some qualitative methods also, but mostly this is in the course Target Group Analysis

Page 14: Introduction

A powder-blue prius

Page 15: Introduction

The rest of the lecture

Practical information about the course

Course objectives

Course textbooks

Course plan

Exercise: Table-top hockey experiment

Page 16: Introduction

About your course convener Center for Computer Games Research

Mostly teaches at DDK-line

Empirical researcher: Science by experimentation

Mostly focused on experiments with humans (annoying bastards!)

User experience analysis in interactive applications Games, websites, etc.

Page 17: Introduction

Practical information

Lectures Wednesday 10-12 in room: 4A22

Exercises Wednesdays 13-15 in room: 4A58

Exercises starts at 13.00 – ends at 15.00 (you can stay longer if you wish!)

Handouts for exercises on the course website (generally the week before):

http://experimentdesign.wordpress.com

http://experimentdesign.wordpress.com/
http://experimentdesign.wordpress.com/
Page 18: Introduction

Things to know ...

Read the course handbook carefully – it contains important information (it is available on the website)

On the website you will find handouts, exercise guides and other documents used in the course, as well as updates and messages from the course convener:

http://experimentdesign.wordpress.com

http://experimentdesign.wordpress.com/
http://experimentdesign.wordpress.com/
Page 19: Introduction

Aims of the course: Basic grounding in research skills and

research methodology Designing and running experiments Data analysis using statistics, SPSS and Excel Writing up studies using standard presentation

conventions

Designing questionnaires and fielding surveys Ethics in research Laws of interaction design

Page 20: Introduction
Page 21: Introduction
Page 22: Introduction
Page 23: Introduction

Course textbook:

Field and Hole (2003). Sage publications.

Sage, 2006

Will also be used:

Field (2005). Sage publications

Page 24: Introduction

Don´t loose your textbookYou will be using it throughout the

course

Page 25: Introduction

Other good statistics textbooks:

Pearson / Prentice Hall 2005 Pearson / Prentice Hall 2004

Page 26: Introduction

Exam and assessment The course will be assessed 100% via the final

exam Exam is written, with aids, on a PC, but minus

internet access. Exam will focus on testing your understanding of

the principles taught in the course It will focus on problem solving and thinking, not

remembering the curriculum word by word Note that changes may happen …

During the course there will be an assortment of assignments, some to be handed in, some to present, during the semester These do not count towards your grade Without doing them you will learn nothing …

Page 27: Introduction

Getting assistance

This is a method course, which can be intimidating

If you need help, get help – problems are easier to fix early on

Primary help: Ask you co-students and the people in your group

Secondary: Contact the course convener during office hours

Office hours: Thursday 10.30-12.00, Monday 10-30-12. Room 4B06.

DO NOT disturb outside office hours

Page 28: Introduction

Term outlineCourse week Date Lecture Exercise Notes

1 27/8 Introduction to the course Tabletop hockey experiment

2 2/9 NO LECTURE NO EXERCISE Start reading for Week 3

3 9/9How to write a scientific report

WORKSHOP (lectures and exercises intermingled, 10-17)

Analyzing a scientific paper

Writing a lab report

4 16/9 Planning and designing experimentsIntroduction to SPSSProblem solving in

groups

Hand in assignments

5 23/9 Descriptive statistics

Descriptive data analysis in SPSS

Problem solving in groups

TBA

628/9 and 29/9

28/9 lecture, room 4A22 10-12: The normal distribution and

hypothesis testing

29/9 Exercise, room 2A52 13-15: Creating graphs in

ExcelProblem solving in groups

TBA

7 7/10 Parametric statistics Performing ANOVA in SPSS & other fun tasks TBA

Page 29: Introduction

Term outlineCourse week Date Lecture Exercise Notes

8 14/10 FALL BREAK - NO LECTURE NO EXERCISE TBA

9 21/10 Non-parametric statistics Yet even more problem solving in groups TBA

10 28/10 Correlation Some really cute problems to be solved in groups TBA

11 04711 Linear regressionStarting the free

experiment (groups)+ problem solving

Prepare experiment I

12 11/11 Survey-based methods and questionnaire design

Running experiment+ constructing surveys Run experiment

13 18/11Principles of interaction design: Fitt´s law and the Power Law of

Practice

Fitt´s law experiment (groups)

Prep. presentation of experiment

14 02/12 Ethics in researchIntroduction to the exam

Presentations of experiment results TBA

Page 30: Introduction

Reading

Each week there will be some core reading From Field & Hole Or from the compendium

Some weeks there is also optional reading suggested – strongly encouraged that you read this (I will be watching you ...)

Page 31: Introduction

Plagiarism and collusion

Plagiarism: Passing of someone else´s work or ideas as your own. Don´t do it – risk being expelled or

taking the course again

Collusion: Working with someone else and claiming that the jointly-produced work is entirely your own Important point: When NOT working in

groups, your work must be unique to you

Page 32: Introduction

Questions?

Page 33: Introduction

Tabletop hockey experiment

Page 34: Introduction

Tabletop hockey experimentAims:

To show you how experiments work in practice

The de-mystify the process

Page 35: Introduction

Outline

Testing how far an improvised hockey puck travels under different conditions

Two factors (or conditions) are involved: Shot type Puck placement along stick

Each factor has two levels (or values): Shot type: Wrist shot, slap shot Puck placement: Near end of stick,

middle of stick

Page 36: Introduction

Outline

So we have 2 factors with 2 levels: This is called a ”two level factorial design” – a very traditional experiment design in engineering sciences

The aim is to test all possible combinations of factors and levels – here 4:Value A Value B

Factor 1 Short end of stick Long end of stick Factor 2 Slap shot Wrist shot

Page 37: Introduction

Outline

In order to make sure our results are valid, we need to run each combination multiple times

Do 10 shots with each combination. Record distance travelled for each shot

Make sure you set up each shot exactly according to the guidelines – otherwise you introduce experimental error

Page 38: Introduction

Outline

Follow the experimental procedure in the handout

The handout is on the course website:www.experimentdesign.wordpress.com

Follow the guidelines for how to analyze the experimental data + answer the questions given

When everyone are done we will discuss the results jointly in class

http://www.experimentdesign.wordpress.com/
Page 39: Introduction

Questions?


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