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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

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Experiments in hci
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 hci1
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


Experiments in hci2
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.


Experiments in hci3
Experiments in HCI

  • People as objects of study:

  • People are different

    • Skills, knowledge, expertise

    • Tiredness, illness, motivation

    • They think and learn

    • => highvariability in experimental results

    • => hard to obtain significantresults


Experiments in hci4
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


Experiments in hci5
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?


Experiments in hci6
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?


”Statistics is the least of your problems!”

Alan Dix, ”Avoiding Damned Lies”


Statistics
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


Statistics1
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.


Statistics2
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


Statistics3
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

  • Somequalitativemethodsalso, but mostly this is in the course Target Group Analysis



The rest of the lecture
The rest of the lecture

  • Practical information about the course

  • Course objectives

  • Course textbooks

  • Course plan

  • Exercise:

    • Table-top hockey experiment


About your course convener
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.


Practical information
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


Things to know
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


Aims of the course
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


Course textbook:

Will also be used:

Sage, 2006

Field and Hole (2003). Sage publications.

Field (2005). Sage publications


Don t loose your textbook
Don´t loose your textbook

  • You will be using it throughout the course


Other good statistics textbooks:

Pearson / Prentice Hall 2005

Pearson / Prentice Hall 2004


Exam and assessment
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 …


Getting assistance
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




Reading
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 ...)


Plagiarism and collusion
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




Tabletop hockey experiment1
Tabletop hockey experiment

  • Aims:

    • To show you how experiments work in practice

    • The de-mystify the process


Outline
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


Outline1
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:


Outline2
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


Outline3
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



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