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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
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 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 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 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 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 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 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

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.

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

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

- Practical information about the course
- Course objectives
- Course textbooks
- Course plan
- Exercise:
- Table-top hockey experiment

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

- 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 ...

- 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:

- 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

Will also be used:

Sage, 2006

Field and Hole (2003). Sage publications.

Field (2005). Sage publications

Don´t loose your textbook

- You will be using it throughout the course

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

- 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

- 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: 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 experiment

- Aims:
- To show you how experiments work in practice
- The de-mystify the process

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

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:

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

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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