Course OverviewIAT 432: Design EvaluationFall 2020Dr. Yasamin Heshmat

yheshmat@sfu.ca

Class Community

Please join the Slack group posted on Canvas for the course

We will use Zoom video calls for classes

Course website:

clab.iat.sfu.ca/432

clab.iat.sfu.ca/432

Teaching Assistant

Hanieh Shakeri (hshakeri@sfu.ca) , office hours Thursdays at 11 am

We have an active classroom!

All Slides are in the website

Listen to file audios on the website and read the slides for that week before

class time

At the beginning of each class, we will have a section that

you can ask your questions about that

week’s content.

During Zoom calls we will also use what

you learned and look at different examples

Why design evaluation?

costs associated with not

evaluating

A system that is

actually usable

competitive advantage

satisfied customers

UX Design FailsWhatsapp deleting a message (leaving no room for errors)

UX Design Fails Netflix auto-play (Not all users want to play a trailer at all time)

Photo source: Elitedaily.com

UX Design Fails Banners on top of the map

Photo source: Elitedaily.com

Factors Important in Evaluation

• why are we evaluating: less tech support, better sales, etc.

• when evaluations should be done: summative, formative

• where they should be done: lab, field

• who should be involved: analytic, participative

• what data to collect: objective, subjective, qualitative, quantitative

• what goals should be evaluated: usability, user experience

When?

• Formative

Gain insights to shape the design direction

Purpose is to create possible solutions or early on ways to go for designs

Recommended: duringprototyping or testing iterationsof a design

• Summative

Measure or validate usability of already existing product.

Recommended: right before or after release or redesign of a system

Who?

• Analytic

Tester is expert

Quick review of known issues

You as an expert on the matter

• Participatory:

Real users

Few assumptions, more questions

Time consuming more enlightning

Qualitative & Quantitative Data

Qualitative

• Descriptive data

• Exploratory studies

• Has more observation

• Results that are hard to measure

Quantitative

• Numerical data

• Measurable data such as time, speed, number of errors, age etc.

What you will learn about in this course?

Controlled Experiments

Affective Evaluation

Usability Evaluation of Collaborative Systems

Field Deployment

Assignments – all assignments are individual

Assignment 1: Ethics

Assignment 2: Controlled Study 15%

Assignment 3: Affective Evaluation 15%

Note: 10% off per day for late assignments.

5%

Evaluation

• you must get at least 50% in each of the above components of the course in order to pass

• You can get up to 2% of bonus marks for participation in research studies

Assignments 35%

Midterm Exam 25%

Final Project 40%

Academic Misconduct

• SFU Code of Academic Integrity

• Plagiarism: using other’s ideas work without giving credit

• Cheating: Using someone else’s answers

• Double dipping: Submitting the same work in 2 courses

Consequences:

• Automatic fail of assignment or exam

• Classroom sharing of ideas is encouraged

Course Resources

Resources in this course:

• Martin, D. Doing Psychology Experiments

• Other papers are posted on the website

First assignment

due next week’s class

Complete the TCPS2 course online and submit the certificate on Canvas