quartz/content/notes/running-in-person-experiments.md
Jet Hughes 8a667e5693 update
2022-05-27 14:12:53 +12:00

118 lines
2.6 KiB
Markdown

---
title: "running-in-person-experiments"
aliases:
tags:
- info203
- scott-video
- lecture
sr-due: 2022-06-01
sr-interval: 7
sr-ease: 250
---
in person
- planning
- execution
- analyzing
higher "bandwitdh" of engagement
# Make clear goals
- scope
- purpose
- what you hope to learn
- hypothesis
- make a prediction
- schedule and location
- use an approprate and relevant location
- participants
- scenarios
# Plan out steps
- questions
- data to be collected
- set up
- roles
- e.g., facilitator, recorder
# Create concrete tasks
write them down
e.g., ![example 1](https://i.imgur.com/FLApe7z.png) ![example 2](https://i.imgur.com/vsEOKjt.png)
# Ethical considerations
participants can feel pressured
get informed consent
remind them that your testing the site.. not them
paticipants feel good about finding issues, not bad about not being able to do something
# Experiement details
- order
- e.g., start simple, shuffle order
- training
- depends on how th real system will be used
- DNF
- set a time limit
- maybe provide help if needed
- pilot
- iron out the kinks in the study design
- can also find very obvious issues that should be addressed so the actual participants aren't "wasted"
# capturing results
- note down critical incidents
- aha moments, stores to share, big problems
- record video
- lets to grab moments easily and share them
- screen recording
- depends if you are interested on their expressions or th interface
- interupptions
- yes/no
- provide help in necessary
- think aloud
- need to know what users are thinking not just what they are doing
- ask users to talk while performing tasks
- what they are;
- thinking
- trying to do
- any questions as they work
- reading
- record or take notes
- prompt them to keep talking
- decide ahead of time about which things to help with
- keep track of things you helped with
- will thinking alout give the right answers
- not always
- avoid specific questions
- if you ask a question, people with always give an answer even it it has nothing to do with the facts
- talking while doing the tasks may change how you do the task
# Greeting participants
welcome, explain setup, scenarios,
# collecting data
- process data
- observations (qualittative)
- bottom line data
- numbers
- i.e., dependent variables
# measuring bottom line usability
useful:
- time requirements
- success/fail
- define in advance what this is
- compare speed or # of errors
dont combine with think aloud
# debrief
tell them what you goals are.
learn more holistically what they are thinking