# CSE 340 Lab 8 (Winter 2021) ## Week 8: Menus Data Analysis .title-slide-logo[ ![:img Data Analysis, 40%, width](menus_data.png) ] --- # Menus Timeline - Programming part (Part 1-4) due: Today, Thursday, February 25 @ 10:00pm - Lock: Saturday, February 27th @ 10:00pm (if you are using late days) - Analysis part (Part 5-6: Report and Reflection) due: Thursday, March 4 @ 10:00pm - Lock: Saturday, March 6 @ 10:00pm (if you are using late days) --- # Section 8 Objectives - Data analysis - In-class demo - Remote testing - Practice gaining participant consent - Cleaning/Predicting data - Menus help & questions --- # Data Analysis In-class demo - Getting Menus data from an Android device or Emulator ([instructions here](https://courses.cs.washington.edu/courses/cse340/21wi/docs/android_files/)) - Working with data: [sample spreadsheet](https://docs.google.com/spreadsheets/d/1JqfKhHugIF-kebs_bVztCnkUe0CizXN8PU_Ar3kXtK4/edit#gid=1104722579) --- # Remote Testing 1. Still looking for participants? Find your group members [here](https://docs.google.com/document/d/1VJ9po9X5Id8XoQFTDrfYmmum7eKclpU-lSjLcVzLd80/edit?usp=sharing) - You can ask us/the course staff too 😊 2. Create an APK: - In your menu project in Android Studio, select the *Build -> Build Bundle(s)/APK(s) -> Build APK(s)*. - When the *Build APK(s)* message popup appears in the lower right hand corner, click the *locate* link to find the `app-debug.apk`. 3. Send a copy of the consent form (Word/Google Doc) to the participant - [Consent form template](../../assignments/consent.html) 4. Set up your phone call or video meeting - Briefly explain the study - Have the participant "sign" [this Google form](https://forms.gle/u8MnQEsK7LcvaMqB6) as written consent --- # Remote Testing (cont.) 5\. Send your APK - Have the participant test your menus: - **Highly recommend** to create a shared Google folder/drive with your participant where: - you upload your APK - your participant can later upload their .csv data file **Notes**: - Participants please make sure to `Clear Result CSV` prior testing and complete a full session - Developer please make sure you have 108 data points from each participant [Report template](../../assignments/menu-report.html) Read more: [Menus Spec](https://courses.cs.washington.edu/courses/cse340/21wi/assignments/menus.html) --- # Dirty Data - Why might you want to clean you data before you begin analyzing it? --- # Dirty Data - Why might you want to clean you data before you begin analyzing it? - Disruption during the experiment (ex: phone call or notification) - Need to categorize people based on input (ex: using mouse on emulator vs using finger on phone) - Same idea but deeper: categorize people based on impairment or ability (ex: person using an assistive device to input their commands) if they're comfortable with you gathering that information --- # Data Predictions - If you were to improve upon the speed of users choosing items in menus in general, what methods would you consider? Prediction methods? - Hypothethical situation answer: Predict which item the user will click on - What data should we collect? - What to do when you predict? How would changing things (like order of items) affect speed? --- # Data Predictions - If you were to improve upon the speed of users choosing items in menus in general, what methods would you consider? Prediction methods? - Hypothethical situation answer: Predict which item the user will click on - Data? - What path they are taking. Could also look at historical behavior, etc if you have it. - What to do when you predict? How would changing things (like order of items) affect speed? Better or worse? - Worse if you move things because the user doesn’t know what to expect, Fitts law only applies to expert behavior. Also recovery time is huge when you make a mistake. - Other ideas besides putting guessed items at the top/easiest to select from? --- # Fitt's Law Question 1 .left-column-half[ - Microsoft toolbars provide the user with the option of displaying a label below each tool. Give a reason why labeled tools may be accessed faster ] .right-column-half[ ![:img Microsoft toolbar with and without labels, 60%, width](fitts1.png) ] --- # Fitt's Law Question 1 .left-column-half[ - Microsoft toolbars provide the user with the option of displaying a label below each tool. Give a reason why labeled tools may be accessed faster - The label becomes part of the target, therefore making the target bigger. ] .right-column-half[ ![:img Microsoft toolbar with and without labels, 60%, width](fitts1.png) ] --- # Fitt's Law Question 2 .doublecolumn[ You have a palette of tools in a graphics application that consists of a matrix of 16x16 pixel icons laid out as a 2x8 array that lies along the left-hand edge of the screen. Without moving the array from the left-hand of the screen or changing the size of the icons, what steps can you take to decrease the time necessary to access the average tool? ] .column[ ![:img Microsoft paint toolbar in 2x8 grid, 20%, width](fitts2.png) ] --- # Fitt's Law Question 2 .doublecolumn[ - You have a palette of tools in a graphics application that consists of a matrix of 16x16 pixel icons laid out as a 2x8 array that lies along the left-hand edge of the screen. Without moving the array from the left-hand of the screen or changing the size of the icons, what steps can you take to decrease the time necessary to access the average tool? - Change the array to 1x16, so all the tools lie along the edge of the screen (makes target size larger) - Ensure that the user can click on the very first row of pixels along the edge of the screen to select a tool. There should be no buffer zone. (screen edge is infinitely deep) ] .column[ ![:img Microsoft paint toolbar in 1x16 grid, 10%, width](fitts2-sol.png) ] --- # Review Consent Your boss wants you to run a user study. Your boss really wants to make sure that a lot of people participate and suggests several options. Mark each as coercive, not coercive, or ambiguous. - Participation in this study is optional, but if you don’t participate it may impact the quality of our project - Participation in this study is optional, but if you don’t participate it may be difficult to draw conclusions about whether bikers want this product - Participation in this study is optional, and you can stop at any time - Participation in this study and we will enroll you in a raffle for a free super-duper go-pro plus --- # Review Consent Your boss wants you to run a user study. Your boss really wants to make sure that a lot of people participate and suggests several options. Mark each as coercive, not coercive, or ambiguous. - Participation in this study is optional, but if you don’t participate it may impact the quality of our project - Coersive - Participation in this study is optional, but if you don’t participate it may be difficult to draw conclusions about whether bikers want this product - Coersive - Participation in this study is optional, and you can stop at any time - Not coersive - Participation in this study and we will enroll you in a raffle for a free super-duper go-pro plus - Ambiguous --- # Questions