Sense-Making Journal : Triggering Curiosity

MDEF: Measuring the world / A world in data activity report.
Purple Team: Seher, Dhriti, Myrto, Samantha, Carolina, Wen, Jimena

Journal Index

• Sense-Making Journal : Triggering Curiosity
  • From objectives to the hypothesis
    • Brainstorming
    • Project Goals
    • Hypothesis
  • From hypothesis to data
    • Tools selection
    • Tool usage documentation
  • Data capture
  • Learning Outcomes
    • Conclusion of the Results
    • Data summary
  • Data insights:
    • QR Codes
    • Surveillance
    • Tips
    • Future explorations
    • Understanding types of Curiosity
    • Data on Curiosity
    • Main takes of the group from the experience

From objectives to the hypothesis

Brainstorming

Brainstorming process:

The group was interested in how spaces can be a catalyst of creativity and well-being and what spaces we feel more whole and rooted. Things like local markets and community activities at the beach came up as examples. That led us trough a roller coaster of abstract concepts like creativity, resistance movements, curiosity, etc.

We settled on seing where people are the most curious or if a space due to its environment can influence someones curiosity and exploration spirit.

Project Goals

Objective: We want spaces to encourage curiosity and consenquently creativity.
Question: How is curiosity triggered?

Hypothesis

Curious responses are influenced by the physical environment.

From hypothesis to data

Tools selection

Post multiple images about the tool. What tool did you use? Would you choose a different tool now?(max 280 char)
We choose the camera.

Tool usage documentation

How can others replicate your data capturing process again?

Data capturing strategy

–
Our plan was to assemble a camera on the IAAC terrace, but the only day we had to gather data turned out a very rainy day. Therefore we had to reconsider the spots where we would place the cameras in a strategic way, so we can later compare the results in relation to the context. Next to the camera we have a QR code. The purpose of this is to see how many people are willing to discover what the camera is doing and why. The camera will film the people that were curious enough to scan the code. To trigger this we used a catchy phrase: "What are you looking at?".

Data Capture: IAAC Main Hall

By scanning the QR code we have a little surprise:

Materials needed

• Raspberry pi camera
• Raspberry pi OS
• laptop and sd card reader
• pen and paper
• 2 smartphones

Detail setup instructions

For using the Raspberry Pi camera:

• downloading the Raspberry Pi OS
  
  Step 1: Install Raspbian on your RPi
  Step 2: Attach camera to RPi
  Step3:Raspberry Pi OS configured with all the settings (ex. Wi-Fi connection, username and password)
  Note: We had to use Victor's computer as ours was not correctly uploading the definitions on to the SD card. Still everytime we tried to connect our definitions were not saved and the permission to acess the camera was continuously denied. So, Victor tried to modify the system so we can use it and we also attemped to use different SD cards.
  Step 4: Commands sudo raspi-config to update to the latest version.
  Step 5: Connecting to GitHub

For using the smartphones as cameras:

• Cardboard stand + phone

Prototype

Final stand (at IACC main hall, Itnig Cafe, IAAC Atelier)
We designed a cardboard stand and printed A4 papers with different messages to spark curiosity in spaces of human transit.

Data capture

Data Capture: Itnig

After an hour at IAAC Main Hall, we were not receiving much interaction. We updated our sign and QR code with "free compliment" because we thought it could be more engaging. We moved our next prototype to Itnig because there would be more movement of people.

The QR code this time led to a compliment generator site called emergency compliments.

2:40 - 3:40 PM - Itnig café
We set up a cardboard right next to the coffee check out area at Itnig for 1 full hour. We recorded a timelapse video of the hour and also tracked the QR scans. It seemed an integrated experience with the coffee service since they were giving out free treats that same day.

Data Capture: Atelier IAAC

4:50 - 5:10 PM - Atelier IAAC
Next we tested a different environment, going to IAAC Atelier to test a private space. This time we had the sign have a riddle that we hoped could prompt curiosity. We placed our sign in the stairwell because it had the most traffic and movement of people. Our riddle asked: "What color is the wind?"

The QR code this time led to a figma page we generated for the answer to the riddle.

7:30 - 8:30 PM - Micampus Residence corridor

The location seemed good as most people have to pass it and they would see it easily because it was placed at eye-level. Although in this duration, only two people scanned the QR code, a lot of people noticed it but walked past. It could have been because of the time and most people were tired at the end of the day and wanted to just go up to their rooms.

9:00 - 11:30 PM - Micampus Residence elevator

There is something weird about having a camera in an elevator so we decided not to place one, but just place the cardboard. Since they are in an enclosed space, they check their phone or just stand in silence in the elevator - to pass that time, we got a lot of scans from this location.

Data collected

How do you combine the tool provided with your creativity to prove your hypothesis? How long did you capture data?
Describe the raw data you collected by posting a sample i.e. a picture, a screen capture, etc.

For our QR codes, we used a generator from qr.io.com- which let us track the number of scans. QR code data sampling example:

Joke QR data: 2 scans, 30 minutes
https://qr.io/public-stats/G6BiFX

Free compliment QR data: 10 scans, 1 hour
https://qr.io/public-stats/2zdiLH

Things to remember:

Explain one or more mistakes you've done during that phase? What would you change if will do it again? (max. 560 char)

• Make sure the URL the QR redirects includes some form of analytics to track how long they read the website.
• Be more intentional about being consistent with time blocks (30 minutes or 1 hour, not both).
• to call the attention of curious and creative people we had to be creative

Learning Outcomes

First Experiment: Itnig

• Orginally we were planning to capture people's faces, however we realize that the angle that our QR code is not eye level so we were not able to capture facial expressions.
• We feel uncomfortable capturing the video data because we did not get their consent, but ironically a lot of our data was taken without our consent. It made us more aware of the camera around us.
• Itnig was giving out mini crosaints, so it is nice that our experiment fits in perfectly.
• We also noticed that the wating area in Itnig works well as while people are waiting for coffee, they tend to take out their phone.
• We noticed that in an lively open environment, where people are comfortable and bored waiting for their coffee, they tend to interact with our prototype.
• Comparing our first spot Iaac main hall, we got 0 interaction despite leaving the prototype there for an hour.
• There is less dynamic going on, people are either working on something or engaged in a discussion, they tend not to pay attention to the surrounding thus less interaction was observed.

Second Experiment: IAAC Atelier staircases

• For the second place, we choose a transition place where people would be passing by.
• We have a good angle so that we don't take the participant's face.
• We didn't have the chance to capture reaction, but it would be interesting if there is a possibility to capture sounds.
• We noticed that we almost affect the data unknowingly forgetting to include the scans that we tried in testing stage.

Images of people scanning the QR code:

Conclusion of the Results

To compare the results effectively, we will be measuring the Rate of Scans (ROS) for our prototype in the two venues.

Rate of Scans (ROS) = Number of Scans (S) / 30 minutes (t)

Data Summary	ROS (S/t)
Itnig Cafe	5 S/t
Iaac Atelier Staircase	2 S/t

The ROS of Itnig (5 S/t) is higher than the ROS in Iaac Atelier Staircase (2 S/t). This validate our inference where people tend to be more curious when they feel bored, for example waitng for a coffee compared to when they are in the process of transitioning in between spaces.

Boredom leads to more curious people: waiting in line and being in the elevator. In these spaces people had more time to be more aware of their surrounds and engage with the QR code and sign.

Data summary

Post at least two images of a chart, a screen-shoot of your data, that you used to prove if your hypothesis is false.

Data Summary
Project Title	Curious Triggers - Itnig Cafe
Capture Start	2:40PM, 09-02-2023
Capture End	09-02-2023
Original Data Format	Film
Submitted format	.MOV file and Analytics tracking
Total Data Points	12 clicks on QR
Number of datasets	1
Data Repository	https://qr.io/public-stats/2zdiLH

Data Summary
Project Title	Curious Triggers - IAAC Atelier staircase
Capture Start	5:00PM, 09-02-2023
Capture End	5:30 PM, 09-02-2023
Original Data Format	Film
Submitted format	.MOV file and Analytics tracking
Total Data Points	5 clicks on QR
Number of datasets	1
Data Repository	https://qr.io/public-stats/G6BiFX

Data Summary
Project Title	Curious Triggers - Micampus Elevator
Capture Start	9:00 PM, 09-02-2023
Capture End	11:30 PM, 09-02-2023
Original Data Format	_
Submitted format	_
Total Data Points	21 clicks on QR
Number of datasets	1
Data Repository	https://qr.io/public-stats/G6BiFX

Data insights:

QR Codes

We started to question QR codes, and how we have a blind trust towards them. Because of the abstract shape of the QR code, the link is hidden and could easily be a scam. We trust QR codes to give us information, but what happens on the other side?

Surveillance

Going through our timelapse capture and being on the otherside of the camera showed how easy it is to invade privacy and how much we are being watched without consent. It felt very creepy invading people's privacy and made us aware of all the cameras around us on a dialy basis.

Tips

Explain one or more mistakes you've done during that phase? What would you change if will do it again? What if you will have more time? (max 560 char)

• Choose areas and times of higher transit. We started during the afternoon but morning has higher rush hours for coffee runs.
• This made us debate the intrusiveness of surveillance cameras. Just watching the videos and using their images without their explicit concerns makes us think of less invasive ways to gather data in this way.
• Next time we could identify and narrow down the scope so that we can have a mroe accurate results and a target users.

Future explorations

Curiosity is a complex subject to explore, so it is best to have a specific way to measure this. To include data scraping methods of data collection, we would look at Twitter data scraping segmenting Barcelona geographically.

Some ideas we wanted to explore:

• Tweets in Poblenou, Barcelona using question marks, the word "Curiosity" o "curiosidad".
• Photo Booth Idea, collect feedback to see if the participants is curious enough to want to get their pictures.
  

Understanding types of Curiosity

We also did some research on curiosity and found some helpful resources. There are 5 distinct factors or dimensions of curiosity:

• Joyous exploration
• Deprivation sensitivity
• Stress tolerance
• Social curiosity
• Thrill seeking

The 4 curiosity profiles
Further, the study found that from these dimensions, four profiles – or types of curious people – emerged:

• The fascinated
• Problem solvers
• Empathisers
• Avoiders

As a group, we think the fascinated is the main user profile that in our targeted places.

Quite often, businesses monetise on our human instinct of being curious. For example, companies that hand out free-(1) scratch cards that you scratch out with a key in the hopes of winnning something for free. Another common example would be our curiosity to know what toy is inside the (2) 'kinder-joy' chocolate egg. (3) A man named Peter Molneux, the man responsible for the Fable game series, created a mysterious social experiment mobile game, 'Curiosity: What's Inside The Cube?' with a lifechanging prize. Thousands of people played this game and spent hours on it to know what was inside the cube. After 6 months, 2000 layers later, the centre of the cube was revealed to the one lucky winner of the game. This is a perfect example of how one can trigger curiosity.

Data on Curiosity

To further our research on curiosity and what kind of spaces can enhance it one could use the Experience Sampling Method. The Experience Sampling Method is a research method that probes participants to report on their thoughts or feelings on multiple occasions over time. This Method has been used to measure boredom trough smart.

2020, Fernandes et al. "Machine Learning approach to boredom detection using smartphone sensors"

Main takes of the group from the experience

We used 4 different locations and boredom as a medium to reach a curious response. We used the proneness of people towards boredom to trigger a sense of curiosity. But we did feel like it was very diffcult to measure such an abstract concept. The more curious people were the more scans we got.

A big take away from this exercise was the surveillance aspect of it all. People were being recorded without consent and scanning QR codes without knowing their content. If we were to do it again, we would have to be more concious of people's privacy and transparency.