PSYCHOLOGICAL CONCEPTUAL FRAMEWORK 
| Visual Analysis of JHiSquares Using
​a Psychological Conceptual Framework
Stephanie Posa

I have chosen to use the method of conceptual visual analysis to examine our JHiSquare corpus. I will specifically be using a conceptual framework known as “ The Information Processing Theory” from the discipline of psychology to formulate an approach to visual analysis.
 
Why take a psychological approach?
A. Cognitive psychology is extremely relevant to information. It accounts for how we attend to, process,communicate information.
B. Look at the corpus! Our participants often visually conceptualize information by using symbols that are often associated with psychology. Ex. Brains, sensory systems.
 
The Information Processing Theory
The Information Processing Theory was initially conceived by psychologists such as Atkinson and Shriffrin (1968), and later modified by figures such as Craik and Lockhart (1972) (as cited in “Information Processing Theory,” 2015). Cognitive psychologists formulated this theory as a means to better understand the seemingly intangibility of mental processes, such as attention, memory, problem solving, and processing information, etc. (Macleod, 2008).  In regards to processing information, the theory outlines the ways in which humans receive and transform sensory stimuli into meaningful information through a series of steps (“Information Processing Theory,” 2015). It poses that rather than passively sensing stimuli in our environment, we actively interact with stimuli as a means to transform various visual, auditory olfactory and tactile cues into information that can be perceived and manipulated. In an attempt to materialize the immaterial nature of this psychological process, the Information Processing Theory uses the analogy that the human mind functions similar to a computer (Macleod, 2008). Like the cognitive processes of the human mind, the technological processes of computers allow them to receive, and modify information.
 
According to the Information Processing Theory, there are a series of steps that the mind may undergo in order to successfully transform stimuli into meaningful information (Macleod, 2008). Analysis of the JHiSquare corpus can be done by organizing various drawings into one of these three stages of Information Processing.

1.  Input Stage: First, an organism must interact with the environment to receive sensory stimuli (Maclead, 2008). At this stage, information is purely sensory and not yet something that organisms can cognitively manipulate or attend to.

2. Storage Stage: the organism actively manipulates the incoming sensory input, through mental processes such as memory, organization, etc. (Macleod, 2008).

3. Output Stage: The last phase of information processing theory. This is when the organism responds to the environment, using the information that they have recently received (Macleod, 2008). Ex. Because an individual receives sensory info about the brightness of the sun, they can communicate this to another individual.

On the Epistomological spectrum, my analytical approach closely follows the interpretivist outlook. This is because the associations I have made between visual images and psychology are socially constructed, and informed by knowledge of psychological concepts, symbols, etc. (ex. we associate brains with cognition). Unlike the positivist outlook, this conceptual analysis approach does not aim to quantifying the content, or formal qualities of the JHiSquares, but instead relies on an understanding of the psychological implications of various graphical representations.
 
This approach is deductive, as one would analyze the JHiSquare corpus using the conceptual framework of Information Processing Theory to guide analysis and interpretation. With conceptual analysis, one automatically approaches the data set with pre-existing ideas of what to look for, and what to attend to. Rather than letting the data jump out at you, this approach requires that the data is viewed with a narrower conceptual lens that allows us to compartmentalize, organize, and analyze the iSquares according to preexisting ideas.
 
Overall, the information processing theory categorizes information as something that
A. Is received from the environment (stimuli carries sensory information)
B. is stored (organized, manipulated)
C. Feedbacks into the environment through our actions, responses, interactions, exchange.
 
It is a dynamic process that is appropriately suited to this psychological/cognitive framework, however it is important to note that not all iSquares fit into this Information Processing Theory. The major outliers include iSquares that are predominantly composed of text.
 
References:
Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. Psychology of learning and motivation, 2, 89-195.

Craik, F. I., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of verbal learning and verbal behavior, 11(6), 671-684.

J L., "Information Processing Theory," in Learning Theories, December 4, 2015, https://www.learning-theories.com/information-processing-theory.html.
​
McLeod, S. A. (2008). Information Processing. Retrieved from www.simplypsychology.org/information-processing.html

FORMAL ANALYSIS | DEDUCTIVE APPROACH
Annie Xu

​When it comes to analysing visual works, I was determined to use formal analysis from the start. Formal analysis originated from the theoretical approach of formalism, supported
by literature within the discipline of art history. Moreover, it is well-articulated in foundation training of designers and artists. This approach also nudges me in the direction of a positivist approach. This method of analysis of the collected data offers a more objective approach to what is an already visually creative and diversified data. It also provides insight into work that may not be easily interpreted through a sociological or cultural lens. The slides show some comparisons of how formal analysis can be used to analyse the JHiSquares and significantly, is a method well-suited for assisting the analysis of the Draw and Write technique. 

INDUCTIVE VISUAL | CONCEPTUAL ANALYSIS
Sydney Bradshaw
​
I tend to be interpretivist and favour inductive approaches to visual analysis.
 
I started off by looking over the iSquare, paying attention to any patterns that jumped out at me. I also noted any instances in which I saw common themes between different squares. Though I didn’t have an initial framework in mind, I found myself piecing together a system of categorization based on the thematic content I found within the images. My methodology proved to be a hybrid of Buckland’s conceptual analysis, thematic analysis and a bit of content analysis to provide structure to my discoveries.
 
Overall, I found that looking at the squares before setting up a stringent system to organize them with allowed me to think outside the box and approach interpretations of the squares that I wouldn’t necessarily have made under a rigid system.
 
Initial qualitative observations that I made:

• 39 iSquares, most with colour but some without
• Words used frequently, both as descriptors and as parts of the diegetic image
• Common motifs: people/body parts, technology, abstract patterns, diagrams

 
Quantitative Analysis:

• Only black and white -> 5 out of 39
• Developed tangible vs intangible and then more subcategories; inspired by conceptual analysis (information-as-thing, etc.)
  • Intangible -> information as a metaphor, a concept, an abstraction, etc.
  • Tangible -> information as an object / multiple objects, a system

 
From there, I could look at each individual square and find the best approximation of what I thought it was trying to say about information, aided by the text on the reverse side. I also thought about the use of colour, making note of the uses of colour in objects especially and how said colour compared to real-life colourings of the same object (eg JHI-018 uses mostly true to life colouring, whereas JHI-001 is far more colourful in its interpretations).
 
Potential Problems:
Of course, there were some outliers that didn’t quite fit into either category, namely, squares that were made entirely of text (eg JHI-014). I also realized that it would be entirely possible for any of my interpretations to be extremely subjective and based on my own experiences and understandings of visual/textual culture.
 
BRIEF TEXTUAL ANALYSIS
http://www.writewords.org.uk/
I also decided to gain some context on the images by looking over the demographic information on the back of the iSquares. As I did this, I noticed several words that appeared multiple times. I ran a ‘Word Frequency Counter’ on the excel document that we used to store said information and outlined below the words that appeared 5 or more times in our group of 39 drawings:

Info- 12
Knowledge - 9
World - 6
Us - 6
You - 5
Web - 5
Think - 5
Perception - 5
Different - 5

Of course, this is not an exhaustive list and there were words that also appeared 2, 3, and 4 times that would be interesting to investigate in the context of the drawing associated with each.

DEEP LEARNING | THE FUTURE DIRECTION
Sicily Shi 

Using Google’s Deep Learning algorithm: Artificial Neural Networks that mimic human brain neurons, this system can constantly learn and improve on it’s own by being exposed to more and more data - this process is called “training” (similar concept as how AlphaGo was developed). 

​In this project, we used an already trained deep learning system, the output image is not simply a mixture of the original drawings; instead, it shows a new perspective, that is “how information itself think what (human think) information is”

As the AI technology advances, we will eventually be able to feed millions of iSquares into the system along with text descriptions, and ask it (or her?) “what is information?”

First Impressions of
​the Beautiful iSquares
 
This week was fun and busy. On Monday we had our “Big Day” which we organized other JHI fellows together and collected their drawings of what is information. We tried to create a welcoming and comfort environment, and prepared for anything that might go wrong. To my surprise, the time seemed to passed so quickly and the entire process was very smooth. Everyone was so concentrated and engaged in their drawings as if they were taking an exam. We feel very appreciated for their effort and support.

This is our first attempt using colour pens and larger squares in the study. Initially we were worried if most people would just stick with one colour anyway because it is the easiest way to work on. However, it turned out that the drawings were so beautiful and multi-coloured, and it seems that the coloured pens and large space inspired their creativity! Compared to the old iSquares, I was impressed about how pretty they are in terms of the visual representation, and how rich they are in terms of the content on each iSquare.  There are only 39 images in total, but all the responses are very diversified. Some depict information as pictorial metaphors such as a web or an eyeball, and some also have similar ideas as mine that drew information as knowledge. Many of them also drew complex and abstract patterns that fill the entire graphic space. As I looked them over and over again and it is hard for me to pick a favourite one.

The introduction of colour in this study brings new inspirations, but at the same time brings more questions. For example, would people associate meanings to a particular colour? Would the textures of different pens communicate different things? These are the questions we have to consider during the data analysis, and I feel quite excited about taking this new challenge as a team, and come up with my own unique way of analyzing them. ​