Tanya Groetchen's Blog

My first speculative narrative was created using Pixton. It looks at education and the ability for it to be personalized for every student. As Dunne and Raby (2013) suggest, future predictions “usually take the form of scenarios, often starting with a what-if question” (p. 3). I began by thinking of what-if scenarios based on my class at school. I have a very diverse class this year, with a wide range of learning needs. I wondered what-if each student had their own teacher who could scaffold the learning and customize the experience for each student. This is where I can up with the idea of each student having their own holographic teacher, with school happening on the student’s schedule and at any location. Education would become personalized and each learner would learn at their own rate, in the environment that was best for them. 

My second speculative narrative was created using Animaker. It looks at the use of technology in a student’s day to day life, but aims to show the negative social implications the technology could pose. While future technological advancements could support day-to-day life and make things easier and more personalized for man-kind, there could also be negative impacts of the technological advancements, such as a lack of social connections. I created this narrative  “to draw attention to a scary possibility in the form of a cautionary tale” (Dunne and Raby, 2013, p. 28). The narrative is a something I speculate could happen and want to forewarn others about the possible implications. 

(Click HERE if the video doesn’t load:

References

 Dunne, A., & Raby, F. (2013). Speculative everything: design, fiction, and social dreaming. MIT press.

The  online game User Inyerface was an interesting experience. It reminded me of an escape room in which you never know if what you are choosing will help or hinder your progress. I played the User Inyerface game two times. The first time I clicked on the terms and conditions. The scroll bar to get through all the terms and conditions moves at a snail pace and there are so many pages to get through, so I quit and restarted the game. I knew I had made a key mistake! On my second try, I spent more time looking and reading things before clicking. There were so many ways in which the GUI is designed to manipulate attention and responses. For example, the game was timed. I am a competitive person so this created a sense of urgency. I wanted to go quickly, but after what happened my first try, I also wanted to read over what I was doing. This lead me to scan the pages, allowing deception by the game as key information was buried in text and was easily overlooked when scanning the page (Brignull, 2011). From being constantly reminded of the time, the use of colors opposite than one would think (ex. green for No, as opposed to red), and clicking on a word instead of what appeared to be a link, to the order of the text boxes that had to be manually deleted, and the ‘I am not a robot’ pages that were open to interpretation, the game was a struggle. Things that I had become familiar with from time spent online, were not the correct choices. The game purposely manipulated me into clicking on specific things.

Tristen Harris (2017) spoke of how the internet is not evolving at random and there is a hidden goal of gaining our attention. This can be accomplished in various ways, but “auto play” was one example that Tristan Harris (2017) used in his Ted talk.  Zeynep Tufekci (2017) spoke of persuasion architecture and how both the physical and online world can be designed to persuade us. As I listened to their TED talks, I was reminded of some of my undergrad courses in human geography. The auto play example in the online world that Harris (2017) discussed can be related to the hallways and aisles in malls and casinos. Malls and casinos are designed to appear never-ending. When one hallway or aisle ends, the next begins. Malls and casinos have a hidden goal of gaining time from the customers because the more time that is spent in the facilities generally means more money being spent. There are also other architectural features that are designed to help accomplish this goal. The exits are not easily visible or they are at the end of long hallways. There are no windows so the customers are removed from the outside world and don’t know if it is getting dark outside, snowing etc. And lastly, there are no clocks so the customers have no idea how much time has gone by while inside the mall or casino. This persuasion architecture has been a part of our physical world for many years and it is no wonder that it has expanded to the online world which now makes up a big part of our daily lives. It is scary to think of how much we are persuaded in both the physical and online world, and even scarier to think of how often we are completely oblivious to it!

References

Brignull, H. (2011). Dark Patterns: Deception vs. Honesty in UI Design. Interaction Design, Usability, 338.

Harris, T. (2017). How a handful of tech companies control billions of minds every day. Retrieved from https://www.ted.com/talks/tristan_harris_the_manipulative_tricks_tech_companies_use_to_capture_your_attention?language=en

Tufekci, Z. (2017). We’re building a dystopia just to make people click on ads. Retrieved from  https://www.ted.com/talks/zeynep_tufekci_we_re_building_a_dystopia_just_to_make_people_click_on_ads?language=en

When I first opened the Palladio program, the music choice data from task #8 was displayed for the entire class. The curators were all represented as light grey dots on the graph and each of those dots was the same size as one curator was not any more important than the other. These dots are all vertices or nodes. The music tracks were represented by dark grey dots, or nodes. The lines connecting the curator nodes and the music track nodes are referred to as edges. The dark grey music track nodes were different sizes, proportional to the number of edges each song had, or the number of connections between the particular music track and curators. The more edges/connections, the bigger the node was represented on the graph. 

I moved the nodes around as I found it overwhelming to view the graph with all the nodes rather randomly placed on the graph. I moved all the curators to the outside of the graph, leaving the music track nodes in the centre. This allowed me to more clearly see which nodes for the music tracks had more edges. Both the size of the node and the number of edges or lines leaving the node allowed me to see this. 

Next I focused on the community I was put into. Community 1 consisted of myself and 4 other classmates. Focusing in on just one community was easier than viewing the graph of the entire class as a whole because it narrowed down the number of nodes and edges. This makes it easier to view all the connections. 

I again re-arranged the nodes in order to see the connections and edges more clearly, as well as to see the size of the music track nodes easier. The bigger music track nodes indicated that more of us from the community had selected that particular music track. 

There were two particular tracks that all 5 of had chosen. In our community, these two tracks have 5 edges. I was curious as to why we all chose these songs. What was it about them? Flowing Streams is a song from China with sounds from a guqin, a seven-string instrument. The other is a percussion piece from Senegal. I chose these songs because I was trying to showcase a variety of instrument sounds. Did the other community members have the same criteria? 

When I looked specifically at the songs that 3, 4 or 5 of the curators in community 1 had in common, the songs were all from different areas of the world, and all featured different instruments. There was also a range of  sounds. It appears as though diversity was a common criteria between the community members. Diversity, however, is quite broad. The criteria could have been geographical diversity, instrumental diversity, or sound diversity. Not being able to confirm the criteria made me wonder if there was ever really a way to know what criteria allowed these 5 curators to have commonality, or if it was always an educated guess.

“The community structure of a network can also be a powerful visual representation of the system: instead of visualizing all the vertices and edges of the network (which is impossible on large systems), one could display its communities and their mutual connections, obtaining a far more compact and understandable description of the graph as a whole” (Lancichinetti et al., 2011, p.1). The data for this task was much easier to view and interpret when just one community was displayed as opposed to the date for the entire class. While the nodes and edges of the 5 curators and song tracks were more apparent and much easier to view, the data did not indicate why these curators were grouped together. I can find commonality between the curators song choices and make assumptions about the criteria that was used, but the data can never tell me the exact criteria or thought process of the curators. The data also doesn’t make it clear as to why the curators didn’t chose specific songs. The nodes are smaller for songs that were not chosen as frequently, however if a song was not chosen at all, it doesn’t appear on the graph. This makes it hard to speculate as to why a song was not chosen, in this case, as it would not even be reflected on the graph.

My interpretations of the data presented could be vastly different than someone else’s. Just as there was cultural and personal bias when choosing our songs, there is also bias the interpretation of the data. I think diversity was the criteria that was used by the curators in community 1, but perhaps there are other criteria that I did not consider. The algorithm put the 5 of us together and while I can speculate why, I don’t know that we can ever really know for sure by just looking at the graph. 

References

Lancichinetti, A., Radicchi, F., Ramasco, J. J., & Fortunato, S. (2011). Finding statistically significant communities in networks. PloS one, 6(4), e18961.

To redesign task #1, I chose to create a spoken word poem. I have had colleagues do spoken word poems with their students, but it is something I have never tried myself or with my own students. I decided I would give it a try and go through the experience as a student would. 

Click HERE to listen to the spoken word poem and see the bag images. 

Click HERE to read the poem lyrics.

Task #1 was about introducing ourselves to the class through our bag and what the items from the bag told others about ourselves. To redesign the task, I started by brainstorming all the roles, traits and experiences that help to define who I am, and then compared them to the items that were in my bag from the first task. Many of the items from my bag were in some way represented by my brainstorming, but many other parts of what defines me was not included in my bag at all. I struggled at first with what to do to redesign this task. My go to response was a video, but I wanted to really focus on the audio component of this task. I decided to take my brainstorming about myself and wrote a poem about who I am. I then recorded the poem in the form of spoken word poetry. I was going to only submit the audio poem, but then decided to include images of the parts of the bag that I felt were represented by the parts of the poem. By creating the poem, it allows the listener to learn much more about me and who I am. The poem allowed me to extend the conversation and go much deeper about who I am as compared to task 1 when I only spoke of the physical items in my bag. The poem has allowed for a narrative that goes with the items and tells others about who I am beyond what they can see.

As the New London Group (1996) suggests, redesigning is “neither a simple reproduction… nor is it simply creative” (p. 76). Redesigning changes the task and the result is something new. The redesigned “is the unique product of human agency: a transformed meaning” (New London Group, 1996, p. 76). The poem in this task is completely transformed from the bag assignment in task #1. While some of the items from my bag in the original task loosely link to part of my poem, the poem is a completely new entity. Writing the poem allowed me to introduce myself in a different way. I was able to rely less on physical, public side of me and share more of my private life and thoughts. By redesigning the task and changing the semiotic mode, the meaning has changed. 

I have been brought up in a culture in which reading and writing are generally thought of as literacy. There are cultures, however, where that is not the case. The idea of multiliteracies “focuses on modes of presentation much broader than language alone” (New London Group, 1996, p. 64). I found it fascinating that the New London Group (1996) spoke of “sci-fi visions of information highways and impending future where we are all virtual shoppers” and that “new communications media are reshaping the way we use language” (p. 64). While information highways and virtual shopping have become the norm, so much can still be said about new communications media reshaping the way we use language. With emojis, tweet, posts, tik tok videos, snaps etc., our language and literacy is being redesigned and multiliteracies are becoming the norm.

References

The New London Group. (1996). A pedagogy of multiliteracies: Designing social futures. Harvard Educational Review 66(1), 60-92.