Ice’s Task 3: Voice to Text Task

https://blogs.ubc.ca/iceetec540/2025/09/21/task-3-voice-to-text-task/

When I read Ice’s Task 3 story, I noticed right away that it sounded like real talking. The sentences were long. Ideas came quickly. There were fillers, fast changes, and strong emotions. This matches what Walter Ong says about spoken language. He explains that oral speech is “additive, redundant, and close to real life” (Ong, 2002). Ice’s story feels alive. I could imagine the crowded bus and the embarrassing moments. The voice-to-text tool kept the mistakes and the fast flow. Because of this, the story stays close to natural speech. This also fits with Haas’s idea that writing tools shape how our thoughts appear on the page. She calls this the “materiality of literacy” (Haas, 1996). My story is a little more careful, but the focus here is Ice’s text. His webpage design also supports this “spoken” feeling. It shows how technology and course tasks help us learn about orality and writing.

References:

Haas, C. (12013). Writing Technology: Studies on the Materiality of Literacy. Routledge.

Ong, W. J. (2002). Orality and Literacy: The Technologizing of the Word. Routledge.

 

James Lin’s Task 4: Manual Scripts and Potato Printing

https://blogs.ubc.ca/jlinmet/2025/09/29/4-4-task-4-manual-scripts-and-potato-printing-optional-task/

In his Task 4, I noticed that his handwriting experience was shaped by speed and technology. He usually types very fast and finds handwriting slow and uncomfortable. He also explains his ideas through McLuhan’s message that “the medium is the message,” meaning the tool changes how we think and write. Looking at theory, his reflections match ideas from the “Mechanization” reading, which explains how writing tools change the pace and rhythm of writing (Bolter, 2001). My story is a little different. For me, handwriting feels rare and emotional after immigration. For him, it feels slow compared to typing. But both pages show that writing tools shape our thinking. He uses WordPress in a clean, structured way. My page feels more personal. Both of us respond to the course goal: learning how writing changes when the medium changes.

References

Bolter, J. D. (2001). Writing Space: Computers, Hypertext, and the Remediation of Print. Lawrence Erlbaum Associates.

 

 

Sara Johnson’s Task 6: An Emoji Story

https://blogs.ubc.ca/sjohnstonetec540/2025/10/16/task-6-an-emoji-story/

In Sara’s emoji story, the first thing I noticed was how quickly her ideas appeared. Her story feels simple and playful. It looks like a small comic made of pictures. Even though it feels light, it shows that pictures can carry strong meaning. Emojis give feelings fast. They do not need long sentences to explain themselves. This connects to what Bolter says about the growing power of visual communication in the digital age (Bolter, 2001). Sara uses emojis to show actions, emotions, and reactions. Each emoji works like a tiny picture. This makes her story quick to read and easy to imagine. It also matches the way many people communicate today. We often use symbols instead of writing long messages. Pictures, colors, and shapes help us understand ideas right away. Her story also reminded me of early picture-based writing, like ancient symbols and pictographs. Emojis work the same way, but their meaning changes depending on the reader. This makes the story interactive. The reader helps build the meaning. Kress explains that modern literacy is multimodal, using many forms, like as images, words, and sound to make meaning (Kress, 2005). In this task, I focused more on the history of writing. Sara’s story focused more on feeling and emotion. Both approaches are valuable. Her work helped me see how strong images are in digital storytelling. It showed me that meaning today is not only written. Meaning is also designed with symbols, pictures, and imagination.

References

Bolter, J. D. (2001). Writing Space: Computers, Hypertext, and the Remediation of Print. Lawrence Erlbaum Associates.
Kress, G. (2003). Literacy in the New Media Age. (Chapter 7: Multimodality and design of meaning). Routledge

 

Laila’s Task 7: Mode-Bending

https://blogs.ubc.ca/etec540laila/2025/10/19/mode-bending-a-desktop-exploration/

When I explored Laila’s Mode-Bending project, the first thing that caught my attention was how she used her desktop as a “text.” Her computer screen was not just a tool. It became a full multimodal space filled with colors, icons, and emotional traces of her daily life. Each part of her desktop like as folders, pictures, tabs worked like a small sign that carried meaning about how she thinks, works, and organizes her world. This follows the view in digital-literacy research that new technologies change the “shape of our interests” and the “character of our symbols” (Postman, 1993). Laila’s project also fits with multiliteracies theory, which says literacy today includes visual, spatial, and digital modes, not only writing (New London Group, 1996). She designs meaning by arranging digital objects, much like students using multimodal “available resources” to express identity. When I compare this to my own audio story, the difference becomes clear. My work uses voice, tone, pause, and rhythm to create meaning. She uses layout, color, and digital arrangement. Both projects show what digital-literacy scholars describe as the shift toward multimodal meaning-making, where reading and writing happen across many modes (Dobson & Willinsky, 2009). Laila helped me to see that storytelling today is not only about words. It is also about design. She reminded me that my audio story shapes meaning through sound, while her desktop shapes meaning through space. Together, both works show how MET encourages us to explore literacy as something dynamic, creative, and multimodal.

References

Dobson, T. & Willinsky, J. (2009). Digital Literacy. Cambridge Handbook of Literacy
The New London Group (1996). A Pedagogy of Multiliteracies; Designing social futures. Harvard Educational Review66(1), 60-92.
Postman, N. (2011). Technopoly: The Surrender of Culture to Technology. Knopf Doubleday Publishing.

 

Kyle’s Task 10: Attention Economy

https://blogs.ubc.ca/contrabot/2025/11/10/bad-ui-an-example-of-what-not-to-do/

In Kyle’s project on “Bad UI”, the first thing I noticed was how clearly, he showed the tricks built into many digital designs. His examples make it easy to see how some interfaces confuse users on purpose. This reminded me the “dark patterns” idea, where designers hide information or push users into choices they did not want to make (Brignull, 2011). Kyle’s work helped me understand how these designs quietly shape our decisions. He shows how a simple button change or a hidden checkbox can make people click without thinking. This connects strongly with Zeynep Tufekci’s warning that today’s technologies can influence people in “hidden, subtle, and unexpected ways” (Tufekci, 2017). Compared to my experience with the attention-economy game, Kyle’s project looks outside the “game world” and focuses on real websites. My work was about how a single interface manipulated me step-by-step. Kyle instead shows how these manipulations exist everywhere: shopping sites, signup pages, and everyday apps. Both projects point to the same problem: modern design often uses our attention as a resource. Kyle’s analysis also connects to Roger McNamee’s point that big tech systems grow by capturing and manipulating user attention, sometimes without users noticing (McNamee, 2019).

Kyle helped me see that dark patterns are not accidents; they are part of a larger system where design, data, and profit work together. His project made me reflect more deeply on how my own web experiences are shaped by choices I never fully see.

References

Brignull, H. (2011). Dark Patterns: Deception vs. Honesty in UI Design. A List Apart, 338.
McNamee, R. (2019). I Mentored Mark Zuckerberg. But I Can’t Stay Silent About What’s Happening. Time Magazine.
Tufekci, Z. (2017). We’re Building a Dystopia Just to Make People Click on Ads. [Video]. TED.

 

Michael Cafuta’s Task 11: Text-to-Image Using Sora

https://blogs.ubc.ca/mcafuta/task-11-text-to-image-using-sora/

When I studied his project, I saw more than just creative images. I saw how AI systems shape our memories and our sense of truth. Michael expected the AI to recreate a real snorkeling moment from his childhood, but the tool added bright life jackets, dramatic scenery, and details that never happened. This showed me something important: AI does not remember, It predicts. It builds new images from patterns learned in huge datasets, not from the storyteller’s actual experiences. Shannon Vallor describes this effect as the “AI mirror” a system that reflects our world back to us, but always with distortions based on the data it has absorbed (Vallor, 2025). The more I read, the more I realized that these distortions can be powerful. Cathy O’Neil explains that many algorithms are treated as objective, even when they contain hidden assumptions or errors (O’Neil, 2016). Her idea helped me understand why Michael felt uneasy seeing his memory reshaped by the system. The AI was confident, but not accurate. In my task, where I explored AI in justice and risk scoring, I now see the same pattern: AI responds with patterns, not understanding. Michael’s images reminded me that, in any field such as art, justice, or storytelling, AI’s output is a statistical guess, not a human truth. His work encouraged me to think more carefully about how we trust AI and how easily its confident guesses can influence our feelings, memories, and decisions.

References

Santa Clara University.  (2025). Lessons from the AI Mirror Shannon Vallor. [Video]. YouTube.

O’Neil, C. (2016). Weapons of Math Destruction: How big data increases inequality and threatens democracy. Crown.