https://blogs.ubc.ca/bryceglendenning/2026/02/01/potato-stamping/
Potato Stamping
I connected to Bryce’s post on potato stamping as we had similar results and findings. He mentions how he quickly realized how certain letters were easier to create than others. Something we didn’t realize until we started to carve. Secondly, the fact that letters needed to be carved backwards. This seems logical when you think about it, but it is easily forgotten when you are carving because you tend to think about the letter as it faces you. Interesting how Bryce decided to fix the issue with backwards letters. Modern tech to flip the image, very MET of him… Finally, I like Bryce’s recognition of the writing process, how it has been a very long evolutionary process. Change came slowly, unlike the changes in literacy and writing these days. A great post and discussion, it really resonated with me.
https://blogs.ubc.ca/sophia540/2026/01/31/4-4-manual-scripts/
I strongly connected to Sophia’s post on Manual Scripts. She explains how difficult it has become to get students to write, both physically and digitally. I too have been having these same issues with my grade 6 students. It seems like I am asking them to do something they have not done before. It is a colossal struggle. I too am conflicted as a “tech forward” (Sophia, 2026) teacher, do I continue to ask students to write physically, or do I focus on what I think they will use most in their futures? I am constantly asking myself this question. I don’t know if I have the answer. I use tech a lot, as I am very comfortable with it, obviously. But am I doing my students a disservice? Am I contributing to this general idea that students are losing the ability to write? Sophia’s post really got me thinking about this conflict again. I am pleased to see that I am not the only one struggling with this.
https://blogs.ubc.ca/etec540jennbose/2026/03/31/task-11-text-to-image/
I loved looking at Jennifer’s text-to-image task. I personally really enjoy AI image creation, it can be enjoyable to critique. A kind of Where’s Waldo for inconsistencies and stereotypes. Jennifer’s prompt was a great place to start with words like “ideal” and “Indigenous principles.” I was excited to see how “outdoor learning” and “modern technology” would come out. I find AI has trouble when you mix things that are not “naturally” together. I agree with Jennifer that the first generation was pretty accurate. It took care of the environment, it made the students multicultural (which is good), and it added tech that was appropriate. It definitely focused the “Indigenous” on Native American or plains Indigenous peoples with the dress of the elder and the tee-pee in the background. Similar to my experience with this task, my images were filled with stereotypes. I believe this will be a part of this technology for more time still, as the bias and beliefs of the architects of the internet are still present in the data that AI uses. So, until the data and the models for collecting it change with us, we will be faced with stereotypical image creation results. There is hope though as Jennifer (2026) says, “Although there was some cultural appropriation where a teepee tent was seen in the background, the images appeared to be way more inclusive than they used to be earlier.” Through the past 2 years, I have been attempting to create images with AI. There has been some improvement in the inclusivity and accuracy of the images that are being produced. Hopefully this will continue to improve as time progresses.
https://blogs.ubc.ca/etec540edouglass/2026/04/04/task-12-speculative-fututes/
Emily’s reflection on AI and how it has infiltrated the high school classroom really struck me. When she said, “There is no longer a thirst for knowledge and understanding, but a desire to jump through the hoop and get a task done as fast as possible” (Douglass 2026). This concerns me so much as an educator. I see it too with my grade 6 and 7’s. Every year I feel like students are less and less interested in learning. I think they feel like there is no point. Is this a result of AI? Or is it a reflection of a new generation of kids that have been fed short doses of info that they are mostly in control of. They choose the content, and the helpful algorithm keeps feeding them more of it. Quick, dopamine hits is what they are looking for. I see it in class, I cannot hold their attention for very long these days. So what is the answer? How do we shift and adjust to this “new” student who just wants to get things done as quickly as possible. It perplexes me, and I don’t think I have the answer. I do think that we need to put a lot of time into teaching the ethics and responsibility of AI. Students are using it, and don’t really know when it’s appropriate or not. Teachers are still resistant to AI use in schools, and for good reason. But it is not going away, the “head in the sand” mentality will not work. I hope the shift will happen sooner than later, teachers need to understand how this new technology can support learning. Hopefully the knowledge I have gained through my experience in the MET program will be helpful in supporting teachers and students in the ethical and responsible use of AI.
I really enjoyed reading Terry’s reflection on using the Golden Record Data. I think he made clear the fact that the Palladio visualization leaves a lot out. In my own reflection on this data, I tried to explain how the data leaves out so much, but I don’t think I made it as clear as Terry did. I like how he explained that, “Two people might choose the same song for completely different reasons.” This is so true, it is impossible to see why people made thier choices, and I think this is important information. I agree that this exercise reminds us how important it is to be wary of the conclusions that are made about data. There is so much that is not addressed or seen when we look at the visualizations.
https://blogs.ubc.ca/jcetec540/2026/03/30/task-11-text-to-image/
I loved looking at Jennifer’s text to image reflection. I am so intrigued by this process, how text propmts are processed and what comes out is always a mystery. Jennifer put forward a very specific detailed prompt and once again the result was full of stereotypes. Her second prompt was equally specific and detailed, and the result was pretty accurate. I have found that AI has trouble with the mix of old and new tech, but the result of this generation was great. I love her satement on how AI “re-skins” the world, I thought this was a great way to describe AI image generation. A great reflection, it really got me thinking deeper about how AI works.