This week we learned about Zotero for curation and citation, and also about the function and importance of annotation.
Curation
I would say that I am a minimalist when it comes to certain technologies, but I am fast to adopt technology that saves me from doing repetitive tasks. One of the most dreadful things experienced in school is finding and formatting references for a paper by hand in MLA, APA, etc. Traditionally if I needed to create references for a paper I would input them into LaTeX first, and that would at least save me from formatting the lines by hand, but I would still have to manually enter all of the information into latex, which is still time consuming and tedious. A wonderful app that fetches all metadata (Author, doi, title, etc) about an article and also formats it into APA, MLA, etc is Zotero. I have been using this app during this semester for some of my classes I can say it’s an absolute game changer for finding references and saves a lot of time. It also accounts for many workflows and technologies that people use like Microsoft Word, LaTeX (BibTex), and HTML for websites. Needless to say, I have adopted this app into my academic app stack and plan to use it in the future.
Personally, I have never really found annotation that useful and I only annotate on things that are temporary. The reason I typically don’t like annotating is that I find it clutters the pages of books and is just distracting from the content being read. I find annotations in books too permanent, the nature of exploring ideas is that they change over time, and that they are iterated on and refined. I have always found even highlighting and writing in the margins to cage my thinking rather than exploring and discarding ideas along the way, in an iterative process. Instead of annotating I would rather just take notes while reading. The way I have found annotations to be useful is on temporary things that are only relevant for a short period of time, like schedules, course outlines, and rough drafts of papers.
Bonnie Stewart this week brought up some very important points to consider. In this article I will talk about some of the topics she brought up, and also share some other considerations.
Value Exchange
My take is that, data collection as a whole is inhumane, malicious, and parasitic. The logical conclusion of this practice, is a form of slavery, because we relinquish our power to monopolistic companies, and that power is then used against us, in the form of advertisements, surveillance technology, and selling that data to other companies. Its true that these products offer a lot of value at no monetary cost, but the value exchange is not equal. I think more people are becoming aware of this exploitative relationship and are starting to use privacy respecting software more and more, however most people are still not aware of the dangers. There are also people that are aware of the consequences but conscientiously choose digital convenience over sovereignty, and the allure of the former is strong. A few common justifications I have heard and have also used myself are, “Well, I’m not doing anything wrong online therefore I don’t care if my data is collected”, “I’m too invested in the ecosystem of this technology to switch”, “How is my data going to make any difference when there already so much data out there already?”
“Anonymous” data
One of the most dishonest change of phrase is Anonymizing Data, there is no such thing as anonymous data because all data can be de-anonymized. This phrase is used purely to mislead people into thinking that their data is somehow safe because it is anonymized. Even if the data was anonymous its still used in nefarious ways.
The exploitative nature of these companies has created an entire market for privacy respecting alternatives, some monetarily free and some paid. These alternatives in a lot of cases are better than the big tech products. They are faster, less buggy and give a sense of freedom that ones data is not being harvested. I am pleased to see that this class uses open-source alternatives, this is important to show that the alternatives are actually good and viable.
Conclusion
It is now clearer than ever that data collection is exploitative, and the outcomes of this practice are not good. I think it is important for people to be aware of the dangers and make a decision on what software they want to use, and to consider the privacy respecting alternatives. There should be more diversity in the eco-system of technology to avoid and break up monopolies that currently exist. I also think that governments should intervene and abolish the practice of exploitative data collection.
It is important to practice a level of skepticism and critical thinking when consuming information online. Mike Caulfield in this weeks material introduces the SIFT method, which is a framework people can use to classify information as potentially a good or bad source. In this post I will talk about the novice-expert problem, how our perception of content can skew how we think about it, and how information online is much more personalized compared to plain text.
How I understand the novice-expert problem is that, a novice in a subject will likely accept plausible sounding explanations for something even if incorrect (using heuristics, or saying “ehh yeah thats probably true”). While an expert will be quick to identify issues with an argument presented to them. Being aware of some of the inherent limitations that people can face can help illustrate to ourselves that we should exercise critical thinking more than we may think we need to.
A number of other metrics can also skew our perception of online media. Consider the concept of “preselection”, this is manifested in metrics like views, likes, and comments. If a piece of media has high metrics, then this piece of content is “pre selected”. Because other people have given their approval of it, giving it online authority. This phenomenon could lead the viewer to believe that the information is trust worthy.
It has always been important to exercise critical thinking when presented with ideas or information, this has been true before the internet existed and is still true today. One thing that makes the internet different than reading plain text is the personal quality that is present in online material. What I mean is that, content on the internet is not just text, but also video, audio, and image. I argue that it would have been easier to be objective about information when it was represented in plain cold text. These other qualities like video, etc., I think can make it harder to be objective because of the inherent personalization of the information being presented.
In a sea of information, influencers, algorithms and online opinions, it can be hard to separate the signal from the noise. Fortunately, there are tools like the SIFT method that can give us more context about a source and make better decisions about information online.
In this post I would like to delve into my experience with using AI, and how this new technology can be leveraged or misused.
The Good and bad of AI
The use of AI is becoming ubiquitous with students, professionals and everyday people in their work. The problem is that this technology is very easily misused, understanding the strengths and weaknesses of AI can help people leverage this technology to reinforce their work, and learning, without interfering with it.
AI similar to a tutor
As a student it can be easy to become bogged down when stuck on a problem. Traditionally this would be overcome by either asking a professor, or hiring a tutor in order to quickly learn a concept. One issue with this traditional approach is that professors do not have enough time to tutor each student and hiring a tutor can be expensive. An effective use of AI is to use it almost like a tutor, doing so can help get past the feeling of being stuck, which can make learning easier and faster. Even if the AI spits out an incorrect answer, encapsulating the idea into writing can sometimes be enough.
Drilling and example problems – active recall
Another good use of AI is drilling for tests. Using AI to create sample questions, to learn, and memorize concepts and methods to solve problems.
Search engines are basically useless
I have talked to many people who have noticed a pattern with modern web search… that it sucks. I personally agree that modern search engines are at best, kind of useful and at worst useless. What I mean by this, is that it is impossible to find real information by real people on the internet anymore. All of the top web results are “Top 10 blah blah blah of 2025”, reddit posts that never answer the question asked, or obscure technical questions from a decade ago that never reach an answer. Also a lot of the top search results are copied and pasted slop that has no real information it is just fluff. The goal of a website is no longer to document and distribute information that a person may find interesting or have expertise in, the goal now is to maximize time spent on their website in order to increase ad revenue, which equates most of the time to wasting the users time.
GenAI as a search engine
To avoid wasting time trying to search the internet for something specific, GenAI can aggregate information from the internet that is relevant to the users query. This may be a more efficient way to gather information from websites, to only receive relevant information, rather than fluff.
The old fashioned way is the best way to access real information
Probably the best alternative to both searching the web and using AI, is to just read the text book. This is the slower but reliable route, reading the text book is less frustrating and in the long term is likely a better resource than both the internet and AI.
Offloading too much to AI
One danger of using AI is that the user will offload too much thinking to the AI. Firstly doing so robs the user of any learning, and also can alter the way we critically think about a problem, by turning off the critical thinking part of the brain. For example, consider the Einstellung effect, when a person sees the answer to a problem, they become unable to think critically to come up with their own solution. This effect is quite common if AI is misused.
AI causes more confusion and distracts from the real solution
One issue with AI is that it is marketed as an all purpose tool that is capable to help with any subject. This is not true, and the AI will confidently give false information, which can lead to confusion and frustration. I would say the best thing to do is to lower ones expectations of AI and use it sparingly.
Conclusion:
GenAI can either be leveraged to aid in learning, or impede it. Learning how AI works and its limitations can give users a better perspective on what AI is good for and what it is not. The current state of AI is no where near equal to the capability of the human brain, for the best outcomes people should not lean on artificial intelligence but use it as a tool, and embrace on our own Human Intellegence.
One problem that arose when the internet became mainstream was that, sharing information was difficult because of copy right laws. One of the major goals of the Creative Commons licenses was to enable people to share their content online by releasing their content under an open license. This revolutionised how people used the internet, because now, people could freely access and distribute information at nearly no cost, without having to worry about copy right laws. There has been movement towards open source, both in software and information, however corporations and tech giants are reluctant to contribute to open source, especially if it would compromise profits. I argue that open source should be the standard not only for institutions like those that are funded by tax money, but also massive corporations and monopolistic tech giants.
It is ironic that there is nothing open about “OpenAI”, their AI models are closed-source, and they are moving from non-profit to for-profit. Contrast this with the communist Chinese release of the most innovative and advanced, free and open-source AI model to date, DeepSeek R1. Cable Green states that “In order to solve big problems information must be open” I agree with this statement. This point is evident when considering, open access to Covid-19 studies and information lead to rapid vaccine development, open curriculum’s saves schools and students tens of millions per year, open source software like Linux is the backbone of the entire internet, and open source AI models are leading in innovation. DeepSeek R1 became the most downloaded app on all app stores, ChatGPT at number two. It has effected American markets (NVidea lost ~one trillion), forced OpenAI to release a better free model, and demonstrated that the future of AI is open.
The open source movement is necessary for making rapid progress in the scientific field, therefore the standard should be open. However some of the biggest players are holding society back from making open source the standard. With that being said there has been massive innovation in the open source movement, yet there is a lot of work to be done.
Teaching, and subsequently learning is not a perfect science, there are flaws with any system of teaching. In this post I will describe potential issues with the direct instruction style of teaching, and why I think it is the most popular mode of teaching. Then I will describe an alternative teaching method which is based around inquiry, and its strengths and weaknesses.
This week we learned about inquiry, a couple of things that stood out for me in Week 3: Inquiry Process, & SIFT Methodology was the contrast between teaching methodologies. The direct instruction system is setup such that students are expected to do well on exams and assignments, but the means to achieve the ends, are not accounted for when graded. Essentially the teacher gives the student material and it is in the students hands to do anything in their hands to do well on the test/assignment, with no weight given to the process of learning. The curriculum is mapped down onto the student which can lead to a mismatch in: interest (the student may not be interested in the subject), and difficulty (the content may be too easy or too hard for the student). In some cases, this teaching structure can cause students to only learn the bare minimum, and memorise rather than deeply understand topics and build mastery. I argue that the main reason that this structure is most commonly used in schools is that its resource efficient. Meaning that the ratio between student learning over resources consumed is high, meaning that, an adequate amount of learning can be achieved by students without the school using many resources.
The other teaching method is called inquiry based learning (IBL), it is based on how people naturally learn. For example children try to atomise (take something complex and reduce it to its most simple parts) anything that they are curious about, they would ask their parent a string of questions about something, or experiment with a thing to better understand it, then apply that knowledge to their understanding and build upon it, this is synonymous to learning using inquiry. This form of learning gives the freedom to the student to map their learning up to the curriculum, which leads to higher quality learning, mastery, and retention of both information and skills. I would argue that inquiry based learning is objectively better than direct instruction because it promotes deep learning, competence, and process over strictly getting good grades. The potential downside to this approach is the expense, the ratio of teachers to students, equipment cost, and work space could all add to the cost to IBL.
Given the pros and cons of each teaching style, I propose that schools should implement aspects of IBL into their courses, or offer some fully IBL courses. Doing so would make students more valuable to the work force by enabling them to obtain mastery, competence, and experience in a specialised field of their interest. This would make it much easier for students to find a high-paying job soon after graduating high school.
Before proceeding with your first blog post, we expect you to consider your privacy preferences carefully and that you have considered the following options:
Do you want to be online vs. offline?
Do you want to use your name (or part thereof) vs. a pseudonym (e.g., West Coast Student)?
Do you want to have your blog public vs. private? (Note, you can set individual blog posts private or password protected or have an entire blog set to private, but everything but your posts would be public, such as your URL, title, etc.)
Have you considered whether you are posting within or outside of Canada? This blog on opened.ca is hosted within Canada. That said, any public blog posts can have its content aggregated/curated onto social networks outside of Canada.
First tasks you might explore with your new blog:
Go into its admin panel found by adding /wp-admin at the end of your blog’s URL
Add new category or tags to organize your blog posts – found under “Posts” (but do not remove the pre-existing “Digital Literacy” category or assignment categories, “Inquiry” and “Reflections”). We have also pre-loaded some competencies as categories should you wish to use them to document your learning. If you would like to add more categories, please do so (e.g., add categories to curate materials and learning from your other courses, your hobbies, etc.). You can then build more menus for them. This blog does not have to be all about just this course.
If you have consented to have your posts show up on the course blog feed, see if your blog posts are appearing on the feed on the course website (you must have your blog set to public and the course categories assigned to a post first and have provided your instructor with your blog URL). It may take a few hours for your posts to show up once public, so please be patient.
Add pages
Embed images or set featured images and embed video in blog posts and pages (can be your own media or that found on the internet, but consider free or creative commons licensed works). You cannot use copyrighted photos. If any media does not state its copyright status, then it is considered copyrighted by default. See the course blog about how to find media you can use and how to attribute them. Your lab instructor can help you.
Under Appearance,
Select your preferred website theme and customize to your preferences (New title, etc.)
Customize menus & navigation
Use widgets to customize blog content and features
Delete this starter post (or switch it to draft status if you want to keep for reference)
Do consider, if creating categories for other courses that you wish to curate your learning for, that you may wish to use the course topic as the category as opposed to the course number as those outside of your program would not be familiar with the number (e.g., we use “Digital Literacy” instead of “edci136).
Lastly, as always, be aware of the FIPPA as it relates to privacy and share only those names/images that you have consent to use or are otherwise public figures. When in doubt, ask us. Even if you have permission to comment about a person or public figure, consider how what you write impacts their digital footprint as well as yours. Your lab instructors can review any posts you are unsure about.
Please also review the resources from our course website for getting started with blogging:
This is where you share your updates and reflections for Assignment 2. This posts uses the “Reflections” category which pulls it into the Reflections menu.
