27 Matching Annotations
  1. Last 7 days
    1. Hypothes.is has both RSS and Atom Feeds. So the IFTTT “if” is a new item in your feed which creates a text post in some appropriate storage account. I use OneDrive as the “that” target, but I’m sure you could potentially use others with some experimentation. If you have something that only saves as .txt files, that’s fine, you can simply rename them as .md files for your vault later.

      I’ve described some of this before at https://boffosocko.com/2020/08/29/a-note-taking-problem-and-a-proposed-solution/ for those interested in further details.

      Hopefully this helps (until someone has a more automated version).

    2. In academia it’s critical to have a system that allows us to read and mine important ideas from papers into your vault as efficiently as possible. My method has continued to evolve and I’m finding it more efficient now. In a nutshell, I’m now adding the one-sentence summaries to highlights as I’m reading (and the tags where possible). This means I don’t need to read the source more than once; instead I’m processing them as I’m reading because that’s when I discover them as important points in the first place. I then bring them into Obsidian in a single note per paper/source. I title each note Surname, date (e.g., Smith, 2018). It’ll make sense why in a moment. Each idea within the note is structured like this: One-sentence summary of idea | Original idea in the author’s words (Reference, date, page number). T: #tags #go #here C: Any connections to other notes or ideas - not necessary to include for every idea but it’s useful to think of connections where possible If you structure all the notes this way, it means you can then add the ideas straight into your index with transclusion without needing to create any additional notes (in the past I created a new evergreen note for each idea). An example of a transcluded idea to pop into your index would be like this: ![[Smith, 2018#One-sentence summary of idea]] This allows you to see the source and the summary of the note in edit mode and just that idea transcluded from your note page in the preview mode. I have another approach for actually turning those ideas into publications, but this is the main approach for processing notes into my index. There may be even more efficient ways to do this. The key I think is being able to process ideas into your vault as quickly as possible while still tagging and making connections to help with later retrieval of ideas. Since changing to this approach I’ve written a couple of book chapters with very little cognitive strain and I’m reading more than in the past (it’s addictive because every paper has the potential to be used to level up your knowledge base). Hope this is somewhat helpful to others. The evolution will undoubtedly continue. I know there are awesome examples of how to do all kinds of things in Obsidian but all I’m really aiming for is being more productive in my academic role. The rest is all interesting but additional to my main purpose for this wonderful app.

      Another great synopsis of useful tips in using Obsidian for research.

      The idea of using the general form ![[Smith, 2018#One-sentence summary of idea]] can be particularly powerful for aggregating smaller ideas up into a longer work.

    3. I’m an Australian academic in the field of education. I read the How to take smart notes book and a couple of Luhmann’s articles which were translated into English. I also would recommend looking at the writing of Andy Matuschak on how to label your notes, what to include in them, and so on. Here’s the process I’ve come up with (which continues to evolve): Initial highlighting: Read journal article via Zotero. Highlight the parts that are relevant to you using the default PDF viewer on your computer. Use Zotfile to extract the highlights (and any notes) in Zotero, then paste them into Obsidian in a new note. I have a template I copy and paste to start each new highlight note with relevant details like the author names, date of publication and so on before the highlights. Refine highlights: Look through your highlights from the article and use the Obsidian highlighting feature (==like this==) to pinpoint what’s valuable in each highlight. This makes it easier to complete the next step, particularly if it’s a long paper or you have to come back to it. Skip if necessary. Process highlights into literature notes: Summarise the highlights into your own words. Add any personal insights. Each literature note should relate to one idea. I do this directly above the highlight notes using bullet points and a L - for literature notes and a H - for highlight notes. Try to write the literature note as if it was part of a journal article. Add a label to each literature note: Above each literature note, I add a label, which should be the briefest possible summary of the literature note. Have this label inside double square brackets. Avoid labels like “Definition of X”. Instead, write “X is y and z”. Try to be specific. I mainly use the bracket links in this way. An example label might be [[E - X is y and z]]. I use E - because it will soon be an evergreen note. Add each label to an index: The index will be a long list of all your literature note labels. Categorise the labels in a logical manner. Create evergreen notes: Click the label (which is a link to a new note) and copy/paste the literature note text (which will be quite short) into this new evergreen note. Add connections to other notes categorised in the same place in your index plus any other relevant evergreen notes. Add relevant tags. The index may not be overly important in the long run, but it definitely helps at this point with connection making. I also add the reference details at the bottom of each evergreen note. Next it’s time to create your paper. 7a. (Top down approach) Create journal article outline: Create an outline for your article, chapter, application, or whatever you’re working on. You can make a quick template with the relevant stages of the genre (e.g. introduction, literature review, and so on). Then, drag relevant evergreen notes into the sections. You’ll need to massage the gaps between notes to make it cohesive. If you use a note, add a tag to say so. You’ll need to reword the note if you use it again in another paper to avoid self-plagiarism. 7b. (Bottom up approach) Add evergreen notes to papers: Instead of starting with a paper outline, you might look at your notes in the index and consider what kind of interesting questions they might help you answer, then build your paper from there. I hope someone out there finds all this useful. One of the best things I’ve done is create a note called master production line which includes these numbered steps as headings, and then I can add my highlight notes as they’re created and move them down the production line as they’re processed. I also organise them in certain steps (like 2 and 3) as high, medium and low priority. It means you never lose track of notes and there’s always something you could be working on. The bit I’m still figuring out is the last step: how to go from evergreen notes to paper drafts as efficiently as possible. I’m a little old fashioned, so I’ll probably so the final edit in Word once everything else is done in Obsidian. The multiple window support in Obsidian is great, but still a bit janky, and this method requires multiple windows to be open at a time. Hopefully a future update keeps the windows in the one spot.

      This is an excellent overview of how to take notes for academic research and creating writing output.

    4. Others on the page here (specifically Dpthomas87's A, B, C) have done a great job at outlining their methods which I'm generally following. So I'll focus a bit more on the mechanics.

      I rely pretty heavily on Hypothes.is for most of my note taking, highlights, and annotations. This works whether a paper is online or as a pdf I read online or store locally and annotate there.

      Then I use RSS to pipe my data from Hypothes.is into a text file in OneDrive for my Obsidian vault using IFTTT.com. I know that a few are writing code for the Hypothes.is API to port data directly into Roam Research presently; I hope others might do it for Obsidian as well.)

      Often at the end of the day or end of the week, I'll go through my drafts folder everything is in to review things, do some light formatting and add links, tags, or other meta data and links to related ideas.

      Using Hypothes.is helps me get material into the system pretty quickly without a lot of transcription (which doesn't help my memory or retention). And the end of the day or end of week review helps reinforce things as well as help to surface other connections.

      I'm hoping that as more people use Hypothesis for social annotation, the cross conversations will also be a source of more helpful cross-linking of ideas and thought.

      I prefer to keep my notes as atomic as I can.

      For some smaller self-contained things like lectures, I may keep a handful of notes together rather than splitting them apart, but they may be linked to larger structures like longer courses or topics of study.

      If an article only has one or two annotations I'll keep them together in the same note, but books more often have dozens or hundreds of notes which I keep in separate files.

      For those who don't have a clear idea of what or why they're doing this, I highly recommend reading [[Sönke Ahrens]]' book Smart Notes.

      I do have a handful of templates for books, articles, and zettels to help in prompting me to fill in appropriate meta data for various notes more quickly. For this I'm using the built-in Templates plug-in and then ctrl-shift-T to choose a specific template as necessary.

      Often I'll use Hypothes.is and tag things as #WantToRead to quickly bookmark things into my vault for later thought, reading, or processing.

      For online videos and lectures, I'll often dump YouTube URLs into https://docdrop.org/, which then gives a side by side transcript for more easily jumping around as well as annotating directly from the transcript if I choose.

      I prefer to use [[links]] over #tags for connecting information. Most of the tags I use tend to be for organizational or more personal purposes like #WantToRead which I later delete when done.

      When I run across interesting questions or topics that would make good papers or areas of future research I'll use a tag like #OpenQuestion, so when I'm bored I can look at a list of what I might like to work on next.

      Syndicated copies: https://forum.obsidian.md/t/research-phd-academics/1446/64?u=chrisaldrich

  2. Feb 2021
  3. Dec 2020
    1. However, the opposite was actually experienced in this study. Students reflected a lack of interest in and ability to participate in blended learning activities which seemed quite frustrating to most participan

      Because there is nothing "good" about blended learning in itself. All teaching and learning activities, if implemented poorly, have poor outcomes. Students disengage when the activity has no value (or perceived value) regardless of the medium in which the activity takes place. It has little to do with technology.

    2. hat’s all that I tried, and I got such a fright that I stopped... So again, for fear of wasting time and embarrassment, rather leave it.

      It doesn't seem like anyone has suggested to these participants that they should only be using technology to try and solve problems that they are experiencing and only when the technology presents a simpler solution than alternatives.

    3. UNLearn courses is like a garden. It needs constant attendance. So it’s a large amount of work to do it, and once it’s done, it doesn't require that much work to tweak it and fiddle with it, but it needs constant work.

      OK but so should your F2F course. You should also constantly be maintaining and refining those resources. I think that this is another opportunity for the researcher to highlight how many academics just don't see all of the time and effort that F2F requires, simply because it's what they do. They "see" the additional work of online but they ignore all the work that's supposed to be going into F2F as well.

    4. Confidence implies competence

      Not at all. These two things might be associated but they are by no means necessarily associated. In fact, there is good evidence that the least competent can sometimes be the most confident. See the Dunning-Kruger effect.

    5. Therefore, it could be argued that belief regarding the usefulness of technologies could lead to change and ultimately the actual use of digital technologies in teaching and learning.

      This goes both ways. A teacher who believes that their job is to control access to specialised information, and to control assessment may use technology to close down learning opportunities (e.g. by banning the use of Wikipedia, YouTube, etc.) and even insisting on the installation of surveillance (proctoring) software on students' personal computers.

      Again, you can argue that technology in itself doesn't make the difference.

    6. Some teachers might believe that their traditional way of transmitting knowledge to students is still the best (Owens, 2012). These pedagogical beliefs can determine whether teachers will implement technologies or not (Judson, 2006; Owens, 2012).

      This seems to continue the assumption that "using technology" = good and "not using technology" = bad. But I really want to see the candidate articulate the understanding that good teaching with technology can be great, but that bad teaching with technology can be awful. Technology can amplify what is there but it doesn't inherently improve something that is bad.

      It would also be interesting, based on the candidate's writing, to hear some reflexivity on their own beliefs, and how these beliefs about the inherent goodness of technology has influenced the direction of the thesis.

    7. It is clear from Bandura’s theory that individuals have the capacity to make their own choices and that several factors influence these choices

      Is there a conflict here with the notion of free will (i.e. that we don't have any)? See Dennet, Harris, Coyne for alternative positions to the notion that we have any agency i.e. that in any situation we could have done something other.

    8. Self-efficacy is defined by Bandura as people’s “judgment of their capabilities to organise and execute courses of action required to attain designated types of performances. It is concerned not with the skills one has but with judgments of what one can do with whatever skills one possesses” (Bandura, 1986:391). In other words, self-efficacy refers to the belief in one’s own ability to perform a task or behaviour (Bandura, 1997), influencing how we think, what we believe and how we conduct ourselves.
    9. n order to determine behavioural intention in a new innovation, Venkatesh and Davis (2000) refer to two key belief constructs to examine: perceived usefulness (PU) and perceived ease of use (PEOU), which are the predictors of users’ attitudes towards using digital technologies. Consequently, attitude depicts the intention to use digital technologies, which affects actual use.

      What we believe influences how we behave.

      "...when a tool is both useful and easy to use, actual system use is more likely"

    10. TAM is based on Fishbein and Ajzen’s theory of reasoned action (TRA), which offers a theoretical perspective that explains human conduct and the significance of one’s beliefs in order to anticipate behaviour (Ajzen & Fishbein, 1975).
    11. This section will focus on the technology acceptance model (TAM) (Davis et al., 1989) and the theory of planned behaviour (TPB) (Ajzen, 1985). The commonality in these theories (TAM, TPB and SCT) will then be discussed. These three perspectives provide a theoretical foundation for understanding the individual’s reactions in the integration of digital technologies in teaching and learning. While TAM and TPB focus exclusively on teachers’ beliefs about digital technologies, SCT focuses on the teachers’ behaviour.
    12. Bandura (1986:18) suggests that these three factors, namely the person, the behaviour and the environment are “all inseparably entwined to create learning in an individual”
    13. heories such as the theory of reasoned action (TRA) (Fishbein & Ajzen, 1975) were drawn on, which initiated one of the most well-known theories in technology adoption, namely the technology acceptance model (TAM) (Davis, Bagozzi & Warshaw, 1989), which will be discussed later in this chapter. In the early 1990s, researchers started using social cognitive theory (SCT) (Bandura, 1986) when they realised the importance and relevance of self-efficacy in the adoption of digital technologies
    14. influences their need to self-direct their learning and discover information

      Categorising entire cohorts of students based on their date of birth.

      There is evidence that the simplistic categorisation of entire cohorts of students based on their date of birth is problematic. It also often fails to distinguish between those who feel comfortable using relatively simple tools in the context of social media (sharing, liking, etc.) and the more complex and nuanced use of digital tools to engage in professional learning, especially when that learning includes collaboration.

    1. If you look at the same graph with distance 2, the layer of additionally visible nodes show how my new Notion might be connected to things like online identity, using the environment to store memory and layered access to information. This triggers additional thoughts during the writing process.

      Lovely. This is such a great insight that I can already see is going to help me a lot.

    2. Usually while writing a Notion, I show the graph of how it connects to other Notions/Notes alongside it. I set the graph to show not only the 1st level links, as that only shows the links already apparent from the text I have in front of me. I set it to show 3 steps out at the start, and reduce to two steps when there are more links.

      This is a great idea that hasn't occurred to me before. When looking for non-obvious relationships between concepts (something that I think forms part of creativity), it makes sense to have the graph view open alongside the note you're working on.

  4. Oct 2020
    1. Obsidian is a powerful knowledge base that works on top of a local folder of plain text Markdown files.

      Alright, I think I may now have things set to use an IFTTT applet to take my Hypothes.is feed and dump it into a file on OneDrive.

      The tiny amount of clean up to the resultant file isn't bad. In fact, a bit of it is actually good as it can count as a version of spaced repetition towards better recall of my notes.

      The one thing I'll potentially miss is the tags, which Hypothes.is doesn't include in their feeds (tucked into the body would be fine), but I suppose I could add them as internal wiki links directly if I wanted.

      I suspect that other storage services that work with IFTTT should work as well.

      Details in a blogpost soon...

      Testing cross-linking:

      See Also:

      • [[Obsidian]]
      • [[Hypothes.is]]
      • [[note taking]]
      • [[zettlekasten]]
      • [[commonplace books]]
      • [[productivity]]

      hat tip to Hypothesis, for such a generally wonderful user interface for making annotating, highlighting, bookmarking, and replying to web pages so easy!

    1. Long comment threads on blog posts are a mixed blessing. It is great to have stirred up such great community discussion. But anything beyond, say, 20 comments is beginning to get beyond what anyone is willing to actually read. What likely happens is people read the article, read the first few comments, then start just scanning them (at increasingly swift rates) until they hit the bottom, then read the last one or two. At least, that’s what I do.

      Doing a quick test of Hypothes.is notes to Obsidian.via a storage source.

      Also checking the difference between html as a source and markdown as a source.

    1. So today, as a somewhat limited experiment, I played around with my Hypothes.is atom feed (https://hypothes.is/stream.atom?user=chrisaldrich, because you know you want to subscribe to this) and piped it into IFTTT. Each post creates a new document in a OneDrive file which I can convert to a markdown .md file that can be picked up by my Obsidian client.

      Trying to see if this work for me when linking with google drive. Unsure how to convert to markdown.