Joplin is a free, open source note taking and to-do application, which can handle a large number of notes organised into notebooks. The notes are searchable, can be copied, tagged and modified either from the applications directly or from your own text editor. The notes are in Markdown format.

The Obsidian vault that I've created for the students is secure (by invitation only in Dropbox) and THEY CAN CONTRIBUTE to it. I've put the questions for discussion in the content sections, and have asked students to answer the questions on the page. This hasn't resulted in the types of threaded discussions I was hoping for, but improvements to the interface and better questions will hopefully lead to that.

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.

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.

Linux has plenty to offer

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

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.

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.

Confidence implies competence

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.

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).

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

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.

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.

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).

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.

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”

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

influences their need to self-direct their learning and discover information

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.

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.

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

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.

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.