Reflecting on research projects
Recently I’ve been reflecting on the subject of knowledge creation and knowledge management. A big part of an educator’s job is knowledge creation. That is, being able to analyse and synthesise different sources of information with a view to remixing that information and creating new knowledge. That is a difficult thing to do. It requires higher-order thinking.
Spending my time researching topics with a view to synthesising that knowledge and creating something new for a specific audience isn’t an easy thing to do. It goes way beyond understanding a new topic. Firstly you need to think about how sophisticated your own learning of a topic needs to be before you teach it. And you need to think about how sophisticated or complex you want your learner’s understanding to be.
Lower-order and higher-order thinking
A useful framework for thinking about this is Bloom’s Taxonomy (this is the revised version by Anderson & Krathwohl in 2001):
The items are intended to become more cognitively demanding as you go up the pyramid. For example, remembering something is not as sophisticated as understanding. Equally, understanding is easier than evaluating. Educators can use the taxonomy as a progression. For example, you have to understand before you can analyse.
According to Blooms taxonomy, understanding and knowledge acquisition are lower order thinking skills. Research and the creation of new knowledge requires analysis, synthesis and evaluation. These are higher order thinking skills.
Conflating research and learning: Moving from lower-order thinking to higher-order thinking
Sharp (2009: 3) defined research simply as ‘finding things
Qut’. This is fine for collecting facts and figures but from a learning point of view, how can we create a process to absorb the things we find out and then use higher-order thinking to come up with something new?
If I were asked to reflect on that question and provide an answer, I’d start with something like: Synthesising new learning with a view to extending and expanding that knowledge requires cognitive effort in the form of intensity of focus multiplied by time and periods of reflection. Of course, what appears simple, is not necessarily easy. It can take time to understand new and abstract topics. Even then, more time is required to embed that new understanding and become comfortable retrieving or recalling that new knowledge fluently.
A further challenge to moving from lower-order thinking to higher-order thinking is how to start drawing connections between those topics that have been learned. Connecting topics and formulating new ideas, frameworks and hypotheses is a creative process. This is what I find particularly difficult as a researcher and educator. It’s messy. There’s a mysticism associated with creativity. For me, it feels like I just need to wrestle with the new topics until new ideas start to emerge. This can take time which isn’t always available if I’m on a deadline to create a report or piece of training material. (Schön, 1983) talked about the swampy lowland. Moving from lower order thinking to higher order thinking feels messy. It’s when I find myself in the swamp and it’s like I just need to keep trudging along until I find my way out.
I have great admiration for professional researchers who can publish paper after paper of high quality work. I don’t know how they do it. Maybe they are more intelligent than I am. It’s a distinct possibility!
I spent a long time working in Dublin City University where colleagues used to nudge me to consider doing a PhD. But the thoughts of undertaking that scale of research terrify me. I’m not sure I fancy being stuck in the swamp for that long.
A structured approach for knowledge management and research output
A challenge for people who need to create training material and new knowledge is creating a process to do that. Personally, anytime I’ve had to write a report whether that is for work, or for a college assignment I’ve found the process to be stressful and messy.
I find the process very difficult and often I find myself reading lots of different sources but never quite managing to pull in all the points from those sources into the new material that I’m trying to create. And so it occurs to me that surely for academics, and professional researchers there must be a more efficient and effective way to manage one’s own learning and to create new knowledge. With that in mind, I’ve been thinking a lot about the different tools and tactics that I can use in order to improve my own process.
Towards a digital knowledge management toolbox
Transcription: Recently, I have been trying new tools, such as Otter.ai, a transcription tool to record and transcribe streams of thought.
Document management: I have been using a tool called Diigo which allows me to read documents online and highlight passages that I think are relevant and noteworthy. By doing that, I can then export those highlights from Diigo and to capture the highlights from that document into a central place like.
Schemogenic thinking tools: I’ve also been using slideware and digital whiteboard tools recently to help me to structure my thoughts. For example, I’ve been using Mural to add digital post-its which I can then move around and arrange in different ways to visualise relationships between bits of knowledge. It’s almost like kinaesthetic learning. I can look at knowledge from different points of view and see how my thoughts are structured in front of me.
Once I’ve settled on a structure, I can start to write a document based on the structure of the cards or the structure of my Mural board. This approach aligns with an idea I had about PowerPoint. I’ve observed that for decks I have created in the past, if I look at PowerPoint in slide sorter view I can see a schema for my knowledge on the topic of that deck.
Another low fidelity technology that I’ve been testing for that kind of schemogenic thinking is to use blank playing cards. What I’ve done with blank playing cards is write notes on the cards which I can then move around to observe relationships between the notes and how they might be best structured holistically. This is useful for reflecting on how that knowledge is structured in my mind but equally it’s useful to help me create new material because I can move those cards around and mix them with cards from other topics to come up with new ideas.
Personal note management: For years I have been taking notes and recording those notes within the OneNote app. However, a challenge of this is that those notes are taken in a linear way and they’re stored in a way that does not support retrieval or connecting notes to each other.
Recently I’ve been investigating a new generation of note-taking apps. These include tools like Obsidian, Notion and Roam research.
— Obsidian is a note-taking and knowledge management app that promises to let you turn a collection of text files into a network of linked thought.
— Roam Research (from what I can tell) promises similar functionality. It’s a note-taking application that unlike OneNote, provides the functionality to connect notes using something called “networked thought” — which essentially produces relationships between notes you’ve created.
— Notion also allows you to take notes but it can also be used for project management and collaboration.
These tools are interesting because their promise is that they allow people to take notes while also enabling the connection of those notes to see the relationships between those notes. For example, imagine I use one of these tools for daily journalling. Over time I can start to see themes in those entries because the tools allow me to create a visual map based on keywords etc. As I write, I can also add tags to represent ideas, insights and inspirations. Instead of those ideas getting lost in multiple physical journals, I can pull them all together with the click of a button. In that sense, they promise to expand your memory and ability to produce new work.
Something that I would like to do in my research is investigate these tools with a view to creating a process for capturing notes with a view to efficiently retrieving and remixing those notes and creating new material in future. If I can do that, I think it will increase both the volume and the quality of my output and decrease the stress and confusion that I sometimes feel when I am working on a research project. This could be useful for me as an individual content creator however I think a more powerful use case might be for organisations that need to create a lot of content in the form of reports, videos and elearning. For example, a typical scenario in my organisation is that we write a report about a marketing related topic. Somebody takes ownership of that report and works through the origination, research and production of the report by themselves in whatever manner works best for them. Once the report is produced to a high enough standard and in good time, nobody really pays any attention to artefacts that were created throughout the research process. Artefacts might include ideas for future content, well-written and unused content and of course the research content itself. Imagine this can all be strategically stored in a networked note-taking tool. All of these bits of content become assets which can be retrieved and repurposed for future content projects. This idea has commercial merit because in non-academic report writing, there’s a lot of content that get rewritten over and over. If that content can exist as assets, it can be retrieved and slotted into new reports as required, thereby reducing the time it takes to produce new content.
There are two obstacles to overcome to create this kind of research process.
- Firstly, each of these tools comes with a high learning curve. This means that I’d need to invest a lot of time investigating these tools and identifying variables to evaluate them.
- Secondly, technology is never the solution in its own right. It is the strategic deployment of the technology. Utilising these tools for research will require either the creation of or the deployment of a methodology for knowledge capture, knowledge mixing and knowledge creation.
