Academic Workflow of an Education Researcher

As an academic researcher, I use a number of software and hardware tools in concert. To illustrate my academic workflow, I created the diagram below [Click on image to enlarge].

Academic Workflow Diagram

"Input" includes the tools I use to collect and organize documents. I distinguish between different document types and input sources. My two favorite tools to organize documents are DevonThink and PersonalBrain. DevonThink allows organizing documents into a hierarchical folder structure. The in-built AI supports storting out new documents into matching folders. PersonalBrain is a dynamic 3D mindmap that allows annotating and tagging weblinks and documents. I currently have over 8000 weblinks organized in PersonalBrain.

"Output" includes the tools I use to write and publish documents. To write academic publications, I use Scrivener to create an outline of the documents and work on drafts. I enter reference tags from Sente into Scrivener. Once I reach a final draft, I export the text from Scrivener to Word and use Sente to generate a bibliography.

What is learning?

There no single and simple answer to the question "what is learning". This blog post aims to give a short visual overview over major theories of learning: Behaviorism, Cognitivsm, Constructivism (classic and socio-cultural), and Networked learning/ Connectivism.

"Learning" is defined differently by different research fields and frameworks. The illustrations below are my attempt to visualize the progression of major theories of learning:

Individual Knowledge Acquisition
Individual Knowledge Acquisition
Collaborative Knowledge Participation
Collaborative Knowledge Participation
Collaborative Knowledge Participation

Figure: Theories of Learning (by Beat A. Schwendimann)

Learning is often closely connected to the nature of knowledge (Epistemology). Like learning, knowledge can be defined in many different ways. In relation to knowledge, Paavola (2005) distinguishes two types of learning. Based on Paavola's paper, I created the following table:

I created the dynamic mindmap below to provide an overview over some major theories of learning and education concepts. This mindmap is ongoing work in progress. Your feedback and suggestions are welcome.

To navigate the dynamic mindmap below, just click on a term and it will move to the center - showing related concepts. You can also search for terms in the textbox at the bottom.


See this mindmap on the webbrain.com website (where you can find other interesting mindmaps).

On Expertise

What are the characteristics of an "expert"? The Oxford dictionary defines an expert as "A person who is very knowledgeable about or skilful in a particular are". However, there is a wide range of how knowledgeable or skilful an expert can be. Education research studies "expertise" for the past 40 years. This blogpost aims to provide a short introduction to some findings about expertise. Education research studied how experts differ from novices to better describe the goal of education: Guiding learners towards more expertise (for example, see "The Cambridge handbook of expertise and expert performance (2006)").


Kozma (2003) described how experts differ from novices:

-Focus on underlying principles instead of surface features.

-See limitations of analogies.

-Use different representations for different purposes.

-See connections between representations and real-world objects.

Research suggests that expertise does not reflect innate abilities and capacities, but is acquired through supervised practice (Ericsson & Charness, 1994).


Research by Chase and Simon (1973) suggests that chess experts don't have a better memory but are better at recognising patterns.

Education research distinguished different types of experts. Cindy Hmelo-Silver et al. (2004) found differences between different types of experts, for example between ecologists (theorist) and aquarium hobbyists (pragmatist). Both are experts but with different focus and goals.

Inagaki (2008) observed that experts are better able to determine the relevance of certain concepts in a certain situation. Hatano (1986) distinguished between routine expertise ("Artisan") and adaptive expertise ("Virtuoso"). The routine expert is capable of skilful performance in a constant environment. The adaptive expert can also perform procedural skills efficiently, but additionally understands the meaning and the nature of his objects that allows him to adapt to novel situations.


Japanase culture has a long interest in the development of expertise (mastery). The video below is an example of one of the last remaining Japanese sword making masters. He notes that the goal of a master should be to train a disciple who is stronger than his master, otherwise the craft would run thin over time.



Handmade Portraits: The Sword Maker from Etsy on Vimeo.

The acquisition of expert knowledge is embedded in a community of practice (See Lave & Wenger 1991). Expertise is socially constructed: Tools for thinking and scripts for action are jointly constructed within social groups enabling that group jointly to define and acquire expertise in some domain. The learner enters a (cognitive) apprenticeship situation in which he/she learns the concepts (tools for thinking) and routines (scripts for action) of the group.

There is an (obvious) limitation to expertise: Expertise is acquired in a limited domain. Outside of this domain, experts are often as naive as laymen, for example Jones et al. (2008).

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References:
-Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4(1), 55-81.
-Ericsson, K. A., & Charness, N. (1994). Expert performance: Its structure and acquisition. American Psychologist. Vol, 49(8), 725-747.
-Inagaki, K., & Hatano, G. (2008). Conceptual change in naive biology. In S. Vosniadou (Ed.), International handbook of research on conceptual change. New York: Routledge.
-Hatano, G., & Inagaki, K. (1986). Two courses of expertise. In H. Stevenson, A. Hiroshi, & H. Kenji (Eds.), Child development and education in japan. (pp. 262-72). New York: W. H. Freeman and Company.
-Hmelo-Silver, C. (2004). Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cognitive Science, 28, 127-138.
-Jones, M. G., Tretter, T., Taylor, A., & Oppewal, T. (2008). Experienced and novice teachers' concepts of spatial scale. International Journal of Science Education, 30(3), 409-429.
-Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. In R. Pea & J. S. Brown (Eds.), Learning in doing: Social, cognitive, and computational perspectives. (pp. 29-129). Cambridge, MA: Cambridge University Press.

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