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).

-------

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.

Over 50,000 visits to Proto-Knowledge

Thanks to the over 50,000 viewers who visited the Proto-Knowledge blog!

Reforming schools for the Knowledge Age

Ørestad College (Denmark)

Current public schools are based on an industrial model of schooling: Standardisation and conveyor-belt analogy.

For example:

-Students are grouped by birth-year; Bells and periods; Sitting in rows; Separate isolated subjects; Fixed time to finish a certain grade; Individual standardised testing.

We need to re-think the current schooling paradigm to create a post-industrial school model. We need schools for the Knowledge Age that focus on technology-enhanced project-based collaborative learning. We need schools that support students to learn how they learn best, monitor their own learning progress, and are driven to become life-long learners. 

For example, as an alternative to grouping students by age, they could be group by their performance level, early birds/night owls (morning school/ evening school), work individually/ in small or large groups (depends on context and personal preference).

Research found evidence that industrial-age schooling reduced creative (and divergent) thinking (as students are conditioned for "there-is-only-one-right-answer" thinking).

See this fascinating animation that illustrates the inspiring TED talk by Sir Ken Robinson:

A number of model schools world-wide lead the way towards a post-industrialist way of learning:

A few examples:

-High Tech High school in San Diego (USA)

-Northern Beaches Christian School in Sydney (Australia)

-Reggio Emilio schools (Italy)

The education group WestEd published a report "Rethinking High School: Five Profiles of Innovative Models for Student Success".

Companies like innovative schools.org offer support for reformers to model their schools after successful models.

Education research aims to gain a more complex picture of learning through the field of the "learning sciences". The learning sciences pursue an interdisciplinary approach to further scientific understanding of learning and to implement innovative learning environments. The bi-annual conference ICLS brings togethers researchers from across the world who study learning as a complex multi-layered system.


This video shows some interesting novel physical and virtual learning environments:

Words as vessels for thought

Words can be described as "vessels for thoughts". Our vocabulary affects the ways in which we are able to conceptualize the world around us. Or in other words, without a word for something we cannot think about something.


This linguistic relativity is expressed in the Sapir-Worf hypothesis that says that language influences (or determines) our thoughts.


An example can be found in the book of Genesis in the bible: In the beginning, the earth was without form and void. Only after God spoke the word, plants and animals took form.


Another example can be found in George Orwell's novel 1984: The government works on Newspeak, a language reform that removes all words related to freedom or rebellion from people's vocabulary - and therefore removing people's ability to think about concept such as freedom or rebellion.


Inventing new words allows us to think about new concepts. For example, medical researchers create new names for a set of symptoms. Giving these symptoms a name allows pharmaceutical companies to start research groups, and patients to form special interest groups.


The number of words in English has grown from 50,000 to 60,000 words in Old English to about a million today (source).


The RSAnimate video below illustrates a talk by psychologist Steven Pinker about language as a window into human nature.

Characteristics of a good teacher

Describing the characteristics of a good teacher is complex as teachers' work involves many different aspects. As many education reforms aim to link teacher payment to performance, it is urgent to get solid measurements of teacher quality. The Graduate School of Education at the University of California, Berkeley recently held a forum on how to assess teachers: Grading the teachers. The forum concluded that there is no reliable way to accurately measure teacher performance (not now and maybe never).

The Bill Gates foundation invests heavily in research on how to measure effective teaching (See: Measures of effective teaching factsheet).

Among other qualities, a teacher needs to have strong content knowledge ("what to teach") combined with pedagogical content knowledge (PCK) ("how to teach).

Stephen Harris (from Sydney Innovation in Education) adds another interesting point: Teachers should be authentic and do what they are in charge of "a physics teacher should research, an arts teacher should paint and an English teacher should write novels or poems."