Human influence on biological speciation (NY Times)

This article (NY Times, may require registration) is interesting for many reasons. The main idea is to point out the influence that humans have on the evolution of other organism populations. The process of speciation seems to be moving towards hybridization and selection for intermediate traits for many organism populations. Classification issues will abound - a good biology "hook" for the idea of representing "differentiated" cognitive resource populations.

A whole new twist on "I Can't Quit You Baby"

Patterson et al have published a study in Nature (press release) indicating that the common ancestry of humans and chimpanzees is more complex than suggested by recent and historic data interpretation. The new study, which utilized a large number of high fidelity DNA sequence comparisons, presents data that suggests that the common ancestor population split once, came back together to form a hybrid population, and then diverged once again to form the modern human and the modern chimpanzee. DNA sequence similarities (particularly on the X chromosome) indicate that the first population break resulted in the modern chimp line, and that the hybrid population evolved into the modern human.

..."Don'tcha realize sweet baby? Woman I don't know... which way to go. Woman I can't quit you babe." (from "I Can't Quit You Baby", a blues song performed by a number of great artists)

A distal enhancer and an ultraconserved exon are derived from a novel retroposon : Nature

A distal enhancer and an ultraconserved exon are derived from a novel retroposon : Nature

In essence: DNA sequencing of all modern vertebrates shows that there are many regions that are always the same, whatever the organism. Enter the modern "coelacanth", an organism (recently thought to be extinct) that has changed very little (in multiple measures) in hundreds of millions of years. When comparing the DNA of the coelacanth with vertebrates (especially mammals), it is found that some of the highly conserved regions in vertebrate DNA act as transposons (sequences of DNA that frequently switch position within the genome) in the coelacanth. Researchers looked at the vertebrate function of one of these transposon sequences and found that it had positioned itself within an RNA processing gene, making it possible for the cell to have another alternative splicing pattern for that protein product (thereby altering the function of the protein).

Potential difficulties with cognitive resource classification

For now, this is just a quick post so that I don't forget a thought that I had during yesterday's CogGroup presentation by JED. Before the presentation, I used a white board to draw a cladistic representation of a classification system for cognitive resources. One of the theoretical benefits of cladistic classification is that, as Dawkins points out in The Blind Watchmaker, with perfect information, and with consideration only of currently (emphasis mine) living individual organisms, we should be able to make a branching represenation that has only binary pathways. This is part of his discussion on dealing with intermediate forms in systemics - Dawkins argues that the biosphere is unique in that it is possible to perfectly classify organisms in unique and non-overlapping categories (i.e. an organism can only belong to one species, whereas I might want to classify my CDs by Mos Def and Talib Kweli as both "Hip Hop" and "Urban Folk").

Now let's shift into considering classification activities with regard to cognitive resources - the species of thought, which exist in what is called the noosphere. The thought I had yesterday is with regard to intermediate forms. I was showing my advisor how the cladistic representation has a "built-in" ability to show the results and process of at least one type of conceptual change (dual construction). The problem, though, is with the common ancestor: is it really "dead"? It seems that the context sensitivity and complexity of the neurocognitive system would make it very difficult to survey the cognitive ecosystem (an issue with "perfect information"), and anecdotal experience along with intuition tells me that the ideas that students have when they begin a learning process (the common ancestor) will likely persist beyond conceptual change. So, there is certainly divergence of a population and speciation, but the common ancestor still seems to survive. This common ancestor is, by definition, an intermediate form!

Ahhhhhh...now this feels familiar. A wrench in the works: cognitive evolution can occur within the neural life cycle. Must be on to something :) Now it's time to teach...

Cognitive systematics and an ontology of cognitive resources (Part 1)

Within the realm of scientific classification, there appear to be three prominant methodus: heirarchical categorization, cladistics, and phenetics.

The first method for classifying the biosphere is based on heirarchical categorization, as per the familiar derivative of the Linnean system: (kingdom (phylum (class (order (family (genus (species))))))). The actual objects that are categorized are individual organisms, with the most specific and exclusive category - species - describing a population of organisms that are similar in some aspect (there are many perspectives on the relative importance of similarities - some definitions of species are biased toward sexually reproducing organisms, while others focus on common ancestry). Perhaps the most important aspect of the species category is that it is the only level of classification that is based on physical objects. All higher, more abstract levels of the heirarchy are based on similarities between and among categories, not on physical objects (because of genetic variability within a population of individuals, I reject the notion that there can be an actual physical instance of species, even among asexual organisms - this debate is even less appropriate among sexual organisms). The system terminates in the most general and inclusive category of kingdom, although the inherent difficulty of such abstract processing has resulted in the recent recognition of a 6th kingdom (archaebacteria) and the suggestion of a category more abstract than kingdom, called domain.

The second method of biological classification is known as cladistics, and is based on the notion of binary pathways forming tree-like branching patterns that demonstrate the relationships of organisms with regard to common ancestry. In this system, the most specific and exclusive category of organisms is still the species, but this method differs from heirarchical categorization because the more abstract connections between species are not guided by categorical similarity, but by the degrees of separation between two species and a common ancestor. Terms used to describe abstract groups of species use the root "phyletic", with prefix modifiers "mono", "para", and "poly".

Coming up: a brief summary of phenetics, and the beginnings of applying these methods to the cognitive domain. In short, I started my thinking about classifying cognitive resources using the familiar heirarchical categorization method, with resources as "species", groups of resources as more abstract "classes", and functions of groups of resources in conceptual change as the most abstract level of categorization, or "kingdoms". While I think that this system will present more utility than currently available, I'm beginning to think that a cladistic representation might also have utility, especially with respect to the developmental patterns observed in long-term learning (specifically I'm interested by the late onset of epistemological resource maturation mentioned in a Hofner article I have in a stack somewhere...). Further, the phenetic system appears to be most useful at the species level of biological classification, so I'm going to explore its utility at the interface between neurological activity and cognitive resources.

Fossil Find Is Missing Link in Human Evolution, Scientists Say (National Geographic)

Also see the article from Yahoo News, and the article from the San Francisco Chronicle. The co-leader of this particular effort is Tim White at UC Berkeley, and it's noteworthy that SFC article is linked from the UC Berkeley research news announcement page. Specifically, the SFC reporter emphasizes the importance of the Middle Awash region in Ethiopia to providing hominid fossil data. Also, it's interesting to note how different news sources report on the same event: Yahoo's article title claims proof of evolution, while National Geographic and the San Francisco Chronicle seem to let the data present itself. Yet again, it brings up the issue of scientific literacy in the media, especially with regard to the differences between data, evidence, and proof. Perhaps the variety of word use and emphasis in these articles also demonstrates important differences in the scientific epistemologies of the authors.

Life is busy

Wow, I started off here with a bang a few months ago, and I think I've just hit a wall over the past two months. First I got the stomach bug that was going around and was out of commission for a solid 48 hours. Catching up with missing a day of school is tough. You catch up, you get behind, and the cycle continues. Then Ayla was born, and it was great to take a day off to be with the fam, but again, got behind. Then the next week I took my old car in for an oil change, and came out 4 hours later with a new one -- OK, I guess I can't complain too much about that. But in any case, life's been busy. Last week I put a ton of effort into my self-evaluation for work - I'll probably post a bit of that material. It was great to have an opportunity to reflect back on the past two years of work since I wrote my first self-evaluation in my first year, when I was teaching part-time. My oh my how things can change - I'm teaching full-time, I've completely changed my thesis project, I bought a house with my partner and then we got married! Woosh!

So, long story short, I haven't had a lot of time to work on the ol' research project, but I was happy to get a comment from Mentifex, with a link showing that this blog has been linked from the Mind.Forth project on SourceForge. Tres cool! I'm looking forward to doing some reading and checking out the project in more detail.

In any case, I'll be on vacation from teaching for a week, starting tomorrow afternoon. I'll be putting some energy into putting some new material up here. I'm excited to make a presentation to our Cognitive Group at UMaine - perhaps not on April 20th as we had scheduled, but hopefully soon. I'm focusing my efforts a bit more (at least, when I have spare brain cycles) on a more narrow aspect of my work: developing a taxonomy for cognitive resources, with a particular emphasis on categorization according to functional roles involved with conceptual change (learning).

Evolution in action!

Yesterday morning at 8:28am my sister gave birth to her first child, the first grand-child for my parents. It's a girl! Her name is Ayla Sophia, and she's beautiful! 6 pounds 11 ounces, 20 inches long, and incredibly calm -- well, so far :)

On the Origin of Concepts - Part 2

In the first part of this extended post, I discussed how I've found biological research patterns to be a useful analogy when doing my work in cognitive education research. I started by trying to characterize the concept of biological evolution, working on a hunch that it was a coordination class concept, which itself was based on a hunch that coordination class concepts can demonstrate the four classical patterns of conceptual change. Although I quickly found that biological evolution fit with many of the criteria for the coordination class model, I got in my own way and started looking at the model pretty closely. I couldn't shake a couple of major thoughts, both of which were rooted in my prior education experiences in neuroscience, developmental biology, and teaching. First off, the coordination class model looks a lot like neural networks, which is a good thing, since - so far - we're making claims about human thinking and learning, and we know from neuroscience that those functions are generated by the brain. Second, I've not yet discovered a conceptual model with an internal and inherent mechanism for learning - that is to say, I kept wondering how it was that a coordination class concept actually changed in learning experiences. Third, I've witnessed a lot of different learning experiences for a number of different high school students first learning about the concept of biological evolution, and I feel totally confident in saying that personal beliefs about the nature of knowledge (fancy: personal epistemology) are part of the conceptual structure and strongly influence the way in which a concept develops - especially the concept of biological evolution. I've also been a part of some incredibly creative learning experiences, and it seemed to me that students with the strongest inventive thinking skills were also the students that formed the most expert-like concepts.

To start answering my first observation that coordination class concept graphs look a lot like neural networks, I did a bit of research into neural networks and learning. Needless to say there is a lot of research on this topic in vivo, and there are also many efforts to model neural networks as abstractions in computer software. One of the interesting ideas that turned up in this process was the idea of scale-free networks. These are, in essence, networks of objects that retain certain properties at different levels of size and complexity. Interestingly, these types of networks exist at (at least) the macromolecular, cellular, and cognitive levels of complexity.

To start answering my second observation that coordination class concepts lacked an internal mechanism for learning, I began researching conceptual change theory literature. I found a simple theory on conceptual change that relied on three progressive processes: plausibility, comprehension, and fruitfulness. Based on my teaching experience, I chose to use these processes as functional categories for different types of parts of thinking in science: plausibility is linked to inventive resources (like imagination), comprehension is linked to sense-making resources (like processing time scales), and fruitfulness is linked to epistemological resources (like knowledge-as-transmitted-stuff). Further literature review has demonstrated that each of these categories can be divided into smaller categories. So, I've started to think of this as the development of a taxonomy for the parts of thinking.

More to come - time to get ready to teach.

On the Origin of Concepts

So, a great meeting with Michael today. I knew we'd hit it in stride right from the get-go when he started off our conversation with an update on cognitive resources. One of the major topics of discussion at the first Cognitive Group meeting this semester was the nature of the components of thinking (see my "farewell to p-prims" post). Word from Michael's contancts in the University of Maryland group is that the term "resource" was created with the intent of allowing for larger scale representations of thinking (so, a concept can be a resource for a larger concept), and that they are not necessarily primitive (though they can be). So, I think that pretty much settles it for me: p-prim, while a useful functional descriptor, isn't going to be useful enough for my purposes. Up until this point, I think I've been fairly vague on that - purpose, intent - but I think today was one of those great times in academic life when you really, really refine your work.

So here it is: I'm developing a taxonomy for cognitive resources, and in so doing, I'm also creating a method for determining and evaluating conceptual complexity. I'm doing this because I am interested in developing a model for the concept of biological evolution that is based on a knowledge-in-pieces view of cognition, and I've been frustrated by the formal, functional, and developmental limitations that are characteristic of existing models for concepts and hypotheses on conceptual change. Because of my frustrations in the modeling of biological evolution from a cognitive perspective, I've applied classical biological methods in the cognitive realm: anatomical dissection (identifying the pieces of thinking and their connections), physiological mechanism determination (indentifying the functions and functional mechanisms of pieces of thinking), developmental classification (characterizing changes in thinking over time, the mechanisms for change, and the influences on change), and taxonomic organization (classifying the formal and functional similarities and differences between and among multiple aspects of cognition).

Next - why this is going to be very useful.

Epistemological Resources and a Developmental Assessment

Steelers 21, Seahawks 10. I was rooting for Seattle since it was their first Super Bowl appearance, but it's good to see the Lombardi Trophy stay in the AFC. Maybe next year will bring some better post-season play from the Pats.

Anyway...

There were a total of four papers that I found the other night at UM, and the next one I want to talk about is by Tsai and Liu, called "Developing a Multi-dimensional Instrument for Assessing Students' Epistemological Views toward Science" and published in the October 2005 issue (v27, n13) of International Journal for Science Education. In this paper, students used Likert scales to "agree" or "disagree" with a number of statements that probed their epistemological view of science. The "multi-dimensional" aspect is really just the further differentiation of epistemological resources into five major categories: social negotiation, inventive and creative nature, theory-laden explanation, cultural impacts, and changing and tentative features. Within each of these categories are a minimum of three ideas (I'll include them in my model as specific resources); social negotiation has 6, inventive and creative nature has 4, and the other three categories each have 3 resources within that category.

Imagination as a Cognitive Resource

I recently stumbled upon a few references to the role of imagination in science learning. The first "hit" turned up in a review of recent editions of the International Journal of Science Education. In the April 2005 issue (Volume 27, Number 5) I found an article by James H. Mathewson called "The visual core of science: definition and applications to education" (pages 529 - 548). [note - I can't find any home page for James H. Mathewson on the SDSU site or elsewhere - he's doing interesting work, so I'm hoping to turn up more info in the future. another note - SDSU apparently has a program that is very similar to UMaine's MST - it's called the Center for Research in Mathematics and Science Education, and features a Ph.D. option.] In the past, he's also written an article called "Visual-spatial thinking: an aspect of science overlooked by educatiors", which appeared in Science Education, v83 n1 p33-54 Jan 1999. I have not yet read this article. Also of note, I was looking through the references in "The Visual Core of Science" and found a book that turned out to be very interesting. The author is Arthur I. Miller, and the book is titled Insights of Genius: Imagery and Creativity in Science and Art, published by MIT Press (paperback in 2000).


So, a brief mention of some of the aspects of the Matheson paper that were most interesting. First is the notion (developed by Gerald Holton - not yet researched) that imagination has three different functional sub-categories: visual, metaphoric, and thematic. I am going to map these as resource categories within the imagination category.


OK, well, Super Bowl parties are 'bout to start, so I'll be catching up on this post tomorrow.

On the Development of a Textbook on Intelligent Design

As it turns out, the first draft of the Intelligent Design textbook, "Of Pandas And People" was titled "Creation Biology". Only after the US Supreme Court ruled in 1987 on Edwards v. Aguillard (also see article from Wikipedia) were most instances of the word "creation" in the draft replaced with the phrase "intelligent design".

Groups in Kansas Preparing for Challenges on New Evolution Education Standards

The Lawrence Journal-World, of Lawrence, Kansas, reports on a public meeting held this weekend at Kansas University. A number of different speakers discussed the science standards adopted by the Kansas State Department of Education on November 8, 2005. Of note is a disclaimer that precedes the standards and specifically addresses the theory of evolution ("Rationale", page ii). Furthermore, while the KSDE does not specifically endorse the inclusion of Intelligent Design in the curriculum, it does guide teachers to "instruct students about scientific explanations of the origin of life, as well as scientific criticisms of those explanations" (grade 8-12 cluster, Standard 3 (Life Science), Benchmark 3, Indicator 7, page 77). The event at KU focused on the likelihood of legal challenges to these standards, given the outcome of the Dover, PA case regarding the required inclusion of a statement about Intelligent Design in high school Biology classes.

Science and Spirituality Sunday - "Original Sin"

Today I'm starting a series on science and spirituality. I hope that I'll be able to write an article on this specific topic once a week, and Sunday has a certain ... je ne sais quoi. Well, not really - it's a day on which millions (billions?) of people around the world set aside at least an hour from their day to attend spiritual gatherings. And ... it has a nice alliteration thing happening with those other "S" words up there :)

I did a little search on Google News for "evolution education", and turned up a great article over at the Centre Daily (the newspaper of State College, PA, here in the USA) called "The argument over origins". The authors, Burrell and Mason, do a really nice job summarizing many of the issues that are involved with evolution education, focusing specifically on the issues of Intelligent Design, creationism, and religion in teaching high school Biology. I particularly enjoyed how the authors point out that students enter the classroom with their own ideas, which sometimes include particularly strong religious beliefs that they would like to discuss. Later in the article, the authors also give a brief mention to the difficulties that teachers and students alike might, or do, face, when the door is opened to such belief-oriented discussions.

As a teacher, a scientist, and a spiritual human being, I can't help being a little bit sad at the degree to which these important issues have become points for all-out fights to commence, dividing communities at various levels. I was raised within the Roman Catholic church, baptised and confirmed, but left the organization after my parents divorced in high school and were denied communion with God. As a child of a very unhealthy parental relationship, I couldn't understand why this incredibly good (but difficult) decision that my parents made would be punished. I mention this only to demonstrate that I am not unfamiliar with scripture - my own, personal relationship with it has changed, but I still find the teachings of Jesus Christ to be incredibly challenging and inspirational. When I went off to college and realized that I needed to decide upon a focus for my studies, I chose neuroscience because it seemed as though it would help me to understand spirit and mind more fully. In the following years, I've learned a lot about the inner workings of the brain and the concept of biological evolution, and I've found that knowledge to enhance my spirituality, not diminish it.

I suppose that one of the major distinctions that I've come to understand in this process is the difference between religion and spirituality. Some people might be tempted to think that by leaving the Catholic faith, I somehow became less connected with my own spirituality, but yet I've found the opposite to be true. I think that a deep understanding of science, and specifically evolution, has helped me to find an even deeper meaning in the very same teachings that I learned in church as a younger person. One such idea is that of original sin (see entries in the Catholic Encyclopedia and Wikipedia).

The main idea of original sin, from the Christian perspective, is that God created humans with free will - we can follow the rules that God sets forth, or we can break those rules. In the Garden of Eden, where God created humanity, his first creations, named Adam and Eve, decided to eat the fruit of a tree that God had forbidden them to eat. After that decision, Adam and Eve were no longer welcome in the Garden, and suffered a demotion in their relationship with God. As a result, all of the children of Adam and Eve (which implies all of humanity) are thought to have a diminished relationship with God (instead of having a relationship like Adam, Eve, and God had before the disobedient behavior occurred). Within this context, the goal and responsibility of humankind is to employ free will, in the face of great suffering and struggles, to build our relationship with God back up to its highest potential.

I think that science, specifically evolution, can also weigh in on the topic of original sin. Although the context is different, I think the main ideas that come out of the religious perspectives on the idea of original sin are that we are not currently as good as we could be, and that the struggles we face in life are actually opportunities for our improvement. To me, this sounds strikingly similar to the idea of increasing biological complexity through natural selection. In the framework of evolution, individual organisms are more or less suited to the demands of their environment, and those environmental demands act as one mechanism to increase the fitness of a population of organisms over many generations. The major difference between the religious and evolutionary perspectives on original sin is the ability of the individual to reach the highest potential within its lifetime. Christianity claims this is possible (specifically through the acceptance of Jesus as the bearer of all sin). Evolution, however, rejects this possibility (specifically because the forces of natural selection act on populations across many generations).

So, I come back to my point on the distinction between religion and spirituality. I find that both share qualities - both address the highest realms of human consciousness and our relationship with others and our universe. However, religion implies that a person follows a specific set of rules in order to develop the spirit, while spirituality allows for a less dogmatic approach to personal development and self-actualization. A religious approach does not permit the dogma-breaking assumptions that evolution implies about the origins of life. However, a spiritual approach allows some relaxation in the interpretation of scripture, so that literal meaning is not quite as important as the larger message. And so, I suggest that the spiritualist can find great comfort by uniting the great messages from scripture and from evolution regarding the idea of imperfection. We can adopt some aspects of the religious approach, challenging ourselves to employ our free will in our struggles so that we can have the best relationship with divinity as is possible in this human form. We can also adopt some aspects of evolutionary theory, finding comfort in the knowledge that there is a natural mechanism in place for the improvement of the capacity of future generations to relate with the divine.

In the religious view, I find hope for myself, but little hope for future generations, knowing that in this model all individuals begin their relationship with spirituality at the same diminished level. In the evolutionary view, I find little hope for myself, but great hope for the ability of future generations to start their relationship with spirituality at a greater level than my own. With a spiritual view that combines aspects of religion and evolution, I find hope for myself and hope for the future.

Goodbye p-prim, I hardly knew ye...

Our "Cognitive Group" here at UMaine is starting a new model for our meetings, with meetings to be held approximately once-a-month this semester, and organized around a presentation by one of our members. We kicked things off this past Thursday, 26 January, with a presentation on "Big Ideas" by "X.Y.". (Note to self, and/or whomever else is reading - I should get permission from CogGroup members to post actual names here, yes?)

The topic of the presentation was, essentially, to map out the ... big ideas ... that we're attempting to deal with when we do educational research from the cognitive perspective. I suppose that I should point out that we're all doing educational research within the sciences - I'm the only member focusing on Biology, while the rest of the folks are focusing on Physics. However, the nature of the domain of our study was not at issue, but rather the "30,000 foot view" of doing research on learning. While we discussed a number of issues, one of the most interesting to me was the subject of cognitive resources.

We all seemed to agree that cognition - thinking - has components, shown in Figure 1 as "A", "B", and "C".
Figure 1 - Cognition Has Components

We also agree, although more generally, that the components of cognition process information that is of a (somewhat) limited domain (though boundaries can be "fuzzy"), and that these components are linked to one another. Furthermore, we also agreed that the links between components can be either excitatory or inhibitory, and are generally directional. In Figure 2, these links are illustrated. I use a convention where lines that end in pointed arrows indicate an excitatory link, and where lines that end in circles indicate an inhibitory link. So, in this graph of cognition (Fig. 2), component "A" excites component "B", which then excites component "C", which then inhibits component "A".
Figure 2 - Cognition Has Linked Components

We hit a bit of a bump in the road, though, as we begin to inspect the nature of the components of cognition. Existing literature (that we're familiar with...) would lead us to label these components of cognition as "resources". But yet, when I think about the resources that are necessary for the concept of evolution, I realize that those resources are in fact concepts. Interviews with other high school biology teachers confirms this notion. To paraphrase (*not* an exact quote, but close): "For students to understand the concept of evolution, they have to have a really good concept of genetics."

So, it seems pretty clear that there is some type of nesting that is happening with concepts and resources, such that a resource for one "big" concept (say, a big one like evolution in biology, or maybe quantum in physics) is a concept of its own. Now we can question whether this is a contextual effect - are we defining concepts *only* within a performance framework? Or is this a question on the nature of cognition - are some resources so tightly and stably linked that they form concepts that can act as resources for other, larger-domain concepts?

Furthermore, we realized during the presentation that some of us think of resources as components of cognition that can't be "unpacked" by the user - essentially highlighting the poor distinction between a resource and a "primitive" (such as diSessa's phenomenological primitives). Primitives tend to be described as highly automated, intuitive, and shallow processing components for cognition - a classic example is "closer means stronger", as in, "the closer I am to the fire, the hotter it feels." The models that we develop regarding thinking and learning will be affected by our interpretation of the components of cognition - if resources can only be primitive, then it will be very difficult for me to use the coordination class to describe the concept of evolution. However, if resources are sometimes primitive but sometimes concepts, we have to be much more specific about the actual nature of a resource, because the implication would be that all components of cognition are resources - which we then "tag" with classifiers such as "primitive" or "concept".

My feeling, which again is highly influenced by my own experience in teaching evolution to high school students, and from interviewing other high school teachers, is that all components of thinking are resources. Some resources are actually resourceful, and other resources are not - sometimes primitive resources are resourceful, and sometimes they are not. There are times when concept resources are resourceful, and there are other times when certain concepts are inappropriately incorporated into another, larger concept. I suspect that part of the resistence of some to think of primitives and resources as the same thing has to do with wanting the structure of a concept to be more complex than the structure of a resource. It here, in this debate, that I think the themes of biology can be applied to cognitive educational research in a way that significantly enriches the field.

In the biological domain, we inspect systems in two ways that are different but related: we look at both form and function. For example, biologists are concerned about the shape of DNA. Biologists are also concerned about the function of DNA. And to make things even more difficult, we look for an internally consistent relationship between form and function - the double helix shape of DNA help us to explain the process of DNA replication that allows heredity information to be passed on to another generation of organisms. Sometimes researchers know the form of a system before they understand the function, and sometimes it's the other way around. But in all cases, biologists seek a consistent and mutually beneficial relationship between the two. In cognition, we're limited because we are still learning about the form of thinking (and, in fact, the form of the brain), and we are still learning about the function and functional relationships between the structural components of thinking (and, in fact, the function and functional relationships of and within the brain). These are murky waters, indeed.

Our debate about the nature of primitive vs. resource vs. concept really illuminates our lack of specificity in our classifiers for the components of cognition - are we talking about form or function? And are our models for cognition inhibiting the relationship between form and function? We're also not being clear about the timescales that we're concerned about when we classify the components of thinking - and our intent has a lot to do with selecting the timescale that is relevent for our inquiry. If we're trying to explain thinking in-the-moment, we're likely to identify all active components of thinking as resources (regardless of utility in the form or function of an expert-level concept). If we're trying to explain student development of a concept across multiple instructional events, we're likely to disregard the spontaneously activated components (or, if we account for them, identify them as primitives) and identify components based on their formal and/or functional similarity to expert concepts.

So, what's a cognitive resource? My argument is that it's any active nerve or neural network that processes a limited domain of information in any instant of cognition. And then, what's a concept? My argument is that it's any group of linked cognitive resources in any instant of cognition. It is only in this model that I find satisfactory resolution of the pressures of related form and function, as well as describing knowledge (what is known in a particular instant in a particular context) and learning (developing concepts by changing the patterns of activation of resources and altering the relationships between those resources).

Finally, what's a p-prim? Well, it's a simple way of classifying the utility of a particular component of cognition - it is only a functional description, not a formal one (to say that the structure of "closer means stronger" or "dying away" is primitive indicates a primitive understanding of the brain and overlooks the necessity that even these processing elements have a complex internal mechanism). As such, I bid p-prims farewell, and choose to focus only on resources and concepts, because they can be analyzed both in form and in function.

Meet my good friend, Cognitive Neuroscience

I attended a lecture from Herb J. Weingartner yesterday afternoon here at UMaine. The title of the lecture was "Cognitive Neuroscience and Education". Unfortunately I had to leave as soon as the presentation finished, and could not stay for the question and answer period that followed. However, the content of the presentation served a great function - it reminded me about how important I think it is to make sure that conceptual models follow the general principles of what we know about the brain.

One of the slides in the presentation could have been a basic map of my vision of the refined coordination class model for concepts. Of course, the labels were different, but the essential features were there: a read-out of information from the environment by the sensory apparatus, a complex processing network that analyzed and interpreted the information presented by the sensory apparatus, and an output from that complex network that was some sort of externally-observable (objective...?) behavior.

But you, reader, might know enough about the original coordination class model to say: hey, why revise? That sounds just like what diSessa and Sheren were talking about: read-out, causal net, and another read-out. Well, yes, but there was another part of Weingartner's diagram that I haven't mentioned yet -- a SECOND input of information into the causal network. That input, I suspect, is incredibly important in order for teachers and other educational researchers to understand the pseudo-random interjections and explanations that students exhibit in using concepts. The second input to the causal network comes from the activity of other nerves within the brain that may or may not be a stable component of the concept.

Various neuroscience experiments have shown that neurons don't just fire when stimulated by another neuron. At least some nerve cells, in various parts of the brain, fire spontaneously - independent of any external stimulus. Some of these spontaneously firing nerve cells act as oscillators, firing with regularity over variable temporal intervals. Within this set of neural oscillators, the degree of regularity is variable, and context-sensitive. In 1998, Prut et. al. published "Spatiotemporal Structure of Cortical Activity: Properties and Behavioral Relevance", which describes some ways in which neurons act in networks that can be related to specific behavior. The authors describe the complexity of neural networks, showing that single neurons can participate in multiple networks through variability in activation in time (a reinforcement of the notion that neural networks exhibit scale-free properties). Furthermore, the authors demonstrate that behavior is highly correlated with the temporal qualities of neural network activation, and not only with external stimulus. In essence, this research highlights the role of spontaneous neural activity in animal behavior. The reading list provided by the authors' citations is comprehensive and provides further sources for information on spontaneous neural activity.

There are multiple consequences from this neuroscience research to the development of cognitive models for concepts. Behavior is certainly linked to external stimulus, and neural activity is coordinated by that external stimulus. This supports the notion that concepts are constructed on-the-fly with a strong degree of context sensitivity. However, the research also demonstrates that there are some components of a particular conceptual construction at a particular instant in time that are not necessarily a stable component of that concept, or that are directly linked to the external environment of the learner. At this point I think it is possible to make a claim that is not yet a part of the knowledge-in-pieces, resources-based models for concepts: we really can think of cognitive resources as activated single nerves or activated networks of nerves. Furthermore, educational researchers should expand the possible behaviors of resources to include the possibility of spontaneous activation that may have significant variability in the regularity of activation.

So, the long and the short of this boils down to the following. Sometimes a student's concept is going to include resources that are not involved in expert concepts and that are not intended to be activated by the teacher when creating the learning context.

Coordination Class Concepts and Scale-Free Networks

Ok ... so I just dumped my first post in as a copy and paste and haven't gone back to edit formatting - I'll get there.

Yet another aspect of the coordination class model for concepts that I like is that it exhibits scale-free properties. One of the central ideas of the coordination class is that the 'causal network' - the aspect of a concept that processes information that is read out from the environment - has components known as "resources". Essentially, this means that the coordination class model follows a "knowledge in pieces" philosophy, in which concepts are constructed of finer-grained cognitive units that tend to be naive and intuitive. Resources can come in a number of flavors - diSessa's phenomenological primitives, Minstrel's facets, and Tuminaro's epistemic frames. It seems reasonable, though, that the resources for some concepts may in fact be reasonably judged as concepts into and of themselves. Of course, evolution jumps out as a prime applicaiton for this idea, since the fully developed concept involves genetics, natural selection, homology, and a multitude of other knowledge that is finer-grained than the concept of evolution, but traditionally thought of as concepts themselves.

So why is this a good thing?

The idea for this refined model of the coordination class, and the application of the concept of evolution, is to develop a model for concepts that shows phenomenological overlap with the supporting layers from which it develops. I think of concepts as properties of the mind, which is itself an emergent property arising from the brain. Neuroscientific research has demonstrated that neural networks demonstrate scale-free properties (it's late for me right now and I'm feeling a tad lazy to do the fancy links...). Additionally, remembering that nerves are cells, researchers are also beginning to find that biochemical pathways that give rise to the emergent properties of cellular function also demonstrate scale-free properties. So, although we can hand-wave and reliably claim that mental objects - concepts - are emergent properties that can escape the limitations of the components from which they arise, I find it easier to support a model for concepts that does show some degree of overlap in properties - patterns - with its foundation. So, just as the scale-free networks of biochemical pathways can give rise to cellular-level properties, and scale-free networks of cells can give rise to mental properties, so can scale-free networks of cognitive resources give rise to concepts.

Of course, it's also interesting the the phenomenon of evolution itself seems to be scale free (in that it does not appear to be a pattern of relationships that is limited only to the biosphere). But more on that later.

The Coordination Class Model for Concepts

• The original coordination class model for concepts does:
o Define certain concepts at the levels of form and function
ß Allows researchers to study the “shape” and “components” of concepts
• We really like to build graphs – we can use this model to generate images(imagination!) of concepts so that we can think of them as actual things, as real objects
• This gives some justification to the concept v. misconception dichotomy a la McDermott / UW physics research – as in, if it looks like a duck … it’s a duck, and if it doesn’t look like a duck … it’s not a duck.
ß Allows researchers to study the performance of concepts
• We really like to experiment with new curriculum, and a great way to test the success of new teaching methods is to use pre- and post-tests that focus on a (relatively) limited amount of knowledge (one concept or a few related concepts)
• This gives some justification to pre- and post-test based research that indicates that dichotomous conceptual modeling doesn’t give us the whole story – there is a significant amount of “middle ground” between expert-level “CONCEPT” and novice-level “MISCONCEPTION”
o When modeling concepts as functions we can include context sensitivity as an influence on concept performance
ß Helps teachers to understand why students will provide different answers in different situations when the intent is to probe the same concept
ß Gives teachers a target for the learning process: how do we get students to recognize the same type of information in different situations? Developing and implementing curricula works best when there is a clear, understandable, and reachable goal (zone of proximal development applies even to teachers?). With that the student’s concept can perform stable read-outs of a particular “class” of information from their “causal networks” in environments that do not always provide the same quantity or quality of stimuli
o When modeling concepts as objects we can dissect concepts into discrete constituent parts
ß read-out from environment
ß causal network
ß read-out from causal network