Maximal Dissipation and Least Information
One person told me I should write what my blog is about. Google defines a blog as “a regularly updated website or web page, typically one run by an individual or small group, that is written in an informal or conversational style”. One website says a blog is “A place to share your thoughts and your passions”. I started this blog to write about what I learnt in class. It is also a great way to recollect and make it your own, particularly for me because I am not a teacher.
In the following piece I use the term “learning” to mean “modification of behavior through practice, training or experience” and not the mere process of acquiring knowledge or skill. I am avoiding the use of the word “understanding” because of its very many connotations.
We studied very early in the program about learning domains and learning models. Some models are better suited for some learning domains and some others are not. Bloom’s taxonomy is used most often in an educational setting (M. Forehand, 2012). Dick and Carey Model is a systematic method to create instruction (Dick and Carey, 2001), whereas Merrill's model is about the nature of the instruction and how to it relates to learning (Merril, 2012). The former is about the instructional process which includes the learners, the instructor, the instructional materials and the learning environment. The latter is all about the instruction itself and is centered around the learner.
Howard Gardner wrote about there being at least seven distinct human intelligences (Gardner, 1983): linguistic, logical-mathematical, musical, spatial, bodily-kinesthetic, interpersonal, and intrapersonal. He pointed out that most standard measures are about testing linguistic and logical intelligence. An integral part of systematic design of instruction is choosing an instructional strategy. It is at this stage the learning domain is identified and a learning model chosen.
Merrill’s book states that by far the most common instructional problem is presenting information and calling it as an instruction (Merrill, 2012). The purpose of instruction is to make learning more effective, efficient and engaging (e^3). Way too much instruction exists today that does not provide examples to back the knowledge presented. They also do not provide the means for the student to apply the knowledge gained to solve a problem or do a new task.
Some recent trends in education are more play and less homework, linked learning (About Linked Learning | Linked Learning Alliance n.d.), blended learning (Blended Learning 2017), experiential education (What Is EE n.d.), connecting children with nature (Benefits of Connecting Children with Nature_InfoSheet.Pdf n.d.) and self organized learning environment (Self Organised Learning Environment 2017). All of them emulate more closely real life which necessarily means increased randomness and reduced structure. For who is it that wanting to evaluate or assess the learning and for what purpose? What is the evaluation and the assessment of the learning, to the learner?
Recently I came across some work that can provide some answers about the common thread among these recent trends. It started with Dr. Still’s work on information theoretic approach to interactive learning (Still_IL2009_EPL.Pdf n.d.). This is a machine learning perspective where the machine is controlled by an observer. In an information theoretic approach, learning is viewed as lossy compression of data. The basic assumption made is that the goal of the learner is to acquire as much predictive power as possible while keeping the world model and the action policy minimally complex (keeping energy consumption minimum).
Simon Dedeo writes, “While Still’s work connects nostalgia to dissipation and loss, England’s work (England, 2013) seems to say that life itself is brought into being by the demands of dissipation. Beings like us exist precisely because we create our worlds―physical, chemical, biological, mental, social―and tear them down faster than the alternatives. Nostalgia may be bittersweet, but it may also underwrite our existence.”
What I want to point out is that the recent trends in education, that more closely emulate real life, therefore, necessarily are about these worlds – physical, chemical, biological, mental, social – and their tearing down. This seems to suggest that, just like how particles tend to dissipate more energy when they resonate with a driving force (A New Thermodynamics Theory of the Origin of Life n.d.), the learner could be seen as maximizing dissipation and minimizing the information or the compressing of the data. “A great way of dissipating more is to make more copies of yourself”, says England. If we were to consider each one of these - physical, chemical, biological, mental, social – as being copies of each other for such purposes, then the recent trends in education have more of these copies than not. David Kaplan explains that increasing entropy could also drive random bits of matter into stable, orderly structures of life (Quanta Magazine n.d.).
This explains very well why Finland’s schools, with their emphasis on no homework and more play, have worked very well. This also explains very well why peer to peer learning is very effective, with its many copies of worlds. England said, “Many examples of dissipation driven adaptive organization could just be right under our nose, but because we haven’t been looking for them we haven’t noticed them.” Surely human learning fits this description? Surely we were not thinking of maximizing learning when we created the schools to produce factory workers, during the industrial revolution. So, should we be searching for ways for the school children to dissipate energy and clump that data the least, in other words maximal dissipation and least information? How do you measure maximal dissipation and least information? How do you build systems that foster and encourage maximal dissipation? Does such an optimal system or state also produce maximal learning?
Of course current schooling does not fit this description and so it would be erroneous to use its students for studying maximal dissipation, particularly at the high school and college level. Perhaps at the elementary school level, we could run a study with multiple groups of students, provide them with a bountiful environment (the light that shines, in David Kaplan’s words) and find out what energy they expended and for what structure (information and learning) they develop. Is energy expended the same or similar for the same information and learning? Should instruction be a part of this environment or would it cause a sub-optimal environment? Thinking back to the one time that I was a manager for a Destination Imagination team, the kids were coming up with so many wonderful ideas, some of them not practical or optimal and thrown aside. The ones thrown aside, are they part of the dissipation then? However, they were given specific objectives or problems to solve, which certainly influenced their process and so surely it is a sub optimal environment to begin with.
Some of the citations below were produced manually and some using Zotero software.
1. Mary Forehandv (o.J.) Bloom’s Taxonomy.- Georgia.
Web: http://projects.coe.uga.edu/epltt/index.php?title=Bloom%27s_Taxonomy (10.2.2012)
2. Gardner, H. (1983) Frames of mind: The theory of multiple intelligences. New York: Basic Books. New Editions: 1993, 2004.
3. Merrill, M. David, 2012. First Principles of Instruction: Identifying and Designing Effective, Efficient, and Engaging Instruction. Hoboken, NJ: Pfeiffer (John Wiley & Sons).
4. Dick, W., Carey, L., & Carey, J. (2001). The systematic design of instruction (5th ed.). New York: Addison, Wesley and Longman.
5. Still, S., Sivak, D.A., Bell, A.J., & Crooks, G.E. The thermodynamics of prediction. Physical Review Letters 109, 120604 (2012).
6. England, J.L. Statistical physics of self-replication. The Journal of Chemical Physics 139, 121923 (2013).
7. A New Thermodynamics Theory of the Origin of Life
N.d. Quanta Magazine. https://www.quantamagazine.org/a-new-thermodynamics-theory-of-the-origin-of-life-20140122/, accessed January 9, 2018.
8. About Linked Learning | Linked Learning Alliance N.d.
http://www.linkedlearning.org/en/about/, accessed January 9, 2018.
9. Benefits of Connecting Children with Nature_InfoSheet.Pdf, N.d. https://naturalearning.org/sites/default/files/Benefits%20of%20Connecting%20Children%20with%20Nature_InfoSheet.pdf, accessed January 9, 2018.
10. Blended Learning 2017
Wikipedia. https://en.wikipedia.org/w/index.php?title=Blended_learning&oldid=817216323, accessed January 9, 2018.
11. Quanta Magazine N.d.
How Does Life Come From Randomness? https://www.youtube.com/watch?v=k9QYtbjzjAw&feature=youtu.be, accessed January 9, 2018.
12. Self Organised Learning Environment 2017
Wikipedia. https://en.wikipedia.org/w/index.php?title=Self_Organised_Learning_Environment&oldid=798222681, accessed January 9, 2018.
13. Still_IL2009_EPL.Pdf N.d.
http://www2.hawaii.edu/~sstill/Still_IL2009_EPL.pdf, accessed January 9, 2018.
14. What Is EE N.d.
http://www.aee.org/what-is-ee, accessed January 9, 2018.
In the following piece I use the term “learning” to mean “modification of behavior through practice, training or experience” and not the mere process of acquiring knowledge or skill. I am avoiding the use of the word “understanding” because of its very many connotations.
We studied very early in the program about learning domains and learning models. Some models are better suited for some learning domains and some others are not. Bloom’s taxonomy is used most often in an educational setting (M. Forehand, 2012). Dick and Carey Model is a systematic method to create instruction (Dick and Carey, 2001), whereas Merrill's model is about the nature of the instruction and how to it relates to learning (Merril, 2012). The former is about the instructional process which includes the learners, the instructor, the instructional materials and the learning environment. The latter is all about the instruction itself and is centered around the learner.
Howard Gardner wrote about there being at least seven distinct human intelligences (Gardner, 1983): linguistic, logical-mathematical, musical, spatial, bodily-kinesthetic, interpersonal, and intrapersonal. He pointed out that most standard measures are about testing linguistic and logical intelligence. An integral part of systematic design of instruction is choosing an instructional strategy. It is at this stage the learning domain is identified and a learning model chosen.
Merrill’s book states that by far the most common instructional problem is presenting information and calling it as an instruction (Merrill, 2012). The purpose of instruction is to make learning more effective, efficient and engaging (e^3). Way too much instruction exists today that does not provide examples to back the knowledge presented. They also do not provide the means for the student to apply the knowledge gained to solve a problem or do a new task.
Some recent trends in education are more play and less homework, linked learning (About Linked Learning | Linked Learning Alliance n.d.), blended learning (Blended Learning 2017), experiential education (What Is EE n.d.), connecting children with nature (Benefits of Connecting Children with Nature_InfoSheet.Pdf n.d.) and self organized learning environment (Self Organised Learning Environment 2017). All of them emulate more closely real life which necessarily means increased randomness and reduced structure. For who is it that wanting to evaluate or assess the learning and for what purpose? What is the evaluation and the assessment of the learning, to the learner?
Recently I came across some work that can provide some answers about the common thread among these recent trends. It started with Dr. Still’s work on information theoretic approach to interactive learning (Still_IL2009_EPL.Pdf n.d.). This is a machine learning perspective where the machine is controlled by an observer. In an information theoretic approach, learning is viewed as lossy compression of data. The basic assumption made is that the goal of the learner is to acquire as much predictive power as possible while keeping the world model and the action policy minimally complex (keeping energy consumption minimum).
Simon Dedeo writes, “While Still’s work connects nostalgia to dissipation and loss, England’s work (England, 2013) seems to say that life itself is brought into being by the demands of dissipation. Beings like us exist precisely because we create our worlds―physical, chemical, biological, mental, social―and tear them down faster than the alternatives. Nostalgia may be bittersweet, but it may also underwrite our existence.”
What I want to point out is that the recent trends in education, that more closely emulate real life, therefore, necessarily are about these worlds – physical, chemical, biological, mental, social – and their tearing down. This seems to suggest that, just like how particles tend to dissipate more energy when they resonate with a driving force (A New Thermodynamics Theory of the Origin of Life n.d.), the learner could be seen as maximizing dissipation and minimizing the information or the compressing of the data. “A great way of dissipating more is to make more copies of yourself”, says England. If we were to consider each one of these - physical, chemical, biological, mental, social – as being copies of each other for such purposes, then the recent trends in education have more of these copies than not. David Kaplan explains that increasing entropy could also drive random bits of matter into stable, orderly structures of life (Quanta Magazine n.d.).
This explains very well why Finland’s schools, with their emphasis on no homework and more play, have worked very well. This also explains very well why peer to peer learning is very effective, with its many copies of worlds. England said, “Many examples of dissipation driven adaptive organization could just be right under our nose, but because we haven’t been looking for them we haven’t noticed them.” Surely human learning fits this description? Surely we were not thinking of maximizing learning when we created the schools to produce factory workers, during the industrial revolution. So, should we be searching for ways for the school children to dissipate energy and clump that data the least, in other words maximal dissipation and least information? How do you measure maximal dissipation and least information? How do you build systems that foster and encourage maximal dissipation? Does such an optimal system or state also produce maximal learning?
Of course current schooling does not fit this description and so it would be erroneous to use its students for studying maximal dissipation, particularly at the high school and college level. Perhaps at the elementary school level, we could run a study with multiple groups of students, provide them with a bountiful environment (the light that shines, in David Kaplan’s words) and find out what energy they expended and for what structure (information and learning) they develop. Is energy expended the same or similar for the same information and learning? Should instruction be a part of this environment or would it cause a sub-optimal environment? Thinking back to the one time that I was a manager for a Destination Imagination team, the kids were coming up with so many wonderful ideas, some of them not practical or optimal and thrown aside. The ones thrown aside, are they part of the dissipation then? However, they were given specific objectives or problems to solve, which certainly influenced their process and so surely it is a sub optimal environment to begin with.
Some of the citations below were produced manually and some using Zotero software.
1. Mary Forehandv (o.J.) Bloom’s Taxonomy.- Georgia.
Web: http://projects.coe.uga.edu/epltt/index.php?title=Bloom%27s_Taxonomy (10.2.2012)
2. Gardner, H. (1983) Frames of mind: The theory of multiple intelligences. New York: Basic Books. New Editions: 1993, 2004.
3. Merrill, M. David, 2012. First Principles of Instruction: Identifying and Designing Effective, Efficient, and Engaging Instruction. Hoboken, NJ: Pfeiffer (John Wiley & Sons).
4. Dick, W., Carey, L., & Carey, J. (2001). The systematic design of instruction (5th ed.). New York: Addison, Wesley and Longman.
5. Still, S., Sivak, D.A., Bell, A.J., & Crooks, G.E. The thermodynamics of prediction. Physical Review Letters 109, 120604 (2012).
6. England, J.L. Statistical physics of self-replication. The Journal of Chemical Physics 139, 121923 (2013).
7. A New Thermodynamics Theory of the Origin of Life
N.d. Quanta Magazine. https://www.quantamagazine.org/a-new-thermodynamics-theory-of-the-origin-of-life-20140122/, accessed January 9, 2018.
8. About Linked Learning | Linked Learning Alliance N.d.
http://www.linkedlearning.org/en/about/, accessed January 9, 2018.
9. Benefits of Connecting Children with Nature_InfoSheet.Pdf, N.d. https://naturalearning.org/sites/default/files/Benefits%20of%20Connecting%20Children%20with%20Nature_InfoSheet.pdf, accessed January 9, 2018.
10. Blended Learning 2017
Wikipedia. https://en.wikipedia.org/w/index.php?title=Blended_learning&oldid=817216323, accessed January 9, 2018.
11. Quanta Magazine N.d.
How Does Life Come From Randomness? https://www.youtube.com/watch?v=k9QYtbjzjAw&feature=youtu.be, accessed January 9, 2018.
12. Self Organised Learning Environment 2017
Wikipedia. https://en.wikipedia.org/w/index.php?title=Self_Organised_Learning_Environment&oldid=798222681, accessed January 9, 2018.
13. Still_IL2009_EPL.Pdf N.d.
http://www2.hawaii.edu/~sstill/Still_IL2009_EPL.pdf, accessed January 9, 2018.
14. What Is EE N.d.
http://www.aee.org/what-is-ee, accessed January 9, 2018.
Es realmente un blog útil para encontrar alguna fuente diferente para agregar mis conocimientos.
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Thank you, Hebe Adventures.
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