Epistemic complexity: Difference between revisions

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* In Biology, {{quotation|Biological evolution is a progressing process of knowledge acquisition (cognition) and, correspondingly, of growth of complexity. The acquired knowledge represents epistemic complexity.}} (Kováč, 2007). Bailly and Longo (2003) provide a similar definition: {{quotation|{{quotation|By this notion we mean the global functions of a system, the external description of it as given by the knowing subject (thus "epistemic").}}.
* In Biology, {{quotation|Biological evolution is a progressing process of knowledge acquisition (cognition) and, correspondingly, of growth of complexity. The acquired knowledge represents epistemic complexity.}} (Kováč, 2007). Bailly and Longo (2003) provide a similar definition: {{quotation|{{quotation|By this notion we mean the global functions of a system, the external description of it as given by the knowing subject (thus "epistemic").}}.


* In artificial intelligence, epistemic complexity could be defined in terms of the {{quotation|complexity of the decision problem for epistemic logics}} (Vardi, 1989).
* In computer science and artificial intelligence, epistemic complexity could be defined in terms of the {{quotation|complexity of the decision problem for epistemic logics}} (Vardi, 1989) or computational incompressibility (Kolmogorov-Chaitin)


* In systems theory, {{quotation|Rescher (1998) distinguished three 'modes', namely
* In systems theory, {{quotation|Rescher (1998) distinguished three 'modes', namely epistemic, ontological and functional complexity. Among these modes of complexity, the epistemic embraces three categories: descriptive, generative and computational complexity}} (Schlindwein et al., 2004).
epistemic, ontological and functional complexity. Among these modes of complexity, the epistemic embraces three categories: descriptive, generative and computational complexity}} (Schlindwein et al., 2004).
 
* In constructivism, epistemic complexity could be related to epistemic fluency, i.e. be able to communicate across epistemic divides using different epistemic games. (Morrison and Collins, 2996). In a similar way, Bing and Redish (2011) argue that: {{quotation|First, experts have larger and better-organized banks of knowledge. Second, experts are better in-the-moment navigators during the problem solving process}}.  ''In-the-moment navigation'' happens between various epistemological framings such as warrants, epistemological resources, and epistemological framing.
 
See also: [[Creativity]]
 
== Measures and instruments ==
 
 
 
 
== Links ==
 
* [http://www.ricercaitaliana.it/prin/dettaglio_completo_prin_en-2006119809.htm Measures of epistemic complexity and knowledge construction]. The "genealogical" unfolding of the teleological and intentional roots of thought processes at the level of cultural evolution.  (Italien research project led by Arturo Carsetti)


* In constructivism, epistemic complexity could be related to epistemic fluency, i.e. be able to communicate across epistemic divides using different epistemic games. (Morrison and Collins, 2996).


== Bibliography ==
== Bibliography ==


* Bailly, Francis and Giuseppe Longo, (2003). Objective and Epistemic complexity in Biology, Invited lecture, International Conference on Theoretical Neurobiology, National Brain Research Centre, New Delhi, INDIA, February 2003. [ftp://ftp.di.ens.fr/pub/users/longo/CIM/obj-epi-complex.pdf PDF]
* Bailly, Francis and Giuseppe Longo, (2003). Objective and Epistemic complexity in Biology, Invited lecture, International Conference on Theoretical Neurobiology, National Brain Research Centre, New Delhi, INDIA, February 2003. [ftp://ftp.di.ens.fr/pub/users/longo/CIM/obj-epi-complex.pdf PDF]
* Bing, Thomas J. , Edward F. Redish (submitted, 2011). Epistemic Complexity and the Journeyman-Expert Transition, ''Physics Education'' [http://arxiv.org/abs/1103.3325v1 arXiv:1103.3325v1]
* Carsetti, A., “Epistemic Complexity and Knowledge Construction”.


* Chinn, C. A., & Malhotra, B. A. (2002). Epistemologically authentic reasoning in schools: A theoretical framework for evaluating inquiry tasks. Science Education, 86, 175–218.
* Chinn, C. A., & Malhotra, B. A. (2002). Epistemologically authentic reasoning in schools: A theoretical framework for evaluating inquiry tasks. Science Education, 86, 175–218.
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* Giovanni B. Moneta (1993), A model of scientists’ creative potential: The matching of cognitive structure and domain structure, ''Philosophical Psychology '' Volume 6, Issue 1. [http://dx.doi.org/10.1080/09515089308573075 DOI 10.1080/09515089308573075]
* Giovanni B. Moneta (1993), A model of scientists’ creative potential: The matching of cognitive structure and domain structure, ''Philosophical Psychology '' Volume 6, Issue 1. [http://dx.doi.org/10.1080/09515089308573075 DOI 10.1080/09515089308573075]
* Kolmogorov, N., (1968) "Logical Basis for Information Theory and Probability Theory",IEEE Trans.IT 14,5,pp.662-4.


* Lakkala, Minna (2010). How to design educational settings to promote collaborative inquiry: Pedagogical infrastructures for technology-enhanced progressive inquiry, Dissertation, Institute of Behavioural Sciences, University of Helsinki, Finland. [http://www.doria.fi/bitstream/handle/10024/59552/howtodes.pdf?sequence=2 PDF]
* Lakkala, Minna (2010). How to design educational settings to promote collaborative inquiry: Pedagogical infrastructures for technology-enhanced progressive inquiry, Dissertation, Institute of Behavioural Sciences, University of Helsinki, Finland. [http://www.doria.fi/bitstream/handle/10024/59552/howtodes.pdf?sequence=2 PDF]
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* Vardi, M.Y. (1989). On the complexity of epistemic reasoning, ''Fourth Annual Symposium on Logic in Computer Science, 1989. LICS '89, Proceedings, 243-252.
* Vardi, M.Y. (1989). On the complexity of epistemic reasoning, ''Fourth Annual Symposium on Logic in Computer Science, 1989. LICS '89, Proceedings, 243-252.




[[Category: learning theories]]
[[Category: learning theories]]
[[Category: Metacognition and learning strategies]]
[[Category: Metacognition and learning strategies]]

Revision as of 15:30, 17 January 2012

Draft

Definitions

The term epistemic complexity is used in several contexts. In various learning science, epistemic complexity often refers to the cognitive challenge of a task, in particular in constructivist whole task settings such as inquiry-based learning. (e.g. Lakkala, 2010). It is also used to describe the complexity of student productions.

  • In Biology, “Biological evolution is a progressing process of knowledge acquisition (cognition) and, correspondingly, of growth of complexity. The acquired knowledge represents epistemic complexity.” (Kováč, 2007). Bailly and Longo (2003) provide a similar definition: {{quotation|“By this notion we mean the global functions of a system, the external description of it as given by the knowing subject (thus "epistemic").”.
  • In computer science and artificial intelligence, epistemic complexity could be defined in terms of the “complexity of the decision problem for epistemic logics” (Vardi, 1989) or computational incompressibility (Kolmogorov-Chaitin)
  • In systems theory, “Rescher (1998) distinguished three 'modes', namely epistemic, ontological and functional complexity. Among these modes of complexity, the epistemic embraces three categories: descriptive, generative and computational complexity” (Schlindwein et al., 2004).
  • In constructivism, epistemic complexity could be related to epistemic fluency, i.e. be able to communicate across epistemic divides using different epistemic games. (Morrison and Collins, 2996). In a similar way, Bing and Redish (2011) argue that: “First, experts have larger and better-organized banks of knowledge. Second, experts are better in-the-moment navigators during the problem solving process”. In-the-moment navigation happens between various epistemological framings such as warrants, epistemological resources, and epistemological framing.

See also: Creativity

Measures and instruments

Links


Bibliography

  • Bailly, Francis and Giuseppe Longo, (2003). Objective and Epistemic complexity in Biology, Invited lecture, International Conference on Theoretical Neurobiology, National Brain Research Centre, New Delhi, INDIA, February 2003. PDF
  • Bing, Thomas J. , Edward F. Redish (submitted, 2011). Epistemic Complexity and the Journeyman-Expert Transition, Physics Education arXiv:1103.3325v1
  • Carsetti, A., “Epistemic Complexity and Knowledge Construction”.
  • Chinn, C. A., & Malhotra, B. A. (2002). Epistemologically authentic reasoning in schools: A theoretical framework for evaluating inquiry tasks. Science Education, 86, 175–218.
  • Kováč L. Fundamental principles of cognitive biology. Evolution and Cognition. 2000;6:51–69.
  • Giovanni B. Moneta (1993), A model of scientists’ creative potential: The matching of cognitive structure and domain structure, Philosophical Psychology Volume 6, Issue 1. DOI 10.1080/09515089308573075
  • Kolmogorov, N., (1968) "Logical Basis for Information Theory and Probability Theory",IEEE Trans.IT 14,5,pp.662-4.
  • Lakkala, Minna (2010). How to design educational settings to promote collaborative inquiry: Pedagogical infrastructures for technology-enhanced progressive inquiry, Dissertation, Institute of Behavioural Sciences, University of Helsinki, Finland. PDF
  • Morrison, D. and Allan Collins (1996), Epistemic Fluency and Constructivist Learning Environments, in Brent Gayle Wilson (ed.) Constructivist learning environments: case studies in instructional design, out of print. Google books
  • Schlindwein, Sandro Luis and Ison, Ray (2004). Human knowing and perceived complexity: implications for systems practice. Emergence: Complexity and Organization, 6(3), pp. 27–32. http://oro.open.ac.uk/58/
  • Rescher, N. (1998). Complexity A Philosophical Overview, New Brunswick: Transaction publishers.
  • Vardi, M.Y. (1989). On the complexity of epistemic reasoning, Fourth Annual Symposium on Logic in Computer Science, 1989. LICS '89, Proceedings, 243-252.