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Use of the Distributed Cognition Theory in a Lesson Plan: A Theory, a Model and a Lesson Plan

Year 2017, , 180 - 190, 07.12.2017
https://doi.org/10.17556/erziefd.341974

Abstract

Distributed
Cognition Theory (DCog) approaches the cognition holistically and argues that
knowledge come into existence not only inside the human mind but also in the
world. It is theoretically related to cognitive and social theories. Simply,
DCog takes information processing model into account and applies it to a
computational functional system. DCog theory is generally used in the field of
human-computer interaction (HCI) to find adequate answers to the design
questions of HCI. But, there are few studies inspired from DCog in educational
sciences. One of such studies is CTOM (connection, translation, off-loading,
and monitoring) framework proposed by Martin (2012) that regard learning as
“coordination” between systems in the natural settings. To increase the
coordination, all of the components of the framework need to be employed in a
learning setting. The framework also includes learning activities that can
increase the technology use in education. In this regard, the main purpose of
this study is to elaborate the use of Distributed Cognition (DCog) Theory and
accordingly the CTOM framework in a lesson plan. To do so, firstly theoretical
orientations of DCog was explained. Then, CTOM framework was criticized by
considering the pedagogical functions of DCog. Finally, a lesson plan was
prepared based on the CTOM framework according to Gagne’s nine events of
instruction. Consequently, the current study can be used in further empirical
studies to test the effectiveness of the model in terms of educational outcomes. 

References

  • Bandura, A. (1991). Self-regulation of motivation through anticipatory and self-reactive mechanisms. In R. A. Dienstbier (Ed.), Nebraska Symposium on Motivation, 1990 (Vol. 38, 69–164). Lincoln, NE: University of Nebraska Press.
  • Bloom, B.S. (1965). Taxonomy of Educational Objectives: The Classification of Educational Goals. New York: David McKay Company, Inc.
  • Driscoll, M.P. (2012). Psychological Foundations of Instructional Design. In Trends and Issues in Instructional Design and Technology. Pearson Education.
  • Gagné, R.M. (1985). The conditions of learning and theory of instruction (4th Ed.). New York: Holt, Rinehart and Winston.
  • Gardner, H. E. (1999). Multiple Approaches to Understanding. In C.M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory, Vol.2. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Harris, S. (2004). Distributed Cognition. Retrieved November 25, 2015, at: http://mcs.open.ac.uk/yr258/dist_cog/
  • Hutchins, E. (1995a). Cognition in the wild. Cambridge, MA: The MIT Press.
  • Hutchins, E. (1995b). How a cockpit remembers its speeds. Cognitive Science, 19, 265–288.
  • Kaput, J. J. (1992). Technology and mathematics education. In D. A. Grouws (Ed.), Handbook of teaching and learning mathematics (pp. 515–556). New York: Macmillan.
  • Martin, L. (2012). Connection, Translation, Off-Loading, and Monitoring: A Framework for Characterizing the Pedagogical Functions of Educational Technologies. Technology, Knowledge and Learning, 17(3), 87–107. doi:10.1007/s10758-012-9193-6
  • MEB, Talim Terbiye Kurulu Başkanlığı (2012) Ortaokul ve İmam Hatip Ortaokulu Bilişim Teknolojileri ve Yazılım Dersi Programı ve Kılavuzu, 5,6,7 ve 8. Sınıflar, Ankara.
  • Norman, D. A. (1993). Things That Make Us Smart. MA: Addison-Wesley.
  • OECD. (2012). How does class size vary around the world?. OECD Factbook 2012. Retrieved from SourceOECD database (http://www.oecd.org/edu/skills-beyond-school/EDIF%202012--N9%20FINAL.pdf).
  • Rogers, Y. (1997). “A Brief Introduction to Distributed Cognition,” Discussion paper, Interact Lab, School of Cognitive and Computing Sciences, University of Sussex.
  • Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.
  • Wenger, E. (1999). Communities of practice: Learning, meaning, and identity. Cambridge University Press.
  • Wenger, E., McDermott, R., & Snyder, WM (2002). Cultivating communities of practice: A guide to managing knowledge. Boston, MA: Harvard Business School Press.

Dağıtık Biliş Teorisinin Ders Planında Kullanımı: Teori, Model ve Ders Planı

Year 2017, , 180 - 190, 07.12.2017
https://doi.org/10.17556/erziefd.341974

Abstract




















Dağıtık
Biliş Teorisi, bilgi işlemeyi bütüncül olarak ele alır ve bilginin sadece insan
zihninde oluşmadığını, insanın çevresiyle etkileşiminden ortaya çıktığını
savunur. Teorik olarak bilişsel ve sosyal teoriler ile yakından ilişkilidir.
Basit bir ifadeyle, dağıtık biliş bilgi işlem modelinin, bireyin içeresinde
olduğu sosyal bir ortama uyarlanmasıdır. Genellikle, insan-bilgisayar
etkileşimi alanında tasarım sorularına doğru cevap bulmak için kullanılır. Fakat
eğitim bilimleri alanında dağıtık bilişle ilgili çalışmalara çok
rastlanılmamaktadır. Martin (2012) tarafından CTOM modeli adında teorinin
eğitime uyarlaması yapılmıştır. Bu modelde öğrenme, doğal ortamdaki iki
sistemin koordinasyonu olarak ele alınır. Bu koordinasyonun, dolayısıyla da
öğrenmenin artırılabilmesi için modeldeki bileşenlerin öğrenme ortamında
kullanılması gerekmektedir. Model aynı zamanda eğitimde teknoloji kullanımını
artırmaya yönelik aktiviteler de içerir. Bu bağlamda bu çalışmanın amacı
dağıtık biliş teorisi üzerinden CTOM modelinin ders planında kullanımını
incelemektir. Bunun için ilk olarak teorinin, teorik temelleri açıklandı.
Ardından CTOM modeli, dağıtık bilişin pedagojik işlevleri bakımından
değerlendirildi. Son olarak, CTOM modeli temel alınarak, Gagne’ nin dokuz
öğretim basamağı doğrultusunda bir ders planı hazırlandı. Bu çalışma ampirik
olmamakla birlikte, dağıtık bilişin ve CTOM modelinin eğitsel anlamda etkisinin
test edilebilmesi için yön gösterici niteliktedir.            

References

  • Bandura, A. (1991). Self-regulation of motivation through anticipatory and self-reactive mechanisms. In R. A. Dienstbier (Ed.), Nebraska Symposium on Motivation, 1990 (Vol. 38, 69–164). Lincoln, NE: University of Nebraska Press.
  • Bloom, B.S. (1965). Taxonomy of Educational Objectives: The Classification of Educational Goals. New York: David McKay Company, Inc.
  • Driscoll, M.P. (2012). Psychological Foundations of Instructional Design. In Trends and Issues in Instructional Design and Technology. Pearson Education.
  • Gagné, R.M. (1985). The conditions of learning and theory of instruction (4th Ed.). New York: Holt, Rinehart and Winston.
  • Gardner, H. E. (1999). Multiple Approaches to Understanding. In C.M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory, Vol.2. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Harris, S. (2004). Distributed Cognition. Retrieved November 25, 2015, at: http://mcs.open.ac.uk/yr258/dist_cog/
  • Hutchins, E. (1995a). Cognition in the wild. Cambridge, MA: The MIT Press.
  • Hutchins, E. (1995b). How a cockpit remembers its speeds. Cognitive Science, 19, 265–288.
  • Kaput, J. J. (1992). Technology and mathematics education. In D. A. Grouws (Ed.), Handbook of teaching and learning mathematics (pp. 515–556). New York: Macmillan.
  • Martin, L. (2012). Connection, Translation, Off-Loading, and Monitoring: A Framework for Characterizing the Pedagogical Functions of Educational Technologies. Technology, Knowledge and Learning, 17(3), 87–107. doi:10.1007/s10758-012-9193-6
  • MEB, Talim Terbiye Kurulu Başkanlığı (2012) Ortaokul ve İmam Hatip Ortaokulu Bilişim Teknolojileri ve Yazılım Dersi Programı ve Kılavuzu, 5,6,7 ve 8. Sınıflar, Ankara.
  • Norman, D. A. (1993). Things That Make Us Smart. MA: Addison-Wesley.
  • OECD. (2012). How does class size vary around the world?. OECD Factbook 2012. Retrieved from SourceOECD database (http://www.oecd.org/edu/skills-beyond-school/EDIF%202012--N9%20FINAL.pdf).
  • Rogers, Y. (1997). “A Brief Introduction to Distributed Cognition,” Discussion paper, Interact Lab, School of Cognitive and Computing Sciences, University of Sussex.
  • Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.
  • Wenger, E. (1999). Communities of practice: Learning, meaning, and identity. Cambridge University Press.
  • Wenger, E., McDermott, R., & Snyder, WM (2002). Cultivating communities of practice: A guide to managing knowledge. Boston, MA: Harvard Business School Press.
There are 17 citations in total.

Details

Journal Section In This Issue
Authors

Hamza Polat

Recep Öz

Publication Date December 7, 2017
Acceptance Date November 21, 2017
Published in Issue Year 2017

Cite

APA Polat, H., & Öz, R. (2017). Dağıtık Biliş Teorisinin Ders Planında Kullanımı: Teori, Model ve Ders Planı. Erzincan Üniversitesi Eğitim Fakültesi Dergisi, 19(3), 180-190. https://doi.org/10.17556/erziefd.341974