Araştırma Makalesi
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Students’ Reasoning Processes While Constructing Causal Diagrams

Yıl 2019, Cilt: 9 Sayı: 1, 13 - 35, 20.04.2019
https://doi.org/10.33403/rigeo.573464

Öz

The use of causal diagrams to externalize the mental representation of a problem is recognized to be an important step in solving complex problems. In geography education several global challenges taught about in class are highly complex due to the interconnectedness of many causes and consequences. A systems thinking approach might be helpful to better understand these global challenges. Former studies have shown the effectiveness of concept maps and causal diagrams to foster students’ systems thinking. However, it is not always obvious for students to construct proper causal diagrams. In order to optimize teaching strategies concerning these complex systems in geography education, this study analyzes students’ cognitive strategies while constructing a causal diagram. We used task-based think-aloud interviews to study their cognitive strategies. Four different cognitive strategies were observed. The different types of cognitive strategies all resulted in an acceptable constructed causal diagram by the students. The presented insights are explorative, but it reveals the thinking processes that are mostly tacit and therefore has the potential to contribute to better teaching strategies. After all, if we know what processes novices go through while carrying out a complex skill, which are often taken for granted by experts, in this case geography teachers, we can raise awareness among teachers to explicitly take those processes into account while designing lessons.

Kaynakça

  • Assaraf, O. B. Z., & Orion, N. (2005). Development of system thinking skills in the context of earth system education. Journal of Research in Science Teaching, 42(5), 518–560. https://doi.org/10.1002/tea.20061
  • Biggs, J. B., & Collis, K. F. (1982). Evaluating the quality of learning : the SOLO taxonomy (Structure of the observed learning outcome). New York: Academic Press.
  • Bruillard, E., & Baron, G.-L. (2000). Computer-based concept mapping: a review of a cognitive tool for students. Proceedings of Conference on Educational Uses of Information and Communication Technologies, (august), 331–338. https://doi.org/10.1.1.365.3379
  • Collins, A., Brown, J., & Newman, S. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematic. Knowing; Learning and Instruction: Essays in Honour of Robert Glaser, 453–494. https://doi.org/10.1017/CBO9781107415324.004
  • Collins, a., Brown, J. S., & Holum, A. (1991). Cognitive apprenticeship: making thinking visible. American Educator, 15(3), 6–11, 38–46.
  • Cox, M., Elen, J., & Steegen, A. (2017). Systems thinking in geography : Can high school students do it ? International Research in Geographical and Environmental Education, 0(0), 1–16. https://doi.org/10.1080/10382046.2017.1386413
  • Dogusoy-Taylan, B., & Cagiltay, K. (2014). Cognitive analysis of experts’ and novices’ concept mapping processes: An eye tracking study. Computers in Human Behavior, 36, 82–93. https://doi.org/10.1016/j.chb.2014.03.036
  • Dörner, D. (1986). Diagnostik der operativen Intelligenz [Assessment of operative intelligence]. Diagnostica, 32 (4), 290-308.
  • Ericsson, K. A. (2006). Protocol Analysis and Expert Thought : Concurrent Verbalizations of Thinking during Experts ’ Performance on Representative Tasks. In K. A. Ericsson, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge Handbook of expertise and expert performance (pp. 223–241). Cambridge: Cambridge University Press. https://doi.org/https://doi.org/10.1017/CBO9780511816796
  • Ericsson, K. A., & Simon, H. A. (1998). How to study thinking in everyday life: Contrasting think-aloud protocols with descriptions and explanations of thinking. Mind, Culture, and Activity, 5(3), 178–186. https://doi.org/10.1207/s15327884mca0503
  • Esters, I.G. & Ittenbach, R.F. (1999) Contemporary theories and assessments of intelligence: A primer. Professional School Counceling, 2(5), 373-376
  • Favier, T. T., & van der Schee, J. A. (2014). The effects of geography lessons with geospatial technologies on the development of high school students’ relational thinking. Computers and Education, 76, 225–236. https://doi.org/10.1016/j.compedu.2014.04.004
  • Fischer, A., Greiff, S., & Funke, J. (2012). The process of solving complex problems. The Journal of Problem Solving, 4(1), 19–42. https://doi.org/10.7771/1932-6246.1118
  • Forrester, J. W. (1994). System dynamics, systems thinking, and soft OR. System Dynamics Review, 10(2–3), 245–256. https://doi.org/10.1002/sdr.4260100211
  • Funke, J. (2001). Dynamic systems as tools for analysing human judgement. Thinking & Reasoning, 7(1), 69–89. https://doi.org/10.1080/13546780042000046
  • Funke, J. (2010). Complex problem solving: A case for complex cognition? Cognitive Processing, 11(2), 133–142. https://doi.org/10.1007/s10339-009-0345-0
  • Hmelo-Silver, C. E., Liu, L., Gray, S., & Jordan, R. (2015). Using representational tools to learn about complex systems: A tale of two classrooms. Journal of Research in Science Teaching, 52(1), 6–35. https://doi.org/10.1002/tea.21187
  • Hogan, K., & Thomas, D. (2001). Cognitive comparisons of students’ systems modeling in ecology. Journal of Science Education and Technology, 10(4), 319–345. https://doi.org/10.1023/A:1012243102249
  • Horn, K. L., & Cattell, R. B. (1966) Refinement and test of the theory of fluid and crystallized general intelligences. Journal of Educational Psychology, 57(5), 253-270 International Geographical Union. (2016). International charter on geographical education. Retrieved from http://www.igu-cge.org/wp-content/uploads/2018/02/IGU_2016_def.pdf
  • Jeong, A. (2014). Sequentially analyzing and modeling causal mapping processes that support causal understanding and systems thinking. In D. Ifenthaler & R. Hanewald (Eds.), Digital Knowledge Maps in Education: Technology-Enhanced Support for Teachers and Learners (pp. 239–251). New York: Springer. https://doi.org/10.1007/978-1-4614-3178-7_13
  • Jonassen, D. H. (2004). Learning to solve problems: An Instructional design guide. San Francisco: Pfeiffer.
  • Jonassen, D. H., & Henning, P. (1996). Mental models : Knowledge in the head and knowledge in the world. Technology, 39(3), 37–42. Retrieved from http://www.jstor.org/stable/44428530
  • Karkdijk, J., van der Schee, J. A., & Admiraal, W. F. (2018). Students’ geographical relational thinking when solving mysteries. International Research in Geographical and Environmental Education. https://doi.org/10.1080/10382046.2018.1426304
  • Kirschner, P. A. (2002). Cognitive load theory: implications of cognitive load theory on the design of learning. Learning and Instruction, 12(1), 1–10. https://doi.org/10.1016/S0959-4752(01)00014-7
  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310
  • Leat, D. (1998). Thinking through geography. Cambridge: Chris Kington Publishing.
  • Leat, D., & Nichols, A. (2000). Observing pupils’ mental strategies: Signposts for scaffolding. International Research in Geographical and Environmental Education, 9(1), 19–35. https://doi.org/10.1080/10382040008667627
  • Löhner, S., Van Joolingen, W. R., Savelsbergh, E. R., & Van Hout-Wolters, B. (2005). Students’ reasoning during modeling in an inquiry learning environment. Computers in Human Behavior, 21(3), 441–461. https://doi.org/10.1016/j.chb.2004.10.037
  • McAleese, R. (1994). A theoretical view on concept mapping. Research in Learning Technology, 2(1), 38–48. https://doi.org/10.3402/rlt.v2i1.9487
  • Ministerie van Onderwijs en Vorming. (2017). Sociale en technische wetenschappen - derde graad TSO. Retrieved March 15, 2018, Retrieved from https://www.onderwijskiezer.be/v2/secundair/sec_detail.php?detail=225&var=3GTSO
  • Neisser, U., Boodoo, G., Bouchard, T.J., Boykin, A.W., Brody, N., Halpern, D.F., Loehlin, J.C., Perloff, R., Sternberg, R.J. & Urbina, S. (1996) Intelligence: Knowns and unknowns. American Psychologist, 51(2), 77-101.
  • Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs: Prentice-Hall.
  • Novak, J. D., & Cañas, a J. (2008). The theory underlying concept maps and how to construct and use them. IHMC CmapTools. https://doi.org/Technical Report IHMC CmapTools 2006-01 Rev 2008-01
  • Öllinger, M., Hammon, S., von Grundherr, M., & Funke, J. (2015). Does visualization enhance complex problem solving? The effect of causal mapping on performance in the computer-based microworld Tailorshop. Educational Technology Research and Development, 63(4), 621–637. https://doi.org/10.1007/s11423-015-9393-6
  • Senge, P. (1990). The Fifth Discipline. The art and practice of the learning organization. New York: Currency Doubieday. Retrieved from http://www.wz.uw.edu.pl/pracownicyFiles/id10926-the-fifth-discipline.pdf
  • Shin, N., Jonassen, D. H., & McGee, S. (2003). Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching, 40(1), 6–33. https://doi.org/10.1002/tea.10058
  • Sins, P. H. M., Savelsbergh, E. R., & van Joolingen, W. R. (2005). The difficult process of scientific modelling: An analysis of novices’ reasoning during computer-based modelling. International Journal of Science Education, 27(14), 1695–1721. https://doi.org/10.1080/09500690500206408
  • Stratford, S. J., Krajcik, J., & Soloway, E. (1998). Secondary students’ dynamic modeling processes: analyzing, reasoning about, synthesizing, and testing models of stream ecosystems. Journal of Science Education Technology, 7(3), 215–234. https://doi.org/10.1023/A:1021840407112
  • Van Merriënboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review (Vol. 17). https://doi.org/10.1007/s10648-005-3951-0
  • Weinstein, C. F., & Mayer, R. F. (1986). The teaching of learning strategies. In M. C. Wittrock (Ed.), Handbook of Research on Teaching (Third edit, pp. 315–327). New York: Macmillan Publishing Company.
  • White, B. Y., Shimoda, T. A., & Frederiksen, J. R. (1999). Enabling students to construct theories of collaborative inquiry and reflective learning: Computer support for metacognitive development. International Journal of Artificial Intelligence in Education (IJAIED), 10(2), 151–182. https://doi.org/citeulike-article-id:4046742
Yıl 2019, Cilt: 9 Sayı: 1, 13 - 35, 20.04.2019
https://doi.org/10.33403/rigeo.573464

Öz

Kaynakça

  • Assaraf, O. B. Z., & Orion, N. (2005). Development of system thinking skills in the context of earth system education. Journal of Research in Science Teaching, 42(5), 518–560. https://doi.org/10.1002/tea.20061
  • Biggs, J. B., & Collis, K. F. (1982). Evaluating the quality of learning : the SOLO taxonomy (Structure of the observed learning outcome). New York: Academic Press.
  • Bruillard, E., & Baron, G.-L. (2000). Computer-based concept mapping: a review of a cognitive tool for students. Proceedings of Conference on Educational Uses of Information and Communication Technologies, (august), 331–338. https://doi.org/10.1.1.365.3379
  • Collins, A., Brown, J., & Newman, S. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematic. Knowing; Learning and Instruction: Essays in Honour of Robert Glaser, 453–494. https://doi.org/10.1017/CBO9781107415324.004
  • Collins, a., Brown, J. S., & Holum, A. (1991). Cognitive apprenticeship: making thinking visible. American Educator, 15(3), 6–11, 38–46.
  • Cox, M., Elen, J., & Steegen, A. (2017). Systems thinking in geography : Can high school students do it ? International Research in Geographical and Environmental Education, 0(0), 1–16. https://doi.org/10.1080/10382046.2017.1386413
  • Dogusoy-Taylan, B., & Cagiltay, K. (2014). Cognitive analysis of experts’ and novices’ concept mapping processes: An eye tracking study. Computers in Human Behavior, 36, 82–93. https://doi.org/10.1016/j.chb.2014.03.036
  • Dörner, D. (1986). Diagnostik der operativen Intelligenz [Assessment of operative intelligence]. Diagnostica, 32 (4), 290-308.
  • Ericsson, K. A. (2006). Protocol Analysis and Expert Thought : Concurrent Verbalizations of Thinking during Experts ’ Performance on Representative Tasks. In K. A. Ericsson, N. Charness, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge Handbook of expertise and expert performance (pp. 223–241). Cambridge: Cambridge University Press. https://doi.org/https://doi.org/10.1017/CBO9780511816796
  • Ericsson, K. A., & Simon, H. A. (1998). How to study thinking in everyday life: Contrasting think-aloud protocols with descriptions and explanations of thinking. Mind, Culture, and Activity, 5(3), 178–186. https://doi.org/10.1207/s15327884mca0503
  • Esters, I.G. & Ittenbach, R.F. (1999) Contemporary theories and assessments of intelligence: A primer. Professional School Counceling, 2(5), 373-376
  • Favier, T. T., & van der Schee, J. A. (2014). The effects of geography lessons with geospatial technologies on the development of high school students’ relational thinking. Computers and Education, 76, 225–236. https://doi.org/10.1016/j.compedu.2014.04.004
  • Fischer, A., Greiff, S., & Funke, J. (2012). The process of solving complex problems. The Journal of Problem Solving, 4(1), 19–42. https://doi.org/10.7771/1932-6246.1118
  • Forrester, J. W. (1994). System dynamics, systems thinking, and soft OR. System Dynamics Review, 10(2–3), 245–256. https://doi.org/10.1002/sdr.4260100211
  • Funke, J. (2001). Dynamic systems as tools for analysing human judgement. Thinking & Reasoning, 7(1), 69–89. https://doi.org/10.1080/13546780042000046
  • Funke, J. (2010). Complex problem solving: A case for complex cognition? Cognitive Processing, 11(2), 133–142. https://doi.org/10.1007/s10339-009-0345-0
  • Hmelo-Silver, C. E., Liu, L., Gray, S., & Jordan, R. (2015). Using representational tools to learn about complex systems: A tale of two classrooms. Journal of Research in Science Teaching, 52(1), 6–35. https://doi.org/10.1002/tea.21187
  • Hogan, K., & Thomas, D. (2001). Cognitive comparisons of students’ systems modeling in ecology. Journal of Science Education and Technology, 10(4), 319–345. https://doi.org/10.1023/A:1012243102249
  • Horn, K. L., & Cattell, R. B. (1966) Refinement and test of the theory of fluid and crystallized general intelligences. Journal of Educational Psychology, 57(5), 253-270 International Geographical Union. (2016). International charter on geographical education. Retrieved from http://www.igu-cge.org/wp-content/uploads/2018/02/IGU_2016_def.pdf
  • Jeong, A. (2014). Sequentially analyzing and modeling causal mapping processes that support causal understanding and systems thinking. In D. Ifenthaler & R. Hanewald (Eds.), Digital Knowledge Maps in Education: Technology-Enhanced Support for Teachers and Learners (pp. 239–251). New York: Springer. https://doi.org/10.1007/978-1-4614-3178-7_13
  • Jonassen, D. H. (2004). Learning to solve problems: An Instructional design guide. San Francisco: Pfeiffer.
  • Jonassen, D. H., & Henning, P. (1996). Mental models : Knowledge in the head and knowledge in the world. Technology, 39(3), 37–42. Retrieved from http://www.jstor.org/stable/44428530
  • Karkdijk, J., van der Schee, J. A., & Admiraal, W. F. (2018). Students’ geographical relational thinking when solving mysteries. International Research in Geographical and Environmental Education. https://doi.org/10.1080/10382046.2018.1426304
  • Kirschner, P. A. (2002). Cognitive load theory: implications of cognitive load theory on the design of learning. Learning and Instruction, 12(1), 1–10. https://doi.org/10.1016/S0959-4752(01)00014-7
  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310
  • Leat, D. (1998). Thinking through geography. Cambridge: Chris Kington Publishing.
  • Leat, D., & Nichols, A. (2000). Observing pupils’ mental strategies: Signposts for scaffolding. International Research in Geographical and Environmental Education, 9(1), 19–35. https://doi.org/10.1080/10382040008667627
  • Löhner, S., Van Joolingen, W. R., Savelsbergh, E. R., & Van Hout-Wolters, B. (2005). Students’ reasoning during modeling in an inquiry learning environment. Computers in Human Behavior, 21(3), 441–461. https://doi.org/10.1016/j.chb.2004.10.037
  • McAleese, R. (1994). A theoretical view on concept mapping. Research in Learning Technology, 2(1), 38–48. https://doi.org/10.3402/rlt.v2i1.9487
  • Ministerie van Onderwijs en Vorming. (2017). Sociale en technische wetenschappen - derde graad TSO. Retrieved March 15, 2018, Retrieved from https://www.onderwijskiezer.be/v2/secundair/sec_detail.php?detail=225&var=3GTSO
  • Neisser, U., Boodoo, G., Bouchard, T.J., Boykin, A.W., Brody, N., Halpern, D.F., Loehlin, J.C., Perloff, R., Sternberg, R.J. & Urbina, S. (1996) Intelligence: Knowns and unknowns. American Psychologist, 51(2), 77-101.
  • Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs: Prentice-Hall.
  • Novak, J. D., & Cañas, a J. (2008). The theory underlying concept maps and how to construct and use them. IHMC CmapTools. https://doi.org/Technical Report IHMC CmapTools 2006-01 Rev 2008-01
  • Öllinger, M., Hammon, S., von Grundherr, M., & Funke, J. (2015). Does visualization enhance complex problem solving? The effect of causal mapping on performance in the computer-based microworld Tailorshop. Educational Technology Research and Development, 63(4), 621–637. https://doi.org/10.1007/s11423-015-9393-6
  • Senge, P. (1990). The Fifth Discipline. The art and practice of the learning organization. New York: Currency Doubieday. Retrieved from http://www.wz.uw.edu.pl/pracownicyFiles/id10926-the-fifth-discipline.pdf
  • Shin, N., Jonassen, D. H., & McGee, S. (2003). Predictors of well-structured and ill-structured problem solving in an astronomy simulation. Journal of Research in Science Teaching, 40(1), 6–33. https://doi.org/10.1002/tea.10058
  • Sins, P. H. M., Savelsbergh, E. R., & van Joolingen, W. R. (2005). The difficult process of scientific modelling: An analysis of novices’ reasoning during computer-based modelling. International Journal of Science Education, 27(14), 1695–1721. https://doi.org/10.1080/09500690500206408
  • Stratford, S. J., Krajcik, J., & Soloway, E. (1998). Secondary students’ dynamic modeling processes: analyzing, reasoning about, synthesizing, and testing models of stream ecosystems. Journal of Science Education Technology, 7(3), 215–234. https://doi.org/10.1023/A:1021840407112
  • Van Merriënboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review (Vol. 17). https://doi.org/10.1007/s10648-005-3951-0
  • Weinstein, C. F., & Mayer, R. F. (1986). The teaching of learning strategies. In M. C. Wittrock (Ed.), Handbook of Research on Teaching (Third edit, pp. 315–327). New York: Macmillan Publishing Company.
  • White, B. Y., Shimoda, T. A., & Frederiksen, J. R. (1999). Enabling students to construct theories of collaborative inquiry and reflective learning: Computer support for metacognitive development. International Journal of Artificial Intelligence in Education (IJAIED), 10(2), 151–182. https://doi.org/citeulike-article-id:4046742
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Marjolein Cox 0000-0002-0805-7920

Jan Elen Bu kişi benim 0000-0003-1611-5075

An Steegen / Research Article Bu kişi benim 0000-0001-7011-2452

Yayımlanma Tarihi 20 Nisan 2019
Gönderilme Tarihi 21 Ağustos 2018
Yayımlandığı Sayı Yıl 2019 Cilt: 9 Sayı: 1

Kaynak Göster

APA Cox, M., Elen, J., & Steegen / Research Article, A. (2019). Students’ Reasoning Processes While Constructing Causal Diagrams. Review of International Geographical Education Online, 9(1), 13-35. https://doi.org/10.33403/rigeo.573464
AMA Cox M, Elen J, Steegen / Research Article A. Students’ Reasoning Processes While Constructing Causal Diagrams. Review of International Geographical Education Online. Nisan 2019;9(1):13-35. doi:10.33403/rigeo.573464
Chicago Cox, Marjolein, Jan Elen, ve An Steegen / Research Article. “Students’ Reasoning Processes While Constructing Causal Diagrams”. Review of International Geographical Education Online 9, sy. 1 (Nisan 2019): 13-35. https://doi.org/10.33403/rigeo.573464.
EndNote Cox M, Elen J, Steegen / Research Article A (01 Nisan 2019) Students’ Reasoning Processes While Constructing Causal Diagrams. Review of International Geographical Education Online 9 1 13–35.
IEEE M. Cox, J. Elen, ve A. Steegen / Research Article, “Students’ Reasoning Processes While Constructing Causal Diagrams”, Review of International Geographical Education Online, c. 9, sy. 1, ss. 13–35, 2019, doi: 10.33403/rigeo.573464.
ISNAD Cox, Marjolein vd. “Students’ Reasoning Processes While Constructing Causal Diagrams”. Review of International Geographical Education Online 9/1 (Nisan 2019), 13-35. https://doi.org/10.33403/rigeo.573464.
JAMA Cox M, Elen J, Steegen / Research Article A. Students’ Reasoning Processes While Constructing Causal Diagrams. Review of International Geographical Education Online. 2019;9:13–35.
MLA Cox, Marjolein vd. “Students’ Reasoning Processes While Constructing Causal Diagrams”. Review of International Geographical Education Online, c. 9, sy. 1, 2019, ss. 13-35, doi:10.33403/rigeo.573464.
Vancouver Cox M, Elen J, Steegen / Research Article A. Students’ Reasoning Processes While Constructing Causal Diagrams. Review of International Geographical Education Online. 2019;9(1):13-35.