Session Information
03 SES 05.5 PS, General Poster Exhibition
General Poster Session during Lunch
Contribution
In recent years, social scientists have become increasingly interested in complexity theory to account for some distinctive qualities of social phenomena. Phenomena as diverse as altruism, wealth distribution, and social segregation have been modeled using complex algorithms (Jacobson, 2001, 2006; Jacobson & Wilensky, 2006). Complex systems have defining features that makes them different from other phenomena: multiple causes as opposed to single, direct causes; emergent processes versus circumscribed events; decentralized control versus centralized control; non-proportionality of effects versus proportionality of effects; and randomness of actions versus predictability of actions.
These features, some of which are rather counter-intuitive, have been proposed by educational and psychological researchers to account for the well-documented perseverance and robustness of student misconceptions in scientific domains (Jacobson & Wiliensky, 2006). For example, Chi (2005) has documented extensively the difficulty that novices experience to explain complex phenomena and how they tend to account for emerging phenomena through direct mental models. According to Levy and Wilensky (2004) the difficulty in understanding complex systems (in physics, biology and social fields) lies in the inability to relate phenomena on a micro level (agents) with phenomena observed at the macro level (aggregate). Yet, they have found that apprentices in familiar domains use their prior knowledge and build sublevels (mid-level) to understand aspects of dynamics of complex systems, reducing the amount of information and the number of agents needed to mentally manipulate the phenomenon and so generate plausible explanations of the functionality of the underlying complex system.
This study adds to the existing literature on the understanding of complex systems, by exploring differences between expert and novice explanations about the armed conflict and guerrilla warfare in Colombia, a complex social phenomenon that dates backs almost five decades ago and that despite its centrality in Colombia’s political everyday life is not yet included in school curricula. The student understanding and learning of historical processes and events has been subject of previous research (Carretero, Jaccott & Lopez-Majon, 2005; Hallden, 1994; Leinhardt & McCarthy-Young, 1996; Voss, Carretero, Kennet & Silfies, 1994; Wineburg, 1991, 1999). However, few studies have been conducted about traumatic events in recent history, which are part of collective memory (Carretero y Borrelli, 2010). In terms of learning and teaching strategies about how to explain history, this paper also innovates in the use of complexity theory as analytical framework to explain why historical phenomena as the guerrilla war is difficult to explain.
If we identify how people understand the complexity of war as a complex social phenomenon, we may be well-positioned to design learning environments that may facilitate the understanding of phenomena whose change is not produced by a single entity, but by the interaction and accumulation of many entities in time. In that respect, one of the biggest challenges for the educational system in the area of history in Colombia is to help citizens, children as well as adults, to develop a sophisticated understanding of an armed conflict that is unfortunately part of our everyday life.
Method
Expected Outcomes
References
Carretero, M. & Borrelli, M. (2010). La historia reciente en la escuela: propuestas para pensar históricamente. En Carretero, Mario, y Castorina, José A. (comps.) La construcción del conocimiento histórico. Enseñanza, narración e identidades. Buenos Aires:Paidós. Carretero, M. & Limón, M. (2005). Construcción del conocimiento y enseñanza de las ciencias sociales y la historia. En Mario Carretero (comp.) Construir y ensenar las ciencias sociales y la historia (4 Ed.). (pp. 33-62). Buenos Aires:Aique. Chi, M. T. H. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. Journal of the Learning Sciences, 14, 161–199. Hallden, O. (1994) On the paradox of understanding history in an educational setting. In G. Leinhardt, I.L. Beck, C. Stainton (Eds.), Teaching and learning in history (pp. 27-46). Hillsdale, NJ:Lawrence Erlabaum Associates, Inc. Jacobson, M. & Wilensky, U. (2006). Complex systems in education: Scientific and educational importance and implications for the learning sciences. Journal of the Learning Sciences,15(1),11-34. Leinhardt, G., & McCarthy-Young, K. (1996). Two texts, three readers: Distance and expertise in reading history. Cognition and Instruction 14(4),441-486. Voss, J.F., Carretero, M., Kenner, J., & Silfies, L.N. (1994). The collapse of the Soviet Union: A case study in causal reasoning. In M. Carretero & 1.F. Voss (Eds.), Cognitive and Instructional Processes in History and the Social Sciences (pp. 403-429). Hillsdale, NJ:Erlbaum. Levy, S. & Wilensky, U. (2008). Inventing a “Mid-Level” to Make Ends Meet: Reasoning between the Levels of Complexity. Cognition and Instruction, 26,1–47. Wineburg, S. S. 1999. Historical thinking and other unnatural acts. Phi Delta Kappan 80 (7).488-499. Wineburg, S.S. (1991). Historical problem solving: A study of the cognitive processes used in the evaluation of documentary and pictorial evidence. Journal of Educational Psychology, 83(1),73-87.
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