Page 110 - Getting the Picture Modeling and Simulation in Secondary Computer Science Education
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Chapter 5
With our format in mind, for the characterization of these SOLO categories we followed the local-to-global perspective. The first three levels describe quantitative progression. Prestructural indicates not answering the question at all or missing the point. Unistructural indicates fragmentary knowledge from a local perspective like mentioning only some of the relevant aspects — such as only a few agents or only some of their states — or missing important details. Multistructural indicates a more complete and coherent multi-point picture of the aspect under scrutiny — like listing all necessary agents and their states — but missing significant connections and without substantiating, clarifying, analyzing or explaining. These activities, however, are characteristic for the last two levels that add qualitative aspects: the relational level requires additionally the understanding of the relations among the parts of the aspect under scrutiny, such as recognizing all the actions an agent can perform, properly identifying conditions for these actions to occur and acknowledging their consequences. Finally, generalizing or theorizing — what if? — about aspects indicate going beyond what was given and typify the extended abstract level (Biggs & Tang, 2011; Meerbaum-Salant et al., 2013). In section 5.3.2, we elaborate the description of the SOLO levels for each criterium defining performance in detail.
5.3.1 Assignment
The assignment consists of a number of questions the students need to answer in writing while designing their model and using it to answer their research question, and of course, the task of implementing the model. After forming groups and choosing a case to model, the students answer the following questions:
Case and research question. Describe what you are going to model and with what purpose:
1. What do you know about this phenomenon? If need be, carry out the necessary research.
2. What part of your phenomenon would you like to build a model of?
3. What do you hope to observe from this model? (Questions 2 and 3
suggested by Wilensky and Rand (2015).)
Design the model. Design and describe the model following the questions
listed here. Report the considerations and choices you make. (E.g., “The sheep can reproduce. If two sheep meet, there is a chance of 20% that a new sheep will be breed. We decided not to take into account the gender of the sheep because that is not relevant in this case.”)























































































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