Page 162 - Getting the Picture Modeling and Simulation in Secondary Computer Science Education

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Chapter 7
with the recommendations for the assessment of modeling competence as such, put forward by Nicolaou & Constantinou (2014), when they suggest to formulate rubrics of students attainment level with regards to modeling competences.
The scientific value of our assessment instrument lies in the fact that is useful beyond the classroom — it can be employed as a research instrument when examining the students’ learning outcomes with respect to computational thinking. Furthermore, the attention our assessment instrument puts on the entire modeling cycle makes it more holistic than most of the other assessment instruments with narrower focus. Finally, next to other forms of validity, we explored one which is essential to the Dutch educational context — the discernment ability to expose the significant differences in the performance levels of the HAVO students compared to the VWO students.
7.2.4 Teachers’ PCK (RQ4)
In the second study (chapter 4), we portrayed computer science teachers’ initial pedagogical content knowledge (PCK) on modeling and simulation in order to answer our fourth research question: How can the teachers’ PCK of teaching Computational Science be portrayed in terms of the four elements of PCK? Additionally, we asked, What differential features of PCK can be used to identify patterns of individual PCK in terms of the four elements of PCK?
First, we characterized the teachers’ PCK and portrayed it in terms of the four components of PCK.
Concerning teachers’ knowledge about goals of objectives (M1) on teaching modeling, we found two types of learning objectives. First, there are conceptual objectives concerning the skills associated with CS subject matter, and second, there are motivational and practical objectives concerning transversal competences and understanding the benefits of models.
Concerning the teachers’ knowledge about students’ understanding (M2), we characterized it in terms of three issues. First, the prerequisite knowledge the students need to learn modeling and skills needed to make models. Second, the issues regarded as successful or contributing to success such as the relevance of the models, the students’ perception, technical aspect and interest. Third, the issues regarded as difficult or contributing to difficulties, such as variation among students in the class, students’ difficulties in understanding the nature of models, or with abstraction or formalization, and students’ approach to task at hand. Furthermore, we observed that some teachers do not know what to say about the successful or difficult issues.