Page 104 - Teaching and learning of interdisciplinary thinking in higher education in engineering

Chapter 5
5.4.3 Data analysis
The data analysis featured a content analysis which, in accordance with Hsieh and Shannon (2005, p. 1278), was considered as a research method for the subjective interpretation of the content of textual data. This content analysis involved the systematic categorization of the data, thereby enabling the identification of patterns. Two types of content analysis were performed: directed content analysis and conventional content analysis (Hsieh & Shannon, 2005). The goal of the directed content analysis approach was to validate and to conceptually extend the theoretical perspectives presented (see chapter 5.2). This analysis involved the use of predetermined codes derived from these theoretical perspectives. This analysis was done by the first author who coded all 150 reported challenges and all 60 reported knowledge connections. The codes with respect to the challenges were based on the three dimensions of Illeris (2002, 2007) and included the categories content-related challenge, incentive-related challenge, and interaction-related challenge. The codes with respect to the knowledge connections were based on the concepts of Luning and Marcelis (2007) and included the categories: fd–hd, referring to food dynamics and human dynamics, fd–ac, referring to food dynamics and administrative conditions, tc–hd, referring to technological conditions and human dynamics, and tc–ac, referring to technological conditions and administrative conditions.
After the directed content analysis, the conventional content analysis was conducted for each data set. For the data set on learning challenges, the goal of the
conventional content analysis was to identify the subcategories of challenges and the strategies. For the data set on knowledge connections, the goal was to identify the subcategories of justification given by the students. The inductive analysis method was kept as simple as possible and started with identifying similar kinds of expressions, clustering
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