First Year Courses in IT: A Bloom Rating

Abstract

Introduction This paper builds on previous work by Oliver, Dobele, Greber and Roberts (2004a, 2004b) that examined the cognitive difficulty of two streams of three courses in an IT degree: a programming stream and a data communications and networking (DCN) stream. Both this study and the earlier study use Bloom's taxonomy as a measure of the cognitive difficulty of a (Bloom, 1956), which is summarized in Table 2. Its purpose is to provide a classification of the cognitive depth required to perform a given task. It is very widely known and has been used as a reference point in a number of publications in IT including the IS2002 curriculum guidelines (Gorgone, Davis, Valacich, Topi, Feinstein, & Longenecker, 2002) and in academic papers (Box, 2004; Burgess, 2005; Howard, Carver, & Lane, 1996; Lister, 2001; Lister & Leaney 2003; Reynolds & Fox, 1996; Sanders & Mueller, 2000; Scott, 2003). The application of Bloom's Taxonomy adopted in these studies is outlined in more detail in the next section. This study concerns the first year courses of an IT degree offered from our school. The presumption in our first study (Oliver et al., 2004a, 2004b), which we share with other writers as described in more detail subsequently, is that the Bloom rating of courses should progress from low ratings in the initial courses to higher levels in later year courses. Since this study is solely of first year courses, we expected that they would share similar Bloom ratings. As unfolded in our presentation of results later in the paper this expectation was not realized from our data. Possible reasons for why this was the case are explored at the end of the paper. The structure of the paper is as follows. Firstly, we classify and describe a number of prior studies in IT that use Bloom's taxonomy. We then describe how we analyse the data and compute the Bloom rating for a course. Following this we present some sample data from the courses analysed and describe how it was classified according to Bloom's taxonomy. We then present the results of our analysis and discuss their implications. Finally, we make some concluding remarks on the outcomes of the study. Applications of Bloom's Taxonomy As mentioned in the introduction, Bloom's taxonomy is used as a reference point in a number of studies of Information Technology (IT) education. Table 1 shows applications of Bloom's taxonomy extend over a broad range of educational contexts from setting assessments to curriculum guidelines. The Association of Information Systems curriculum guidelines (Gorgone et al., 2002), uses a modified form of the taxonomy to describe the depth of treatment required for different topics in a degree programme. They propose A topic may be covered at a low depth of knowledge level as part of an introductory and in more depth (higher competency) in a subsequent course (Gorgone et al., 2002). Reynolds and Fox, (1996) use Bloom's Taxonomy to specify the cognitive difficulty of different educational in subject areas within the ACM Curriculum '91 guidelines. Their intent is to highlight the differing cognitive demands of different topics to ensure that those with higher cognitive demands are given adequate exposure in the curriculum, as they hold the belief that objectives tend to concentrate at the lowest levels of mastery because they are the easiest ones to teach and test. Sanders and Mueller (2000) describe a curriculum design exercise for an entire degree based upon the principles of Bloom's taxonomy. Their proposal is consistent with that of Gorgone et al.(2002) in that they argue that courses in the early years of the programme should concentrate on achieving set at the lower end of Bloom's taxonomy, whereas those in the final years should be oriented towards skills development at the upper end of the scale. This assumption underpins the work we have done. In Oliver et al. …