Linking engineering students’ assessment preferences to their learning approaches

The very nature of an Engineer implies that one has an inherent passion for investigation and problem solving. The secondary school system and to some extent the traditional university system is focused on teacher-centred learning; however, this approach does not ideally foster deep learning approaches, research-based learning (RBL) and teamwork that are vital attributes of any graduate engineer. Previous studies have confirmed that engineering students thrive and feel comfortable with traditional teacher-centred learning, which is focused on exams, and rote learning. These research studies instigated a strong resolve of many engineering educators to implement project/problem-based learning (PBL) approaches in program curriculum in order to enhance graduate outcomes. This study offers one of the first attempts to link engineering students’ approaches to learning with their assessment type preferences. The study empirically confirmed the proposition that deep learners also had a greater preference for deep assessment items and surface learners preferred surface assessment methods. Surface learners ranked both surface and deep assessment items on average lower than deep learners, indicating that surface learners do not have the same level of engagement in their learning through assessment in general. The paper concludes with some recommendations for engineering education policy and practice. Introduction A deep approach to learning is one of the foundations of being a lifelong learner (Baeten, et al., 2008), and as a consequence, there is no argument that the modern university graduate needs a deep learning approach to have the ability to succeed in the modern world (Kreber, 2003; Gijbels and Dochy, 2006; Male et al., 2010). The literature generally supports the broad hypothesis made herein by the authors; that students in general prefer surface type assessment (Birenbaum, 2007; Furnham, et al., 2008; Van de Watering, et al., 2008). Further, it also confirms that it is, in general, difficult to induce deep learning approaches into students (Baeten, et al., 2008). The engineering professional infers by its very nature, an innate, instilled and heightened deep assessment preference and approach to learning over and above other disciplines (Kreber, 2003; Leung, et al., 2008; Heller, et al., 2010). It has been noted recently that learning approaches can differ between the various disciplines (Birenbaum, 1997; Kyndt, et al., 2011). Remarkably little research has been undertaken on the learning approaches and assessment preferences of engineering students. Most of the published literature in this area focuses on the development of a new assessment method designed to encourage deep learning followed by an assessment on the relative efficacy in practice (Hargreaves, 1997; Nordstrom and Korpelainen, 2011). Very little research has in fact been undertaken on the study of the makeup of the engineering student psyche. It is the authors’ contention that a sound understanding of the learning orientation of the typical engineering student is required before assessment aimed at nurturing deep learning can be implemented. The focus of this paper is on a second year core subject being comprised of a variety of engineering disciplines.