Students acknowledge that deep assessment types improve engineering graduate attributes: Shallow learning still prevails

Abstract

BACKGROUND In response to the common goal of enhancing the overall skills of engineering graduates, a large body of literature relating to the study of student approaches to learning and assessment has developed. In a similar vein, there is also an area of research focussed on identifying and developing methods of improving graduate outcomes. Typically, previous studies have focussed on only one of these topic areas. This study analyses the interwoven link that connects all three aspects of student learning. PURPOSE This study presents one of the first attempts to link a students' approach to learning and assessment type preferences to Engineers Australia graduate attributes. Students also provided their perceptions on the extent to whether their approach to learning and assessment type preferences correlated to professional attributes such as their ability to communicate and their capacity for lifelong learning. Literature reviews on the beliefs of the engineering industry at large has reinforced the notion that strongly desired graduate attributes such as the capacity for innovative thinking is not being instilled within today's engineering graduate. This paper is part of an ongoing investigation into the design of new teaching and assessment methods designed to foster a deep-learning approach. Before this can be achieved, the hypothesised mismatch between many students' preference for recall type assessment and their acknowledgement that multi-faceted critical thinking types of assessment improve their graduate attributes needs to be empirically reconciled. DESIGN/METHOD Data was collected through a student survey of 132 second year civil engineering students. The questionnaire was comprised of five main sections: Part A collected basic student demographic information; Part B was designed to elicit the students' view on their own personal approach to learning; Parts C and D were structured in a similar way to collect the students' assessment preferences; and Part E was designed to elicit information about how students perceived the extent to which different assessment types are linked to the development of graduate attributes. Using Biggs' et al., (2001) Revised Study Process Questionnaire, students were first classified into one of two primary groups, namely, having either a Surface Learning Approach (SLA) or Deep Learning Approach (DLA). Students were also either classified as having a Surface Assessment Preference (SAP) and Deep Assessment Preference (DAP). Clustered groupings of students based on their SLA, DLA, SAP and DAP were mapped against students perceptions on how Surface Assessment Types (SAT) and Deep Assessment Types (DAT) contributed to Engineers Australia graduate attributes. RESULTS This paper examines the tripartite relationship between the approach to learning, assessment type preference and graduate outcomes. Results indicated that there is a mismatch between many students preference for SAT and their acknowledgement that the multi-faceted critical thinking DAT assessment (e.g. PBL) contributes to improved engineering graduate attributes. CONCLUSIONS The findings reveal that engineering students acknowledge that instilling deep learning skills is essential to be an effective engineering graduate that is embraced by industry. However, many second year engineering students still have a short-term focused preference for assessment that is highly defined. Furnishing empirical evidence on this mismatch is the first step to acknowledging this issue. The study indicates that Engineering Schools need to work with high schools to encourage deeper learning and continue to foster this style of learning at the outset of the engineering program to ensure that short-term goal orientated learning approaches do not become entrenched.