Attitudes to concept maps as a teaching/learning activity in undergraduate health professional education: influence of preferred approach to learning

Abstract

Pre-prepared concept maps that organise knowledge in a non-linear fashion appeal to a variety of cognitive learning styles and may thus represent an educational tool that supports ‘teaching to all types’. However, another central cognitive factor, learning approach, may have a bearing on student take-up of this learning resource. Student attitudes to pre-prepared concept maps introduced in Stage 2 MPharm and BSc Pharmacology lectures were therefore examined in relation to the principal learning orientations according to Duff's 30-item revised approaches to study inventory (RASI). Approximately one half of students (49.6 ± 4.5%) reported pre-prepared concept maps to be useful to their learning (n = 121). When preferred learning approach was examined, derived from the highest RASI score per individual and excluding ties, 31.9 ± 4.3%, 29.3 ± 4.2% and 38.8 ± 4.5% of students demonstrated a preference for the deep approach (DA), strategic approach (STA) and surface approach (SUA), respectively (P > 0.05, χ2 goodness-of-fit test, n = 116). There was a weak but statistically significant association between preferred learning approach identified by Duff's 30-item RASI and the self-reported usefulness of concept maps (P < 0.05, χ2 test of independence; Cramer's V = 0.235; lambda = 0.193). In contrast, gender was not significantly associated with attitude to concept maps in this student cohort. A preliminary analysis of standardised residuals based on observed and expected frequencies revealed that the greatest contributions to this significant association were: a positive influence of DA and a negative influence of STA, respectively, on attitude to concept maps. These data now indicate a contribution of the principal learning orientations vis-à-vis student attitudes to pre-prepared concept maps when employed alongside more traditional teaching/learning activities in medical and biomedical science education, and may further suggest a role for concept maps in the support of deep learning.