Putting the student in context : a social and normative model of learning approaches and their outcomes

Abstract

The focus of the current thesis is on developing and extending research on the role for social identification in the determination of learning approaches in tertiary students and the consequent outcomes. The social identity approach literature (Tajfel & Turner, 1986; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987) has practical and theoretical advances to offer here, in the form of a clear and practically applicable model of social influence. We apply this model of social influence processes to the tertiary education context across a variety of courses and disciplines, to explore how social influence might be embedded in the process of learning. This process of student learning in a tertiary context has been characterised (Biggs, 1989) as comprising three stages ("the 3 Ps"): Presage, Process and Product. The current thesis builds on this model in two ways. First, by taking into account the explicitly social nature of the learning process, exploring the normative and identity processes that have influence on learning. Second, we develop the original model by exploring explicit links between aspects of the presage (student attributes and aspects of the learning environment), differing processes (learning approaches) and several products of interest. A series of six studies explores social influence processes and normative processes over time in an educational context. Study 1 is undertaken in a PBL-based context, replicating a cross-lagged longitudinal model of social identity in education (Platow, Mavor, & Grace, 2013) wherein discipline-related social identification and deep learning approaches are in a dynamic, reciprocal relationship. Findings mirror the original paper and suggest the inclusion of a normative element in the model. Study 2 expands on this model, including perceived norms and both learning approaches. Both the cross-lagged model and a model drawing on the theory of planned behaviour, are tested. Findings indicate the value of including a normative component in the model and that deep learning behaviours are associated with higher grades. Study 3 then takes this model into a more traditional learning context and tests it across courses, disciplines and year-groups, while also accounting for personal and contextual influences. Findings indicate that discipline social identification, perceived norms and their interaction have influence on learning approaches, above and beyond presage factors. Study 4 accounts more explicitly for discipline variations and tests the identity-based normative-influence, using a clustered SEM model. Findings indicate that both deep and surface learning approaches are subject to identity-based normative influence and demonstrate impacts on several outcomes. Studies 5 and 6 draw these threads together, testing models in a dataset comprising both cross-sectional and longitudinal data. Overall, findings suggest that the ways in which students approach learning, evaluations of the course, intentions to continue and grades are all influenced by their social identification and the norms they perceive, as well as alignment between the two. These findings can inform ways in which tertiary courses are taught, such that the inclusion of activities to foster discipline identification and deep learning norms could positively influence student adoption of deep learning approaches, and, ultimately, academic outcomes. Show more