This mixed methods study investigates a number of aspects related to tool-use in undergraduate mathematics as seen from an Activity Theory perspective. The aims of this study include: identifying the tools that undergraduates use; seeking for an empirically-based typology of these tools; examining how undergraduates themselves can be profiled according to their tool-use; and finally identifying the factors influencing students tool preferences. By combining results from survey, interview and diary data analyses, it was found that undergraduates in the sample preferred using mostly tools related to their institution s practice (notes, textbooks, VLE), other students and online videos. All the tools students reported using were classified into five categories: peers; teachers; external online tools; the official textbook; and notes. Students in the sample were also classified into five distinct groups: those preferring interacting with peers when studying mathematics (peer-learning group); those favouring using online tools (online-learning group); those using all the tools available to them (blended-learning group); those using only textbooks (predominantly textbooks-learning group); and students using some of the tools available to them (selective-learning group). The main factor shaping students tool choices was found to be their exam-driven goals when examined from an individual s perspective or their institution s assessment related rules when adopting a wider perspective. Results of this study suggest that students blend their learning of mathematics by using a variety of tools and underlines that although undergraduates were found to be driven by exam-related goals, this is a result of the rules regulating how Higher Education Institutions (HEI) function and should not be attributed entirely as stemming from individuals practices. Assigning undergraduates exam- driven goals to their university s sociocultural environment, was made possible by combining two versions of Activity Theory (Leontiev and Engestrøm s) and analysing data at two different levels (individual and collective respectively).
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.