Learning, Data and Methodological Approaches – Qualitative, Quantitative or Mixed Methods Dilemmas? Educational outcomes, even at an individual learner level, are often now recorded or integrated through digital management systems, which collect increasing quantities and forms of background data. Arguments are made that these forms of data can be used to interpret features of use and of users that will inform better learning. Some previous research studies have explored learning features of the individual, using background data in qualitative ways (sometimes displaying outcomes through forms of imagery). Other previous studies have used much wider sets of data, gathered from across (sometimes very large) numbers of users; interpretations of those data are sometimes stated to say something about an individual’s learning from a statistical or quantitative perspective. Increasingly, mixed methods are argued as an important alternative. However, the length of study also needs to be considered as a critical associated dilemma. This talk explores these different paradigms and perspectives, arguing that dilemmas in the choice of methodological approach when studying technologies used for learning are not the only or necessarily the key dilemmas that researchers face if their research findings are to be of value to the field of education and learning. Different stakeholders – policy makers, educational advisers, head teachers or principals, teachers, parents, students, educational software developers – all need specific forms of data output if they are individually to be most effectively supported in terms of enhancing learning or teaching. A number of studies and their outcomes will be used to illustrate current and future implications and dilemmas we face in this field.