Abstract:

Learning is an incredibly complex process. Learners come to education with a variety of attributes and preferences that influence that process. Video interviews were conducted with K-12 learners to highlight the differences in learner preferences. The interviewer asked each learner a similar set of questions about learning in general and their schooling experience. One purpose of the videos was for student teachers to appreciate learner differences before entering their practicum experiences. The researcher devised a data visualization approached called Diversity Maps to visualize the nature of learner responses. These maps are 3D models derived from learner responses and then visually constructed into a landscape representation. Diversity Maps may sensitize educators to individual differences, the fuzziness of the underlying data, and teaching and learning complexities. This paper will outline the development process of Diversity Maps and the results of using this to analyze a set of interviews with K-12 students. Much of the social sciences deal with ill-defined subjective data derived from making qualitative judgements. This paper suggests that there is value in creating forms of representation that reflect that variability and imprecision. The development of Diversity Maps was an experiment to give the viewer a sense of the landscape of individual differences. Ultimately, seeing Diversity Maps might make educators more reflective of their instruction, assessment, and differentiation practices by recognizing learners' differences. Future research into the Diversity Maps' effectiveness with intended audiences will determine the extent to which these assumptions are valid.

Keywords:

Individual Differences, Data Visualization, Visualization, 3D Modelling, Virtual Reality, Diversity.