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In this paper, we put forward a theoretical framework for understanding data literacy in initial teacher education. We have come to understand that data literacy is non-linear, non-hierarchical, and requires pre-service teachers to be able to work with a range of data sources to respond to the complexities of a classroom. Knowledge, therefore, can be seen as interconnected rhizomes. These rhizomes grow and are retained or a pruned as a result of direct instruction and vicarious experiences. Three theories have been presented here that enable researchers to grasp the complexities of data literacy. These theories being Technological Pedagogical Content Knowledge (TPACK), Rhizomes of Knowledge, and Knowledge in Pieces. Through understanding that knowledge may be formed in interconnected rhizomes that are activated to complete a task, a potent standpoint is offered for understanding the dynamic nature of knowledge and knowledge development in pre-service teacher education.

Knowledge types in initial teacher education: a multi-dimensional approach to developing data literacy and data fluency