Statistical thinking begins when young children collect, sort, classify and make meaning from tangible objects in their immediate environment (MacDonald, 2018). Therefore, it is argued that a strong foundation for using and representing data (data handling) will lead to stronger reasoning and thinking skills in older children (Makar, 2016). In the early years of mathematics education in Australia, there is a focus on patterning, estimation, data representation and handling during inquiry-based learning. By using the Zoo STEM Teach program as a stepping stone, we, as STEM teacher educators in an Australian university, explored how n=50 pre-service teachers (PSTs) were intentionally taught strategies for teaching statistics through real data. First, by collecting first-hand data through ethograms at the local zoo (Curran, 2016), and then followed back in the classroom, opportunities to visualise their results with loose parts to explain their findings. Our results revealed the process of collecting data was useful in capturing animal behaviours (the ethogram) using images or text, but some PSTs had difficulty categorising and representing this data informally, even once shown the process by their tutor. By using a content analysis of the student’s workbook and observations as photos taken by the tutor, we identified n=25 PSTs (50%) successfully summarised their learning experiences to communicate their understanding of the concepts being taught. The limitations are discussed for the next stage of this project on teaching early statistical skills and ways of working in STEM initial teacher education.