Joanne Mulligan|Russell Tytler|Vaughan Prain|Melinda Kirk
Implementing a pedagogical cycle to support data modelling and statistical reasoning in years 1 and 2 through the Interdisciplinary Mathematics and Science (IMS) project
Macquarie University|Deakin University|Deakin University|Deakin University
abstract paper illustrates years 1 2 students guided engage data modelling statistical reasoning interdisciplinary mathematics science investigations drawn australian 3year longitudinal study interdisciplinary mathematics science learning httpsimslearningorg project developed learning sequences 12 inquirybased investigations involving 35 teachers cohorts 25 70 students across years 1 6 research used designbased methodology develop implement refine 4stage pedagogical cycle based students problem posing data generation organisation interpretation reasoning data across stages ims cycle students generated increasingly sophisticated representations data made decisions whether supported explanations claims solutions scientific problems teachers role supporting students statistical reasoning analysed across two learning sequences ecology year 1 paper helicopters year 2 involving cohort students explicit focus data modelling metarepresentational practices enabled year 1 students form statistical ideas distribution sampling aggregation construct range data representations year 2 students engaged tasks focused ordering aggregating data measures central tendency inferential reasoning cases informal ideas variability study explores representationfocused interdisciplinary pedagogy support development data modelling statistical thinking early age