Development of a higher-order instruction coding taxonomy for observational data: Initial application to professional driving instruction

Development of a higher-order instruction taxonomy, informed by best practice in driver education (Goals for Driver Education) and self-determination theory (guiding teaching strategies), was tested. Inter-coder reliability was assessed by coding 93 data elements from 5-min clips from three driving instructors. Seventy-three instruction and 32 teaching approach codes were selected. Reliability between two independent coders was high (IOC = 94.6%). Application to data from 17 randomly-selected, 1-h lessons (n = 3 driving instructors) in a pilot study of professional learner driver lessons assessed taxonomy validity. Missed, taken, and untaken opportunities for higher-order instruction via 9 instruction and 19 teaching-approach categories were identified. Reliability assessment and taxonomy application demonstrates evidence to facilitate a comprehensive understanding of driving instruction content and quality, with implications for assessing and evaluating the impact of higher-order instruction in relation to driving and other safety-critical sectors requiring higher-order skills.