Statistical literacy, reasoning, and thinking may be the most prominent objectives of statistics education; they are unsatisfactorily defined and demarcated. Therefore, they are difficult to monitor, and assess. As a consequence they are impractical as educational goals. Instead, assessment could be focused on those aspects of specific statistical knowledge that are indicative for different levels of understanding. Factual knowledge directly derived from sources of information indicates a superficial level of understanding; a comprehensive, coherent knowledge structure indicates a more profound level of understanding, and the ability to transfer knowledge (the ability to flexibly engage statistical knowledge in novel tasks) indicates an expert level of understanding. This classification of hierarchically related levels of statistical understanding may produce adequate ways of measurement and assessment.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education