By Catherine Case, Christine Franklin, and Kaycie Maddox, University of Georgia
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In mathematics, Smith and Stein (1998) argue the most effective tasks are those that “engage students in high levels of cognitive thinking and reasoning,” and they use a four-tiered hierarchy to classify cognitive demand: memorization, procedures without connections, procedures with connections, and doing mathematics. This poster provides descriptions and examples prompting teachers to consider those tiers through a statistical lens. Further, the poster proposes an expansion of Smith and Stein’s classification system to include context – a feature inextricably linked to statistical reasoning. Although different cognitive levels and types of contexts are appropriate for different goals, students should have opportunities to complete investigations in “rich” contexts that are meaningful to students, invite interrogation of the data collection, promote multivariable thinking, and generate new investigative questions. Finally, this poster provides examples of quality lessons available through ASA’s online journal Statistics Teacher and solicits submissions of high-demand, rich-context lessons from USCOTS attendees.