摘要：The objective of the present paper is to propose a refined conception (Ennis, 2016) of critical thinking in data-rich environments. The rationale for refining critical thinking stems from the need to identify specific information processes that direct the suspension of prior beliefs and activate broader interpretations of data. Established definitions, many of them originating in philosophy, do not include such processes. A refinement of critical thinking in the digital age is developed by integrating two of the most relevant areas of research for this purpose: First, Stanovich and Stanovich’s (2010) tripartite model of critical thinking is used to outline proactive and reactive information processes in data-rich environments. Second, Shavelson, Zlatkin-Troitschanskaia, Beck, Schmidt, and Marino’s (2019) assessment framework is used to illustrate how educational interventions and assessments can be used to incorporate processes outlined in the tripartite model, thus providing a defensible conceptual foundation for inferences about higher-level thinking in data-rich environments. Third, recommendations are provided for how a performance-based teaching and assessment module of critical thinking can be designed.
