In online learning, the most widely used model which outlines students’ learning experience is the community of inquiry (CoI) model. Central to the CoI model is the construct of cognitive presence, which focuses on students’ development of critical and deep thinking skills and is essential for the attainment of learning outcomes.
Given the latent nature of cognitive presence, there are significant challenges related to its assessment, which currently requires manual coding of online discussion transcripts or reliance on self-reported measures using survey instruments. In this paper, we present a novel model for assessing students’ development of cognitive presence using automated learning analytics techniques. Building on the foundations of evidence-centered design, we developed a flexible model for assessing students’ cognitive presence based on educational trace data that can be used in variety of learning contexts (e.g., traditional for-credit online courses, massive open online courses, and blended courses). We used the model to develop two analytics systems for real-time monitoring of cognitive presence development and for delivering valuable feedback for instructors, enabling them to use different instructional interventions during a course.