A Novel Model of Cognitive Presence Assessment Using Automated Learning Analytics Methods.
One of the significant trends in educational is the increased interest in the development of students’ critical and deep thinking skills. Besides creativity, collaboration, and communication, critical thinking has been recognized as one of the core 21st-century skills necessary to work in the globalized economy. One of the widely used approaches for the development of critical thinking skills is inquiry-based learning, which — instead of presenting facts and information in a smooth learning path — begins with a question, problem, or scenario, and students build knowledge through interaction with the learning content and other students. In the context of online learning, the Community of Inquiry (CoI) model is a widely used pedagogical framework that outlines the constructs that shape students’ overall learning experience, including cognitive presence, which captures the development of students’ critical and deep thinking skills. Although cognitive presence has been recognized as important in student learning outcomes, assessing it is challenging, primarily because of its latent nature and the physical constraints of online learning settings. However, the vast amounts of data collected by the learning systems provide opportunities to assess student levels of cognitive presence through automated data analytics techniques, often referred to as learning analytics. In this presentation, we will overview a framework for the formative assessment of student cognitive presence based on learning analytics methods. Those include automatic analysis of student discussions and profiling of students based on their use of the available learning systems. With the goal of providing both instructors and students with timely and actionable feedback, the developed tools also enable to better understand the overall complexity of learning, thus advancing both the practice and theory of online learning.
Vitomir Kovanović is a Ph.D. student and research assistant at School of Informatics, University of Edinburgh, United Kingdom, and a research assistant at the Learning Innovation and Networked Knowledge Research Lab at the University of Texas, Arlington. Vitomir’s research is in the area of Learning Analytics and Educational Data Mining focuses on the development of novel learning analytics methods based on the trace data collected by learning management systems and their use to improve inquiry-based online education. He authored and co-authored several book chapters, conference papers, and journal articles. Vitomir is a recipient of two best paper awards (LAK15 and HERDSA15 conferences) and scholarships by the Serbian Ministry of Education, Simon Fraser University, and the University of Edinburgh.