Development of a Coding Framework for Cognitive Engagement Based on Online Asynchronous Discussion

Abstract

Online learning has broken the constraints of time and space, significantly enhancing the quality and accessibility of higher education. However, real-time monitoring and effective assessment of learners' cognitive engagement within online learning environments present a major challenge. Due to variations across different learning contexts, general cognitive engagement coding frameworks increasingly reveal limitations in applicability, underscoring the need to develop context-specific frameworks. Therefore, this study adopts a grounded theory approach, analyzing 180 asynchronous discussion entries from six courses on the Chinese University MOOC platform. Through bottom-up coding, a three-level indicator system was established. Subsequently, the Delphi method was employed for validation, and the Analytic Hierarchy Process (AHP) was applied to determine indicator weights. This resulted in a cognitive engagement evaluation indicator system encompassing two primary indicators, six secondary indicators, and seventeen tertiary indicators. The study also found that non-cognitive factors such as learners' emotions and behaviors significantly influence cognitive engagement, while the impact of interaction on cognitive engagement is somewhat reduced in online learning contexts compared to offline learning.