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Time and Performance in Online Learning: Applying the Theoretical Perspective of Metacognition
Authors:Lin Zhao  Chen Ye
Abstract:Educational psychologists have found that metacognitive calibration predicts learning outcomes in self‐regulated learning. In this research the authors apply theories of metacognition from educational psychology and postulate that metacognitive calibration influences learning time and performance in online learning. Data gathered from 230 college students who completed online self‐regulated assignments in an introductory information systems course confirms that higher calibration accuracy leads to better performance on assignments, which contributes to higher exam grades. In addition, higher calibration accuracy also reduces the amount of time students spent on the online assignments. However, time spent on the assignments is not a mediator of the effect of calibration on learning performance. This research presents pioneering work in examining a holistic model that assesses the impact of metacognition in online learning on both assignment and exam level learning outcomes using field data collected through a natural learning setting. The findings highlight the need to include metacognitive calibration as one of the learner characteristics in research models addressing student performance in online learning.
Keywords:academic achievement  metacognition  online education  self‐assessment  self‐regulated learning
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