| Sumario: | Using hidden Markov models (HMM), the current study looked at how learners' metacognitive monitoring is related to their physiological reactivity in the context of collaborative learning. The participants (N = 12, age 16–17 years, three females and nine males) in the study were high school students enrolled in an advanced physics course. The results show that during collaborative learning, the students engaged in monitoring in each self‐regulated learning phase such as task understanding, planning and goal setting, task enactment, adaptation and reflection. The results of the HMM indicated that the learners' physiological reactivity was low when monitoring occurred. The associations between the states based on the HMM provide insights not only into how learners engage in metacognitive monitoring but also about their level of physiological reactivity in each state. In conclusion, exploring aspects of metacognitive monitoring in collaborative learning can be done with the help of physiological reactions. Lay Description: What is already known about this topic: Metacognitive monitoring is an internal process which can be an indicator of learners' ability to recognize success or failure in collaboration.Metacognitive monitoring is difficult to capture, because it is internal process.Sometimes metacognitive monitoring activities are conducted without conscious effort. What this paper adds: Physiological data, such as Electrodermal Activity (EDA) is potential indicator about metacognitive monitoring.Hidden Markov Models have the ability to reveal latent states of how monitoring events are reflected in physiological data Implications for practice and/or policy: The current study shows that the learners' physiological reactivity in terms of EDA was low when monitoring occurred.Measures of physiological data has potential to use inform about student metacognition.
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