Search

© 2019 Arguel, Lockyer, Chai, Pachman and Lipp. When students perform complex cognitive activities, such as solving a problem, epistemic emotions can occur and influence the completion of the task. Confusion is one of these emotions and it can produce either negative or positive outcomes, according to the situation. For this reason, considering confusion can be an important factor for educators to evaluate students' progression in cognitive activities. However, in digital learning environments, observing students' confusion, as well as other epistemic emotions, can be problematic because of the remoteness of students. The study reported in this article explored new methodologies to assess emotions in a problem-solving task. The experimental task consisted of the resolution of logic puzzles presented on a computer, before, and after watching an instructional video depicting a method to solve the puzzle. In parallel to collecting self-reported confusion ratings, human-computer interaction was captured to serve as non-intrusive measures of emotions. The results revealed that the level of self-reported confusion was negatively correlated with the performance on solving the puzzles. In addition, while comparing the pre- and post-video sequences, the experience of confusion tended to differ. Before watching the instructional video, the number of clicks on the puzzle was positively correlated with the level of confusion whereas the correlation was negatively after the video. Moreover, the main emotions reported before the video (e.g., confusion, frustration, curiosity) tended to differ from the emotions reported after the videos (e.g., engagement, delight, boredom). These results provide insights into the ambivalent impact of confusion in problem-solving task, illustrating the dual effect (i.e., positive or negative) of this emotion on activity and performance, as reported in the literature. Applications of this methodology to real-world settings are discussed.

© 2019 Arguel, Lockyer, Chai, Pachman and Lipp. When students perform complex cognitive activities, such as solving a problem, epistemic emotions can occur and influence the completion of the task. Confusion is one of these emotions and it can produce either negative or positive outcomes, according to the situation. For this reason, considering confusion can be an important factor for educators to evaluate students' progression in cognitive activities. However, in digital learning environments, observing students' confusion, as well as other epistemic emotions, can be problematic because of the remoteness of students. The study reported in this article explored new methodologies to assess emotions in a problem-solving task. The experimental task consisted of the resolution of logic puzzles presented on a computer, before, and after watching an instructional video depicting a method to solve the puzzle. In parallel to collecting self-reported confusion ratings, human-computer interaction was captured to serve as non-intrusive measures of emotions. The results revealed that the level of self-reported confusion was negatively correlated with the performance on solving the puzzles. In addition, while comparing the pre- and post-video sequences, the experience of confusion tended to differ. Before watching the instructional video, the number of clicks on the puzzle was positively correlated with the level of confusion whereas the correlation was negatively after the video. Moreover, the main emotions reported before the video (e.g., confusion, frustration, curiosity) tended to differ from the emotions reported after the videos (e.g., engagement, delight, boredom). These results provide insights into the ambivalent impact of confusion in problem-solving task, illustrating the dual effect (i.e., positive or negative) of this emotion on activity and performance, as reported in the literature. Applications of this methodology to real-world settings are discussed.

© 2019 Arguel, Lockyer, Chai, Pachman and Lipp. When students perform complex cognitive activities, such as solving a problem, epistemic emotions can occur and influence the completion of the task. Confusion is one of these emotions and it can produce either negative or positive outcomes, according to the situation. For this reason, considering confusion can be an important factor for educators to evaluate students' progression in cognitive activities. However, in digital learning environments, observing students' confusion, as well as other epistemic emotions, can be problematic because of the remoteness of students. The study reported in this article explored new methodologies to assess emotions in a problem-solving task. The experimental task consisted of the resolution of logic puzzles presented on a computer, before, and after watching an instructional video depicting a method to solve the puzzle. In parallel to collecting self-reported confusion ratings, human-computer interaction was captured to serve as non-intrusive measures of emotions. The results revealed that the level of self-reported confusion was negatively correlated with the performance on solving the puzzles. In addition, while comparing the pre- and post-video sequences, the experience of confusion tended to differ. Before watching the instructional video, the number of clicks on the puzzle was positively correlated with the level of confusion whereas the correlation was negatively after the video. Moreover, the main emotions reported before the video (e.g., confusion, frustration, curiosity) tended to differ from the emotions reported after the videos (e.g., engagement, delight, boredom). These results provide insights into the ambivalent impact of confusion in problem-solving task, illustrating the dual effect (i.e., positive or negative) of this emotion on activity and performance, as reported in the literature. Applications of this methodology to real-world settings are discussed.

© SAGE Publications. Confusion is an emotion that is likely to occur while learning complex information. This emotion can be beneficial to learners in that it can foster engagement, leading to deeper understanding. However, if learners fail to resolve confusion, its effect can be detrimental to learning. Such detrimental learning experiences are particularly concerning within digital learning environments (DLEs), where a teacher is not physically present to monitor learner engagement and adapt the learning experience accordingly. However, with better information about a learner's emotion and behavior, it is possible to improve the design of interactive DLEs (IDLEs) not only in promoting productive confusion but also in preventing overwhelming confusion. This article reviews different methodological approaches for detecting confusion, such as self-report and behavioral and physiological measures, and discusses their implications within the theoretical framework of a zone of optimal confusion. The specificities of several methodologies and their potential application in IDLEs are discussed.

© SAGE Publications. Confusion is an emotion that is likely to occur while learning complex information. This emotion can be beneficial to learners in that it can foster engagement, leading to deeper understanding. However, if learners fail to resolve confusion, its effect can be detrimental to learning. Such detrimental learning experiences are particularly concerning within digital learning environments (DLEs), where a teacher is not physically present to monitor learner engagement and adapt the learning experience accordingly. However, with better information about a learner's emotion and behavior, it is possible to improve the design of interactive DLEs (IDLEs) not only in promoting productive confusion but also in preventing overwhelming confusion. This article reviews different methodological approaches for detecting confusion, such as self-report and behavioral and physiological measures, and discusses their implications within the theoretical framework of a zone of optimal confusion. The specificities of several methodologies and their potential application in IDLEs are discussed.

© SAGE Publications. Confusion is an emotion that is likely to occur while learning complex information. This emotion can be beneficial to learners in that it can foster engagement, leading to deeper understanding. However, if learners fail to resolve confusion, its effect can be detrimental to learning. Such detrimental learning experiences are particularly concerning within digital learning environments (DLEs), where a teacher is not physically present to monitor learner engagement and adapt the learning experience accordingly. However, with better information about a learner's emotion and behavior, it is possible to improve the design of interactive DLEs (IDLEs) not only in promoting productive confusion but also in preventing overwhelming confusion. This article reviews different methodological approaches for detecting confusion, such as self-report and behavioral and physiological measures, and discusses their implications within the theoretical framework of a zone of optimal confusion. The specificities of several methodologies and their potential application in IDLEs are discussed.