Assessment of cognitive student engagement using heart rate data in distance learning during COVID-19

Student engagement allows educational institutions to make better decisions regarding teaching methodologies, methods for evaluating the quality of education, and ways to provide timely feedback. Due to the COVID-19 pandemic, identifying cognitive student engagement in distance learning has been a challenge in higher education institutions. In this study, we implemented a non-self-report method assessing students' heart rate data to identify the cognitive engagement during active learning activities. Additionally, as a supplementary tool, we applied a previously validated self-report method. This study was performed in distance learning lessons on a group of university students in Bogota, Colombia. After data analysis, we validated five hypotheses and compared the results from both methods. The results confirmed that the heart rate assessment had a statistically significant difference with respect to the baseline during active learning activities, and this variance could be positive or negative. In addition, the results show that if students are previously advised that they will have to develop an a new task after a passive learning activity (such as a video projection), their heart rate will tend to increase and consequently, their cognitive engagement will also increase. We expect this study to provide input for future research assessing student cognitive engagement using physiological parameters as a tool. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Development of an affective database made of interactive virtual environments.

Despite the great potential of Virtual Reality (VR) to arouse emotions, there are no VR affective databases available as it happens for pictures, videos, and sounds. In this paper, we describe the validation of ten affective interactive Virtual Environments (VEs) designed to be used in Virtual Reality. These environments are related to five emotions. The testing phase included using two different experimental setups to deliver the overall experience. The setup did not include any immersive VR technology, because of the ongoing COVID-19 pandemic, but the VEs were designed to run on stereoscopic visual displays. We collected measures related to the participants' emotional experience based on six discrete emotional categories plus neutrality and we included an assessment of the sense of presence related to the different experiences. The results showed how the scenarios can be differentiated according to the emotion aroused. Finally, the comparison between the two experimental setups demonstrated high reliability of the experience and strong adaptability of the scenarios to different contexts of use.

Assessment of Cognitive Student Engagement Using Heart Rate Data in Distance Learning during COVID-19

Student engagement allows educational institutions to make better decisions regarding teaching methodologies, methods for evaluating the quality of education, and ways to provide timely feedback. Due to the COVID-19 pandemic, identifying cognitive student engagement in distance learning has been a challenge in higher education institutions. In this study, we implemented a non-self-report method assessing students’ heart rate data to identify the cognitive engagement during active learning activities. Additionally, as a supplementary tool, we applied a previously validated self-report method. This study was performed in distance learning lessons on a group of university students in Bogota, Colombia. After data analysis, we validated five hypotheses and compared the results from both methods. The results confirmed that the heart rate assessment had a statistically significant difference with respect to the baseline during active learning activities, and this variance could be positive or negative. In addition, the results show that if students are previously advised that they will have to develop an a new task after a passive learning activity (such as a video projection), their heart rate will tend to increase and consequently, their cognitive engagement will also increase. We expect this study to provide input for future research assessing student cognitive engagement using physiological parameters as a tool.