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

2021 ◽  
Vol 11 (9) ◽  
pp. 540
Author(s):  
Andrea Catalina Ladino Nocua ◽  
Joan Paola Cruz Gonzalez ◽  
Ivonne Angelica Castiblanco Jimenez ◽  
Juan Sebastian Gomez Acevedo ◽  
Federica Marcolin ◽  
...  

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.

2020 ◽  
Vol 24 (5) ◽  
pp. 63-71
Author(s):  
G. R. Chaynikova

Purpose of study. In the situation of the coronavirus pandemic, distance learning technologies have become the only way to organize the educational process. The transition to distance learning required both adaptation of the content, tools and methods of teaching to the new conditions, and adaptation on the part of students, in particular, it demanded from them to be much more independent and responsible, as well as the ability to effectively use their time. In this connection, the aim of the study was to analyze how the technology of blended learning allows students to better adapt to the conditions of distance learning.Materials and methods. The author considered the following as the main indicators of students’ adaptation to distance learning: 1) actual results of learning activities; 2) the degree of students’ satisfaction with the results of their learning activity; 3) self-assessment of readiness to use ICT tools in learning process, development of independent work and self-organization skills, self-report on the psychological state. The analysis of pedagogical literature on blended learning made it possible to identify a number of important principles which the learning process should be based on in the flipped classroom model, the analysis of which, in turn, showed that they fully correspond with the principles of distance learning. All this suggests that blended learning as a component of full-time instruction, implemented from the first term when teaching English as an academic discipline, should help students better adapt to the conditions of distance learning. To confirm this hypothesis, an analysis and comparison of the results of learning activities in the conditions of blended and distance learning, as well as a questionnaire of students were conducted.Results. Comparison of the current and final performance in English as an academic subject in the conditions of blended and distance learning did not reveal any significant changes. Survey analysis showed that the transition to distance learning was a challenge for most students and demanded from them to make significant efforts  to adapt, which was manifested in a decreased level of satisfaction with the results of their learning activities in general, an increased level of anxiety, as well as highlighting a number of difficulties that they had to face. However, a comparison of data obtained on the discipline “English language”, where training was initially built on the flipped classroom model, and data on distance learning in general allows the author to conclude that the technology of blended learning makes it possible to reduce a number of difficulties, in particular, technical difficulties when switching to distance learning, and the indicator of satisfaction with the results of their learning activities shows that the flipped classroom model allows students to more fully realize their abilities and achieve the desired results not only in the conditions of blended learning, but also when switching to distance one.Conclusion. The analysis made it possible to show a significant potential of blended learning in the conditions of introducing information technologies in education. At the same time, it is necessary to keep in mind the importance of pedagogical support in the context of e-learning.


1998 ◽  
Vol 2 ◽  
pp. 141-148
Author(s):  
J. Ulbikas ◽  
A. Čenys ◽  
D. Žemaitytė ◽  
G. Varoneckas

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.


Author(s):  
Kotaro SATO ◽  
Kazunori OHNO ◽  
Ryoichiro TAMURA ◽  
Sandeep Kumar NAYAK ◽  
Shotaro KOJIMA ◽  
...  

2014 ◽  
Vol 8 (1) ◽  
pp. 64-69 ◽  
Author(s):  
Matthew Stenerson ◽  
Fraser Cameron ◽  
Darrell M. Wilson ◽  
Breanne Harris ◽  
Shelby Payne ◽  
...  

2017 ◽  
Vol 220 (10) ◽  
pp. 1875-1881 ◽  
Author(s):  
Olivia Hicks ◽  
Sarah Burthe ◽  
Francis Daunt ◽  
Adam Butler ◽  
Charles Bishop ◽  
...  

Author(s):  
Junichiro Hayano ◽  
Emi Yuda

The prediction of the menstrual cycle phase and fertility window by easily measurable bio-signals is an unmet need and such technological development will greatly contribute to women's QoL. Although many studies have reported differences in autonomic indices of heart rate variability (HRV) between follicular and luteal phases, they have not yet reached the level that can predict the menstrual cycle phases. The recent development of wearable sensors-enabled heart rate monitoring during daily life. The long-term heart rate data obtained by them carry plenty of information, and the information that can be extracted by conventional HRV analysis is only a limited part of it. This chapter introduces comprehensive analyses of long-term heart rate data that may be useful for revealing their associations with the menstrual cycle phase.


2020 ◽  
Vol 32 (5) ◽  
pp. 242-244 ◽  
Author(s):  
Aaron B. Neinstein ◽  
Michael Blum ◽  
Umesh Masharani

SLEEP ◽  
2019 ◽  
Vol 42 (12) ◽  
Author(s):  
Olivia Walch ◽  
Yitong Huang ◽  
Daniel Forger ◽  
Cathy Goldstein

Abstract Wearable, multisensor, consumer devices that estimate sleep are now commonplace, but the algorithms used by these devices to score sleep are not open source, and the raw sensor data is rarely accessible for external use. As a result, these devices are limited in their usefulness for clinical and research applications, despite holding much promise. We used a mobile application of our own creation to collect raw acceleration data and heart rate from the Apple Watch worn by participants undergoing polysomnography, as well as during the ambulatory period preceding in lab testing. Using this data, we compared the contributions of multiple features (motion, local standard deviation in heart rate, and “clock proxy”) to performance across several classifiers. Best performance was achieved using neural nets, though the differences across classifiers were generally small. For sleep-wake classification, our method scored 90% of epochs correctly, with 59.6% of true wake epochs (specificity) and 93% of true sleep epochs (sensitivity) scored correctly. Accuracy for differentiating wake, NREM sleep, and REM sleep was approximately 72% when all features were used. We generalized our results by testing the models trained on Apple Watch data using data from the Multi-ethnic Study of Atherosclerosis (MESA), and found that we were able to predict sleep with performance comparable to testing on our own dataset. This study demonstrates, for the first time, the ability to analyze raw acceleration and heart rate data from a ubiquitous wearable device with accepted, disclosed mathematical methods to improve accuracy of sleep and sleep stage prediction.


2018 ◽  
Vol 42 (2) ◽  
pp. 182-191 ◽  
Author(s):  
Renee M. McFee ◽  
Andrea S. Cupp ◽  
Jennifer R. Wood

Didactic lectures are prevalent in physiology courses within veterinary medicine programs, but more active learning methods have also been utilized. Our goal was to identify the most appropriate learning method to augment the lecture component of our physiology course. We hypothesized that case-based learning would be well received by students and would be more effective at helping them learn physiological concepts compared with more traditional laboratory exercises. In this study, approximately one-half of the laboratory sessions for the two-semester course were dedicated to traditional hands-on laboratory exercises, whereas the remaining one-half of the sessions were dedicated to case-based exercises. The lecture portion of the course was not altered. Student attitudes were evaluated after each session and at the end of each semester via quantitative and qualitative survey questions. Student performance was evaluated using section exams and end-of-semester posttests. The vast majority of survey responses received were positive for both cased-based activities and traditional hands-on laboratories. In addition, participation in both types of active learning activities, but not lecture, was associated with retention of conceptual knowledge based on student performance between the section exams and posttests ( P < 0.002). These results indicate that both case-based learning and laboratory exercises are beneficial learning activities to incorporate into a lecture-based physiology course. However, positive survey responses were significantly greater following case-based activities vs. traditional hands-on laboratories, and only participation in case-based activities resulted in greater student performance on the posttest ( P < 0.04). Therefore, case-based activities may be the preferred supplemental learning activity for veterinary medical physiology.


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