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(searched for: doi:10.4236/jilsa.2019.111001)
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Published: 3 January 2023
by MDPI
Journal: Brain Sciences
Brain Sciences, Volume 13; https://doi.org/10.3390/brainsci13010095

Abstract:
Nowadays, fostered by technological progress and contextual circumstances such as the economic crisis and pandemic restrictions, remote education is experiencing growing deployment. However, this growth has generated widespread doubts about the actual effectiveness of remote/online learning compared to face-to-face education. The present study was aimed at comparing face-to-face and remote education through a multimodal neurophysiological approach. It involved forty students at a driving school, in a real classroom, experiencing both modalities. Wearable devices to measure brain, ocular, heart and sweating activities were employed in order to analyse the students’ neurophysiological signals to obtain insights into the cognitive dimension. In particular, four parameters were considered: the Eye Blink Rate, the Heart Rate and its Variability and the Skin Conductance Level. In addition, the students filled out a questionnaire at the end to obtain an explicit measure of their learning performance. Data analysis showed higher cognitive activity, in terms of attention and mental engagement, in the in-presence setting compared to the remote modality. On the other hand, students in the remote class felt more stressed, particularly during the first part of the lesson. The analysis of questionnaires demonstrated worse performance for the remote group, thus suggesting a common “disengaging” behaviour when attending remote courses, thus undermining their effectiveness. In conclusion, neuroscientific tools could help to obtain insights into mental concerns, often “blind”, such as decreasing attention and increasing stress, as well as their dynamics during the lesson itself, thus allowing the definition of proper countermeasures to emerging issues when introducing new practices into daily life.
Ghulam Ruqeyya, Tehmina Hafeez, Sanay Muhammad Umar Saeed, Aleeza Ishwal
Abstract:
Modern era has changed the lifestyle of the people with technological advancement. Video games have become an integral part of daily entertainment for society. This study proposes an engagement index for a video game using electroencephalography (EEG) and compares its result with existing indices available in the literature. This study employs the use of a 14-channel Emotiv EPOC headset for evaluating the engagement of the players in a video game. The study utilizes the dataset of 10 volunteer participants available on Kaggle. Previously available engagement index calculation techniques utilized three or more features while we propose the use of only two features i.e., theta AF3 and alpha P7 for the calculation of the player's engagement index. Results depict that our proposed index is statistically similar to previous indices, while it needs only two electrodes to gauge player engagement. Additionally, these indices can also differentiate between an expert and a novice player. Thus, it is a step towards the improvement of player experience using dynamic difficulty adjustment (DDA).
Keren Avirame, Noga Gshur, Reut Komemi,
Published: 29 September 2022
Frontiers in Human Neuroscience, Volume 16; https://doi.org/10.3389/fnhum.2022.971314

Abstract:
Natural fluctuations in sustained attention can lead to attentional failures in everyday tasks and even dangerous incidences. These fluctuations depend on personal factors, as well as task characteristics. So far, our understanding of sustained attention is partly due to the common usage of laboratory setups and tasks, and the complex interplay between behavior and brain activity. The focus of the current study was thus to test the feasibility of applying a single-channel wireless EEG to monitor patterns of sustained attention during a set of ecological tasks. An EEG marker of attention (BEI—Brain Engagement Index) was continuously recorded from 42 healthy volunteers during auditory and visual tasks from the Test of Everyday Attention (TEA) and Trail Making Test (TMT). We found a descending pattern of both performance and BEI in the auditory tasks as task complexity increases, while the increase in performance and decrease in BEI on the visual task. In addition, patterns of BEI in the complex tasks were used to detect outliers and the optimal range of attention through exploratory models. The current study supports the feasibility of combined electrophysiological and neurocognitive investigation of sustained attention in ecological tasks yielding unique insights on patterns of sustained attention as a function of task modality and task complexity.
Published: 11 September 2022
by MDPI
Journal: Mathematics
Mathematics, Volume 10; https://doi.org/10.3390/math10183294

Abstract:
Objective: to identify energy patterns in the electrophysiological bands of the brain as possible indicators of overconfidence in students when they receive feedback indicating they have erred while solving a mathematical task. Methodology: EEG were recorded from 20 subjects while they performed mathematical exercises. Energy changes in the delta and theta bands before, during, and after solving the task were analyzed. Results: when the answers to the exercises were shown, an increase of energy in the delta band was observed in participants with correct answers but a reduction in that band in those who answered incorrectly. Subjects with incorrect answers received feedback and then attempted to solve a second, similar, exercise. Subjects who answered correctly showed an increase of energy theta, while those with incorrect answers showed a decrease. Conclusions: the energy changes when subjects erred while solving a mathematical task could serve as a quantitative indicator for characterizing overconfidence.
Maryam Alimardani, Jishnu Harinandansingh, Lindsey Ravin, Mirjam de Haas
Abstract:
Social robots have been shown effective in pedagogical settings due to their embodiment and social behavior that can improve a learner’s motivation and engagement. In this study, the impact of a social robot’s motivational gestures in robot-assisted language learning (RALL) was investigated. Twenty-five university students participated in a language learning task tutored by a NAO robot under two conditions (within-subjects design); in one condition the robot provided positive and negative feedback on participant’s performance using both verbal and non-verbal behavior (Gesture condition), in another condition the robot only employed verbal feedback (No-Gesture condition). To assess cognitive engagement and learning in each condition, we collected EEG brain activity from the participants during the interaction and evaluated their word knowledge during an immediate and delayed post-test. No significant difference was found with respect to cognitive engagement as quantified by the EEG Engagement Index during the practice phase. Similarly, the word test results indicated an overall high performance in both conditions, suggesting similar learning gain regardless of the robot’s gestures. These findings do not provide evidence in favor of robot’s motivational gestures during language learning tasks but at the same time indicate challenges with respect to the design of effective social behavior for pedagogical robots.
Yuhao Li, Mengyi Chang, Hanxuan Zhao, Caihong Jiang,
Published: 23 August 2022
by Wiley
Journal of Computer Assisted Learning, Volume 39, pp 63-76; https://doi.org/10.1111/jcal.12727

Rabi Shaw, Chinmay Mohanty, Bidyut Kr. Patra
Abstract:
Flipped Classroom is an innovative learning pedagogy based on students’ academic engagement inside and outside the classroom. Students take lessons from pre-loaded lecture videos through desktop, tablets and mobiles before coming to the classroom. Inside the classroom, the sole focus is on doubt clearing and problem solving. However, it is very difficult to ensure that students really pay attention while watching lecture videos. This is a concern, given the levels of distraction the students are exposed to in this age of internet. Electroencephalogram (EEG) signals can be captured from brain of students and used to monitor their attention.In this study, we develop an efficient approach of feature engineering to analyze the attention level of students in Flipped Classroom from captured brain wave signals. We process the EEG signals using Fast Fourier Transform (FFT). Subsequently, we apply our proposed novel handcrafted features method to obtain the features. Standard classification methods are employed to test the effectiveness of our designed features. Experimental results demonstrate that our proposed handcrafted features perform better than standard FFT-derived-frequency bands.
, John Sadauskas, Robert Christopherson, , , Christian Seto, Irfan Kula, , Robert K. Atkinson
Published: 13 January 2022
Behaviour & Information Technology pp 1-13; https://doi.org/10.1080/0144929x.2021.2024597

Abstract:
This study aimed to establish an accurate baseline for Facebook usage and to investigate its learning potential via biometric perspective. This was explored by asking college students to browse their own Facebook page and peruse the content while wearing a high-fidelity EEG headset to record brainwave activity they experienced. Their actions were then coded using the empirically based Interactive-Constructive-Active-Passive (ICAP) engagement model to identify elements that could potentially be leveraged for learning. Based on these results, Facebook does not seem to make an ideal learning platform, due to higher frustration levels during higher cognitive tasks compared to passively consuming personally relevant non-instructional content. However, it may have more positive impacts on learning as long as initial frustration level is transformed smoothly to engagement and motivation for some learning opportunities and activities.
Людмила Александрова, Раиса Богачева, Татьяна Чекалина, М.в. Максимова,
Vocational Education and Labour Market pp 98-13; https://doi.org/10.52944/port.2021.47.4.007

Abstract:
Изучение возможностей мозга для повышения качества обучения находится в центре внимания педагогической науки уже много лет. Развитие цифровизации позволило использовать в исследованиях специальное оборудование, с помощью которого можно оценивать и контролировать работу мозга, развивать умственные способности, познавательные функции и т. п. Нейротехнологии стали эффективным средством, позволяющим трансформировать образовательный процесс за счет подбора специального учебного контента с учетом индивидуальных особенностей обучающихся. Вместе с тем возникает необходимость в конкретизации терминологии и определении актуальных направлений исследований в данной области. For a long time, the study of the brain capabilities for the improvement of the quality of education has been an urgent direction in pedagogical science. Due to the development of digitalization, new areas of research have emerged related to the use of special equipment that makes it possible to assess and control brainwork, develop mental abilities, cognitive functions, etc. One of them is neurotechnology, which is an effective means of transforming the educational process: it offers educational content based on the individual characteristics of students. Thus, a need to concretize the terminology and determine the current research areas arises. The article aims to attempt to fill this gap with the help of a representative analysis of publications on neurotechnologies, as well as the essence of neuroeducation.
Published: 18 July 2021
by MDPI
Journal: Sensors
Sensors, Volume 21; https://doi.org/10.3390/s21144885

Abstract:
Adults are constantly exposed to stressful conditions at their workplace, and this can lead to decreased job performance followed by detrimental clinical health problems. Advancement of sensor technologies has allowed the electroencephalography (EEG) devices to be portable and used in real-time to monitor mental health. However, real-time monitoring is not often practical in workplace environments with complex operations such as kindergarten, firefighting and offshore facilities. Integrating the EEG with virtual reality (VR) that emulates workplace conditions can be a tool to assess and monitor mental health of adults within their working environment. This paper evaluates the mental states induced when performing a stressful task in a VR-based offshore environment. The theta, alpha and beta frequency bands are analysed to assess changes in mental states due to physical discomfort, stress and concentration. During the VR trials, mental states of discomfort and disorientation are observed with the drop of theta activity, whilst the stress induced from the conditional tasks is reflected in the changes of low-alpha and high-beta activities. The deflection of frontal alpha asymmetry from negative to positive direction reflects the learning effects from emotion-focus to problem-solving strategies adopted to accomplish the VR task. This study highlights the need for an integrated VR-EEG system in workplace settings as a tool to monitor and assess mental health of working adults.
Mo Wang, Minjuan Wang, Yulu Cui,
Published: 6 April 2021
Frontiers in Psychology, Volume 12; https://doi.org/10.3389/fpsyg.2021.627095

Abstract:
The pandemic in 2020 made online learning the widely used modality of teaching in several countries and it has also entered the spotlight of educational research. However, online learning has always been a challenge for disciplines (engineering, biology, and art) that require hands-on practice. For art teaching or training, online learning has many advantages and disadvantages. How art teachers embrace and adapt their teaching for online delivery remains an unanswered question. This research examines 892 art teachers' attitudes toward online learning, using learning environment, need satisfaction, mental engagement, and behavior as predictors. Structural equation modeling was used to explore the relationship between these four dimensions during these teachers' participation in an online learning program. The results reveal significant correlations between the learning environment, need satisfaction, mental engagement, and behavior. Moreover, this study reveals the group characteristics of art teachers, which can actually be supported by online learning programs. These findings provide insights into how art teachers view and use online learning, and thus can shed lights on their professional development.
E. Rafael Hernandez-Rios, Christian Penaloza
Abstract:
The concept of the knowledge transfer from a human expert to another non-expert human through technological interfaces, where a task can be learned by using brain-to-brain or body-to-body connections has great potential for future applications in which traditional verbal or visual communication channels are not available. In this paper, we present a novel approach of human-to-human knowledge transfer using a system based on functional electrical stimulation (FES). Using the proposed approach, hand-arm movements from a human teacher are recognized through an electromyogram signal classification algorithm. Using a master-slave approach, the movement signals are then translated into electrical stimulation signals and transmitted to a human learner using a functional electrical stimulation device. In the experiment conducted, we show how a human expert teaches seven learners a task that consists of associating hand-arm movements with visual stimuli presented to the learners. Furthermore, cognitive engagement was monitored during the learning process using an electroencephalogram (EEG) system. Experimental results show that four out of seven participants were able to learn the task with an accuracy over 80% and their cognitive engagement correlates to their performance.
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