Xi Li^1,2, Weiwei Zhu², Qian Li^3,*, Changhui Hou^1,*, Yaozong Zhang¹

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 369-391, 2024, DOI:10.32604/cmc.2024.054982 - 15 October 2024

Abstract Automatically detecting learners’ engagement levels helps to develop more effective online teaching and assessment programs, allowing teachers to provide timely feedback and make personalized adjustments based on students’ needs to enhance teaching effectiveness. Traditional approaches mainly rely on single-frame multimodal facial spatial information, neglecting temporal emotional and behavioural features, with accuracy affected by significant pose variations. Additionally, convolutional padding can erode feature maps, affecting feature extraction’s representational capacity. To address these issues, we propose a hybrid neural network architecture, the redistributing facial features and temporal convolutional network (RefEIP). This network consists of three key components:… More >

Farhad Mortezapour Shiri^1,*, Ehsan Ahmadi², Mohammadreza Rezaee¹, Thinagaran Perumal¹

Journal on Artificial Intelligence, Vol.6, pp. 85-103, 2024, DOI:10.32604/jai.2024.048911 - 24 April 2024

Abstract Automatic detection of student engagement levels from videos, which is a spatio-temporal classification problem is crucial for enhancing the quality of online education. This paper addresses this challenge by proposing four novel hybrid end-to-end deep learning models designed for the automatic detection of student engagement levels in e-learning videos. The evaluation of these models utilizes the DAiSEE dataset, a public repository capturing student affective states in e-learning scenarios. The initial model integrates EfficientNetV2-L with Gated Recurrent Unit (GRU) and attains an accuracy of 61.45%. Subsequently, the second model combines EfficientNetV2-L with bidirectional GRU (Bi-GRU), yielding More >

Lennize Pereira Paulo^1,2,*, Catherine Tourette-Turgis^1,2, Marie-Paule Vannier^1,3

Psycho-Oncologie, Vol.18, No.1, pp. 9-15, 2024, DOI:10.32604/po.2023.042981 - 25 March 2024

Abstract Cet article présente l’histoire et les enjeux de la diplomation des patients en la posant comme un dispositif de soutien de l’engagement des patients et des usagers du système de santé. Un ensemble de lois relatives aux droits des malades et à la qualité du système de santé permettent l’intégration des patients dans le système de santé mais elles se heurtent à la non-préparation des institutions à ce nouveau champ de pratiques. La diplomation des patients nécessite des transformations dans les modes d’accueil et de financement des universités et aussi dans les méthodes pédagogiques qui More >

Wan Xiao^1,*, Miaoting Cheng^2,*

International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1303-1311, 2023, DOI:10.32604/ijmhp.2023.042976 - 29 December 2023

Abstract Internet addiction and cyberbullying have emerged as significant global mental health concerns in recent years. Although previous studies have shown a close association between Internet addiction and cyberbullying, the underlying mechanisms connecting these two phenomena remain unclear. Therefore, this study aimed to reveal the mechanisms involved between Internet addiction and cyberbullying perpetration from the perspective of cognition function. This study recruited 976 Chinese youth through online survey, using the short version of Internet Addiction Test (s-IAT), Chinese Cyberbullying Intervention Project Questionnaire (C-CIPQ), Cyberbullying Moral Disengagement Scale (CMDS), and Internet Literacy Questionnaire (ILQ) to investigate the More >

Jialing Miao¹, Wei Liao^2,*, Baoguo Xie³

International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1147-1157, 2023, DOI:10.32604/ijmhp.2023.030671 - 03 November 2023

Abstract Although employers believe that encouraging and supporting physical exercise activities by purchasing fitness equipment and building sports venues can improve employees’ well-being, the utilization rate is rather low. Since most of the evidence of the well-being promotion in the workplace concentrated on the perspectives of organizational factors and psychosocial factors and focused on the reduction of the negative affect of well-being, it is still an open question whether physical exercise has benefits on both negative and positive affect of wellbeing and who benefits more from physical exercise. Thus, the purpose of this study is to… More >

F. Farsi, E. Huyghe, L. Vanlemmens, S. Dolbeault, T. Almont, E. Marx, I. Flandrin, J. Véronique-Baudin, B. Panes-Ruedin, P. Bondil

Psycho-Oncologie, Vol.17, No.2, pp. 99-104, 2023, DOI:10.3166/pson-2022-0235

Abstract L’abord systématisé et en routine de la préservation de la vie intime, de la sexualité et de la fertilité n’est pas encore pleinement intégré à la consultation des praticiens et pas de manière significative par les autres intervenants du parcours de soins en cancérologie. On sait pourtant, et de manière de plus en plus documentée, que ce sont des sujets de préoccupation pour les patients et leurs partenaires, qui considèrent, pour leur grande majorité, que leur santé sexuelle et/ou leurs projets parentaux sont des sujets importants. Depuis maintenant plus de dix ans, un groupe d’experts… More >

Yi Chen^1,*, Jin Zhou¹, Qianting Gao², Jing Gao¹, Wei Zhang³

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 381-401, 2023, DOI:10.32604/cmes.2023.023234 - 05 January 2023

Abstract Prediction of students’ engagement in a Collaborative Learning setting is essential to improve the quality of learning. Collaborative learning is a strategy of learning through groups or teams. When cooperative learning behavior occurs, each student in the group should participate in teaching activities. Researchers showed that students who are actively involved in a class gain more. Gaze behavior and facial expression are important nonverbal indicators to reveal engagement in collaborative learning environments. Previous studies require the wearing of sensor devices or eye tracker devices, which have cost barriers and technical interference for daily teaching practice. More >

Lei Chen¹, Ting Wen^2,*, Jigan Wang¹, Hong Gao¹

International Journal of Mental Health Promotion, Vol.24, No.1, pp. 69-84, 2022, DOI:10.32604/ijmhp.2022.018932 - 20 December 2021

Abstract The average stress of people in China’s workplace is reaching the peak in recent two years. To improve employee’s positive psychological factors, Spiritual leadership has a good performance in this regard. Based on the mediating effect of goal self-concordance and self-efficacy, this paper further studies the impact of spiritual leadership on employee’s work engagement. Through the empirical study, the following conclusions are drawn: (1) Spiritual leadership significantly positively affects the employee’s work engagement. (2) Spiritual leadership has a significant positive effect on goal self-concordance and self-efficacy. (3) Goal self-concordance and self-efficacy have significant positive effects More >

Suraya Hamid¹, Shahrul Nizam Ismail¹, Muzaffar Hamzah^2,*, Asad W. Malik³

Computer Systems Science and Engineering, Vol.42, No.1, pp. 335-350, 2022, DOI:10.32604/csse.2022.021927 - 02 December 2021

Abstract Learning analytics is an emerging technique of analysing student participation and engagement. The recent COVID-19 pandemic has significantly increased the role of learning management systems (LMSs). LMSs previously only complemented face-to-face teaching, something which has not been possible between 2019 to 2020. To date, the existing body of literature on LMSs has not analysed learning in the context of the pandemic, where an LMS serves as the only interface between students and instructors. Consequently, productive results will remain elusive if the key factors that contribute towards engaging students in learning are not first identified. Therefore, More >

Shoroog Khenkar^1,*, Salma Kammoun Jarraya^1,2

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2655-2677, 2022, DOI:10.32604/cmc.2022.019152 - 27 September 2021

Abstract This paper proposes a novel, efficient and affordable approach to detect the students’ engagement levels in an e-learning environment by using webcams. Our method analyzes spatiotemporal features of e-learners’ micro body gestures, which will be mapped to emotions and appropriate engagement states. The proposed engagement detection model uses a three-dimensional convolutional neural network to analyze both temporal and spatial information across video frames. We follow a transfer learning approach by using the C3D model that was trained on the Sports-1M dataset. The adopted C3D model was used based on two different approaches; as a feature More >