Real-Time Emotion Recognition in Online Learning Using Google Teachable

A learning environment’s quality has crucial influence on a student’s engagement. In this study, we utilized a structural equation modeling approach to explore the structural relationships between students’ perceptions of an online learning environment and their online learning engagement during China’s COVID-19 school closure period by focusing on an online learning environment and the specific features that facilitate student engagement. The online learning environment was conceptualized as a multidimensional structure consisting of four elements: pedagogy, social interaction, technology, and the consideration of home learning conditions. Student engagement was conceptualized as a multifaceted construct comprising behavioral, emotional, and cognitive engagement. The results showed that teaching presence significantly predicted deep behavioral engagement (β = 0.246), emotional engagement (β = 0.110), and cognitive engagement (β = 0.180). Social presence significantly positively predicted cognitive engagement (β = 0.298) and emotional engagement (β = 0.480), whereas its effect on behavioral engagement was not significant. The perceived ease of technology use significantly predicted only emotional engagement (β = 0.324), and the family learning presence significantly predicted only behavioral engagement (β = 0.108). The results also indicated that emotional and cognitive engagement had indirect effects on the predictive power of the online learning environment for behavioral engagement. These findings provide valuable guidelines and effective strategies for teachers and parents to design suitable online learning environments to enhance K–12 student engagement.

Learning persistence is recognized as an essential factor for effective online learning, and students interaction and emotional engagement are significant antecedents of learning persistence. In order to promote students' learning achievement and outcome, it is valuable to explore their relationships in online learning environments. Therefore, this study employed structural equation modeling (SEM) to examine the relationships among students' online interaction, emotional engagement and learning persistence. The path model was proposed to test the mediating effects of emotional engagement. Data were collected from 328 university students in China, and the path was analyzed. The results of this study demonstrated that online interaction and emotional engagement were positively associated with students' learning persistence. In addition, emotional engagement also mediated the relationships between student-instructor interaction, student-content interaction and learning persistence in online learning environments. Consequently, from the perspectives of interaction and emotion, implications were discussed to promote students'learning persistence.

Lack of student engagement in online learning is reported as the major challenge contributing to poor academic performance and completion rates. When transforming an in-person undergraduate remote sensing course to online, this study implemented interactive storytelling lecture trailers (ISLTs) as a tool to effect changes in the realms of behavioral, cognitive, emotional, and student-instructor engagement. We collected survey data to examine students’ own perception of how ISLTs impacted their online learning, and analyzed students’ course participation and performance on tests. Results indicated that ISLTs enhanced some aspects of students’ behavioral engagement such as page views, effectively engaged students’ emotions when viewing ISLTs, and improved student-instructor engagement. Regarding cognitive engagement, ISLTs were able to improve short-term learning skills like remembering and applying levels of thinking. A majority of students recognized that ISLTs enhanced their learning experience and made learning more accessible, while a few considered them burdensome and overwhelming. However, there was no clear evidence indicating that ISLTs enhanced participation or promoted students’ emotional engagement in the follow-up lectures. Further, the improvement of student-instructor engagement we observed through quantitative data analysis lacked representative qualitative support. In summary, this study demonstrates the utility of ISLTs as an online learning engagement tool for stimulating students’ interest and improving their performance in lower levels of cognitive thinking. Further work is required to explore ways to further enhance students’ participation and emotional engagement throughout the semester and confirm the usefulness of ISLTs for student-instructor engagement.

Real-time emotion recognition provides promising applications for mental healthcare monitoring and human-computer interaction design. Electroencephalography (EEG) emotion recognition has become a hot topic in the field of affective computing and intelligent brain-computer interface (BCI), and it is a feasible solution for achieving real-time emotion recognition. However, due to the uncertainty and individual specificity of emotional cognition, there are still some challenges in achieving efficient online emotion decoding applications. To address this, in this work, we propose an online emotion decoding method named DMSGL (Real-Time EEG Emotion Recognition from Dynamic Mixed Spatiotemporal Graph Learning). Specifically, in the DMSGL, we propose to explore the latent emotion-related graph features from EEG with cognition-inspired and data-driven learning strategies, and the temporal analysis with attention learning is utilized to further extract the robust spatiotemporal graph patterns for efficient EEG emotion decoding. Both simulated online emotion decoding and real-time emotion monitoring experimental results have consistently indicated that the proposed DMSGL can effectively satisfy the application requirements of real-time emotion decoding and achieves an accuracy of 68.35% in real-world online scenarios. Compared with other baseline methods, the proposed DMSGL has improved by 2-5% in the scenario of real-time emotion recognition. In conclusion, the proposed DMSGL provides a promising solution for realizing real-time emotion recognition and further exploring related applications. Our code is released on https://github.com/UESTC-BAC/DMSGL.

An experimental design was carried out to study the effectiveness in learning of tenth grade students in Physics, when taught through online and face-to-face (F2F). A mash-up of different online tools and learning environment is used for the study. Website 'Wiziq.com' provides these online tools and learning environment hence it is used for the study of effectiveness of online learning on students' achievement. A high score in achievement among students' taught and studied through online tools and online learning environment was found through this research. Similarly achievement among students of F2F teaching was found low, this is because in F2F learning, collaborating and sharing of resources is limited to the walls of classroom, but online learning made possible to learning, collaborating, and sharing of resources beyond four walls. Online learning environment provides features such as, user centre, user control and communication, and making teaching learning process learner centric.

The chapter discusses the development of emancipatory online learning environments in quality teacher education. Under the uncertainty of a changing world caused by COVID-19 pandemic, teachers were required to adapt their teaching to online learning environments. Additionally, they had to learn how to design interactive and quality online learning environments. Against this backdrop, it is necessary to raise new questions about what quality teaching means in online learning environments. Discourses on quality teaching are commonly associated with teacher effectiveness. We argue, however, that quality teaching in teacher education also implies thinking about emancipatory pedagogical approaches in the development of (online) learning environments. In this sense, we explore emancipatory ways of understanding quality in online learning teacher education. First, we elaborate on quality debates in teacher education. Second, we focus on a specific dimension of quality teaching, that is, the development of (online) learning environments in teacher education. Third, we explore critical perspectives and emancipatory pedagogical approaches in teacher education. Last, we advise teaching strategies to create online learning environments with a focus on emancipatory pedagogical approaches. As a result, teaching strategies are suggested to connect quality online learning environments to emancipatory pedagogical approaches.

These years, emotion recognition has been one of the hot topics in computer science and especially in Human-Robot Interaction (HRI) and Robot-Robot Interaction (RRI). By emotion (recognition and expression), robots can recognize human behavior and emotion better and can communicate in a more human way. On that point are some research for unimodal emotion system for robots, but because, in the real world, Human emotions are multimodal then multimodal systems can work better for the recognition. Yet, beside this multimodality feature of human emotion, using a flexible and reliable learning method can help robots to recognize better and makes more beneficial interaction. Deep learning showed its force in this area and here our model is a multimodal method which use 3 main traits (Facial Expression, Speech and gesture) for emotion (recognition and expression) in robots. We implemented the model for six basic emotion states and there are some other states of emotion, such as mix emotions, which are really laborious to be picked out by robots. Our experiments show that a significant improvement of identification accuracy is accomplished when we use convolutional Neural Network (CNN) and multimodal information system, from 91 % reported in the previous research [27] to 98.8 %.

Learners’ emotional engagement in synchronous online learning (SOL) is critical for improving learning persistence and performance. Nevertheless, there is currently a lack of comprehensive and systematic reviews of emotional engagement in SOL. This review synthesizes the strategies to promote emotional engagement in SOL found in published empirical studies. A total of 32 articles were systematically analyzed by following the grounded theory approach. The primary themes were grouped into four categories: (a) instructor actions (e.g., interacting informally before and after class, encouraging the expression of ideas), (b) learner behaviors (e.g., building rapport with peers, recognizing individual accountability), (c) environment characteristics (e.g., creating a supportive atmosphere, selecting communication modes), and (d) activity design (e.g., using breakout rooms, embedding diverse elements). These findings offer comprehensive understanding and guidance for promoting emotional engagement in SOL for instructors, researchers, and course developers.

The implementation of Online Synchronous Learning (OSL) poses many challenges to existing instruction technology theory because of the complexity of the digital age. Although many studies have been carried out for an OSL, there is little evidence of OSL for teaching language learning. This is especially so when it involves multiple cultural perspectives. This chapter describes the implementation of OSL for teaching English to foreign students from different cultures. The authors believe that the cultural historical Activity Theory is ideal for understanding OSL and its pedagogy. Through the lens of Activity Theory, this study takes close look at OSL courses and examines the socio-cultural factors affecting the success of the course as well as their complex relationships. Applying Activity Theory to analyze data collected over three years we have developed a framework to help educators who intend to implement OSL from multiple cultural perspectives.

The implementation of Online Synchronous Learning (OSL) poses many challenges to existing instruction technology theory because of the complexity of the digital age. Although many studies have been carried out for an OSL, there is little evidence of OSL for teaching language learning. This is especially so when it involves multiple cultural perspectives. This chapter describes the implementation of OSL for teaching English to foreign students from different cultures. The authors believe that the cultural historical Activity Theory is ideal for understanding OSL and its pedagogy. Through the lens of Activity Theory, this study takes close look at OSL courses and examines the socio-cultural factors affecting the success of the course as well as their complex relationships. Applying Activity Theory to analyze data collected over three years we have developed a framework to help educators who intend to implement OSL from multiple cultural perspectives.

The facial and physiological sensor-based emotion recognition methods are two popular methods of emotion recognition. The proposed research is the first of its kind in real-time emotion recognition that combines skin conductance signals with the visual-based facial emotion recognition (FER) method on a Raspberry Pi. This research includes stepwise documentation of method for automatic real-time face detection and FER on portable hardware. Further, the proposed work comprises experimentation related to video induction and habituation methods with FER and the galvanic skin response (GSR) method. The GSR data are recorded as skin conductance and represent the subject's behavioral changes in the form of emotional arousal and face emotion recognition on the portable device. The article provides a stepwise implementation of the following methods: (a) the skin conductance representation from the GSR sensor for arousal; (b) gathering visual inputs for identifying the human face; (c) FER from the camera module; and (d) experimentation on the proposed framework. The key feature of this article is the comprehensive documentation of stepwise implementation and experimentation, including video induction and habituation experimentation. An illuminating aspect of the proposed method is the survey of GSR trademarks and the conduct of psychological experiments. This study is useful for emotional computing systems and potential applications like lie detectors and human–machine interfaces, devices for gathering user experience input, identifying intruders, and providing portable and scalable devices for experimentation. We termed our approaches "sensovisual" (sensors + visual) and "Emosense" (emotion sensing).

Objectives This study aimed to analyze the structural relationships among online course organization, student engagement and perceived learning outcome in university online learning environment. Methods The survey data were collected from a total of 359 students who took the 100% online course offered by K University in the fall semester of 2021. The structural equation modeling was conducted to examine the relationships among course organization, behavioral, emotional, cognitive engagement and perceived learning outcome. Results The findings showed that online course organization had significant effects on behavioral engagement and perceived learning outcome. Behavioral engagement had a positive(+) effect on emotional and cognitive engagement, and emotional engagement had a positive(+) effect on cognitive engagement. In addition, emotional engagement was found to mediate the relationship between behavioral, cognitive engagement and perceived learning outcome. Conclusions This study attempts to broaden the understanding of student engagement reflecting multidimensional concepts by identifying the interrelationships among behavioral, emotional and cognitive engagement. Also, the results of this study can provide implications for teaching strategies to promote student engagement in online learning.

The primary goal of the study is to investigate the effect of the usage of humor on behavioral, emotional, and cognitive engagement in online learning. Humorous elements were integrated into the online learning components. The mixed-method study was conducted over 14 weeks with the participation of 74 university students in an online university course. As a result, elements of humor can be integrated into materials for attention grabbing, recalling, feedback, and humor breaks. A diversity of humorous elements created a significant difference and improved behavioral engagement for course materials, discussions, and assignments. However, humorous elements did not contribute to the behavioral engagement for quizzes. It was additionally observed for emotional engagement that the use of humor created a significant difference and improved emotional engagement. As for cognitive engagement, a positive influence of the usage of humorous elements in course materials, discussions and assignments was observed.

PurposeIn this paper the authors have sought to create solid connection between theory and practices pertaining to the immense value of students' emotional engagement in online instruction. This conceptual paper is motivated by the inadequacy of literature translating the emotional engagement concept to the micro level of online instructions within the upsurge intention to the new trend of online teaching-learning. This paper aims to contribute by addressing the fundamental issues of emotional engagement starting from revisiting the roles of teachers in students' emotional engagement, reviewing and underscoring the importance of students' emotional engagement in higher education and finally conceptualizing and framing how to infuse emotional engagement into the instructions.Design/methodology/approachThe explanation of how to advocate for students' emotional engagement in online learning praxis is inadequately discussed although the library of literature has informed the fundamental role of students' emotional engagement in establishing successful online learning. This paper aims to address this practical need by interactively connecting the theory, empirical findings and pedagogical practices in the area to provide praxeological contribution to the development of quality online teaching-learning practices.FindingsThis study presents a framework that advances the existing body of research at the juncture of emotional engagement and online learning. This conceptual paper foregrounds an examination of the roles of teachers in students' emotional engagement and underscores the significance of students' emotional engagement in higher education. Moreover, it proposes a conceptual framework delineating effective strategies for the integration of emotional engagement within instructional methodologies. This framework comprises four key aspects: (1) fostering students' learning autonomy and ownership, (2) establishing socioemotional construction through verbal and non-verbal expressions, (3) integrating a multimodal approach to online learning and (4) honing the art of constructive feedback.Research limitations/implicationsThis conceptual paper is rooted in a nested theory and draws upon empirical studies. While the presented framework holds promise, its efficacy in the classroom setting requires validation through further empirical investigation.Practical implicationsThose proposed pedagogical strategies detailed with the practical examples explained in the previous part would afford students with a better socioemotional amenities of learning environment benefitting them with positive affective engagement.Originality/valueGiven the imperative to enhance students' emotional engagement in online learning and the limited discourse surrounding its practical implementation, the proposed framework stands poised to enrich and inform online pedagogical practices.

With online learning moving into the long term, the mental and academic impacts on students arelikely to be challenging. Preliminary results obtained from three different student surveys are presented and analyzed for different cohorts of undergraduate engineering students enrolled in an engineering program at the Université de Moncton. The first survey was administered during the last week of the Winter semester, before the final exams period. This survey was administered by the Engineering Faculty and created to get an overview of students experience during their online learning sessions. Specifically, the goal of this survey was to get information on which technical tools work best for distance learning during their online sessions and to improve future online learning sessions. Another survey was completed at the end of the Fall 2020 online learning semester. About half of all engineering students completed the surveys and a preliminary analysis was conducted. Finally, a third survey was administered during the Winter 2021 online learning semester. The aim of this study is to evaluate and analyze the results of these surveys using educational data mining. This work will provide an overview of the online learning experience during the end of the Winter 2020 semester and the academic year 2020-2021 and establish relations between classroom and online learning environments. New data analysis may help to accelerate and improve future hybrid classroom-online learning pedagogy since permanent changes are expected in the near future for many engineering programs. This study shows that students vary in their abilities to adapt to this new reality. Most prefer recorded audio clipsof PowerPoint presentations beforehand combined with online synchronous learning using video conferencing software. This suggests that effective online learning requires extra time from educators to better prepare class sessions. Furthermore, there is an important correlation between the level of student motivation and their appreciation level of online learning.