Social emotional interaction in collaborative learning: Why it matters and how can we measure it?

A text semantic classification is an essential approach to recognising the verbal intention of online learners, empowering reliable understanding and inquiry for the regulations of knowledge construction amongst students. However, online learning is increasingly switching from static watching patterns to the collaborative discussion. The current deep learning models, such as CNN and RNN, are ineffective in classifying verbal content contextually. Moreover, the contribution of verbal elements to semantics is often considerably varied, requiring the attachment of weights to these elements to increase verbal recognition precision. The Bi-LSTM is considered to be an adaptive model to investigate semantic relations according to the context. Moreover, the attention mechanism in deep learning simulating human vision could assign weights to target texts effectively. This study proposed to construct a deep learning model combining Bi-LSTM and attention mechanism, in which Bi-LSTM obtained the verbal features and keywords, and the generated keywords were weighed in accordance with the attention mechanism. A total of 12,000 sentences generated in online collaborative discussion activities have been classified into six categories, namely statement, negotiation, question, management, emotion and others. Results showed that the classification accuracy of Attention-Bi-LSTM reached 81.50&#x0025;, which is higher than that of the baseline Bi-LSTM model. This study theoretically uncovers the features of collaborative discussion of onliners and practically provides an effective approach to automatic behaviour analysis in an online context. 

Optimising Automatic Text Classification Approach in Adaptive Online Collaborative Discussion - A perspective of Attention Mechanism-Based Bi-LSTM

Exploring the emotional aspect in Learner’s personal annotation colors

This paper describes visitor interaction with an interactive tabletop game on the topic of evolutionary adaptations of social insects that we designed in collaboration with a large American museum. We observed visitors playing the game and talked to them about the experience. The game explores the emergent phenomena of ant behavior. Research has shown that such emergent behavior is difficult for people to understand, and that there are different emergent schemas that work best for understanding these phenomena. We tested the visitors preand post-gameplay and counted the prevalence of visitors expressing direct and emergent schemas of complex processes. We then considered four hypotheses measuring changes between these schemas and found that two groups shifted their schemas. To better understand this change we provide a qualitative overview of the visitors’ interactions. Our exhibit, called Ant Adaptation, takes the form of an agent-based modeling game that integrates complex system learning with gameplay. We video recorded 38 groups (114 participants) playing the game and conducted preand post-gameplay interviews. We coded the groups that contained children for this analysis: 9 groups (27 participants). Our results show that visitors held both emergent and direct schemas before and after play, and three people changed from direct schemas before play to emergent schemas after play. We then examine the process of how one of these groups shifted their schemas.

/pdf/prevalence-of-direct-and-emergent-schema-and-change-after-vnvlsxwidu.pdf

Prevalence of Direct and Emergent Schema and Change after Play.

The purpose of this study was to determine the mediating role of cognitive flexibility in the relationship between emotional intelligence and academic self-regulated learning. Utilizing quantitative, non-experimental design via correlational technique, data were obtained from 267 respondents of the study who are learners among public elementary schools in Cateel 1 and 2, Davao Oriental. The researcher utilized a stratified random sampling technique and an online survey mode of data collection. The researcher also utilized the statistical tools mean, Pearson r, and Medgraph using the Sobel z-test. From the results of the study, it was found that there is a very high level of cognitive flexibility, emotional intelligence, and academic self-regulated learning. Also, results revealed that there is a significant relationship between emotional intelligence and academic self-regulated learning, a significant relationship between emotional intelligence and cognitive flexibility, and a significant relationship between cognitive flexibility and academic self-regulated learning. Further, it was revealed that there is a partial mediating effect of cognitive flexibility on the relationship between emotional intelligence and academic self-regulated learning.  Article visualizations:

pdf/the-mediating-role-of-cognitive-flexibility-on-the-3y2es1xw4g.pdf

The mediating role of cognitive flexibility on the relationship between emotional intelligence and academic self-regulated learning of senior high school students

Collaborative learning involves intricate interactions in which students participate in cognitive activities within social-emotional environments. Cognitive interactions mediate knowledge sharing, construction, and creation, while social-emotional interactions shape student perception of community climate and influence their emotional expressions, which, in turn, have a significant impact on their cognitive interactions. Although research has consistently found that social presence and student-student interaction has a positive influence on students' learning through emotional engagement, subject-based teaching remained largely more of cognitive activities. Teachers tend to treat lessons that heightened social-emotional aspects separate from subject-based lessons. This symposium brings together an international group of scholars to present recent studies on emotion and cognition in collaborative learning environments. Methods, such as self-report, video observation, affective state detection using FACET, and machine learning models, were adopted to investigate students' emotions. The results collectively suggest that these methods indeed served to uncover students' emotions; emotions such as joy/enjoyment/happiness, confidence, and surprise were associated with students' knowledge building progress; and that students' online interactions had a high impact on the emotional and linguistic tone of learners. The symposium aims to discuss the theoretical, practical and policy implications of these studies on collaborative learning. The overall focus of the symposium Collaborative learning describes a situation where particular cognitive and social-emotional forms of interaction among people trigger learning mechanisms (Dillenbourg, 1999). Cognitive interactions mediate knowledge sharing, construction, and creation. Social-emotional interactions shape student perception of community climate and influence their expressions of emotions (Bakhtiar, Webster, & Hadwin, 2017; Järvelä, Järvenoja, Malmberg, Isohätälä, & Sobocinski, 2016). In previous studies, achievement emotions such as anxiety and enjoyment were the most researched emotions (Loderer, Pekrun, & Lester, 2018). However, epistemic emotions such as confusion, curiosity, and surprise, which tend to arise during cognitive activities and the learning generation process (Pekrun & Linnenbrink-Garcia, 2012, 2014) and social emotions triggered by students' interactions in collaborative learning have been rarely researched (Loderer et al., 2018). The study of how students' social and epistemic emotions interplay with students' knowledge construction or knowledge building process is in its infancy. Presentations in this symposium have responded to this question in different learning contexts, using different methods and from different perspectives. Multimodal data can be collected and analyzed using different techniques—including sentiment analysis, facial expression recognition, self-reports, and biosensors—to measure emotions (e.g., Arguedas, Daradoumis, & Xhafa, 2016; Koolagudi & Rao, 2012; Loia & Senatore, 2014). Researchers have explored ways to study socialemotional interactions between students (e.g., Isohätälä, Näykki, & Järvelä, 2019; Sinha, Rogat, Adams-Wiggins, & Hmelo-Silver, 2015). Despite these developments, real contextual constraints in collaborative learning environments (e.g., multiple students, movements during activities) may limit the use of the technologies to ICLS 2020 Proceedings 382 © ISLS measure emotions. The five studies included in this symposium will present different methods used to uncover students' emotions in collaborative learning contexts. The pedagogical implications of these findings are critical in translating this research to impact classroom practice. The overarching points illustrated by the collective work This symposium aims to achieve the following goals: 1. Enhance our awareness of cutting-edge studies on emotion and cognition in collaborative learning environments. 2. Discuss and reflect on the reliability, applicability, and possible limitations of the methods adopted. 3. Advance the theoretical understanding of relations between emotions and cognition. 4. Discuss the practical and policy implications of these studies, such as how to design supportive emotional and cognitive learning environments to foster productive knowledge building and student well-being. The significance of the contributions The five studies in this symposium represent initiatives of understanding how to uncover students' emotions and how emotions interplay with students' knowledge building processes in classrooms, museums, or fully online platforms. Methods, such as self-report, video observation, affective state detection, and machine learning models, were adopted to investigate students' emotions. The results collectively suggest that these methods helped uncover students' emotions; emotions such as joy/enjoyment/happiness, confidence, surprise were associated with students' knowledge building progress; and students' online interactions had a high impact on the emotional and linguistic tone of learners. Furthermore, these studies open areas for further inquiry and provide practical implications-regulating students' socio-cognitive-emotional dynamics to foster productive knowledge building and emotional well-being. For instance, Teo and Ng suggested that Knowledge Building students seemed to be developing some (meta) emotions that had helped them to cope with otherwise a stressful learning experience. In Badron, Teo, and Tan's study, the students themselves indicated that more opportunities for group work, longer thinking time, and usage of videos as additional resources would enhance their learning experience. How the collective presentations contribute towards the issues or points raised In this symposium, an international group of scholars will present recent studies on emotion and cognition in collaborative learning environments, ranging from classrooms to museums, from physical spaces to online communities, and across Western and Asian societies. Also, diverse methods such as speech emotion analysis, data mining, qualitative ethnography, and grounded methodology have been adopted in different studies. Collectively, these studies found that (1) collective reflection design in knowledge building contributed to students' increased enjoyment, curiosity, and surprise; compared to enjoyment, confidence was more highly associated with students' elaborated explanations and proposals of inquiry directions; (2) knowledge aggregation was followed by a higher joy score; (3) as students entered into the 'more difficult' knowledge building activities, more students reported that they felt happy about their knowledge building experience although fewer students reported they wanted to know more about the topics; (4) cogenerative dialogue helped uncover students' emotion engagement and brings about awareness of the potential emotion climate experienced by most students in the class; and (5) during fully online learning, various types of interactions had a high impact on the emotional and linguistic tone of learners. Structure of the session This symposium includes five studies on the relations between emotion and cognition: (1) Collective Reflections, Knowledge Advancement and Emotional Well-being of Young Students; (2) Associations between Emotion and Moments of Learning Studied through Dialogue and Affective State Tracking; (3) Understanding the Academic Emotion of Students in the Knowledge Building Process; (4) Exploring Student's Emotion Engagement and Mediating Change through Cogenerative (cogen) Dialogue; and (5) Towards Understanding Emotional Presence in An Online Community of Inquiry: A Machine Learning Approach. We will use the following session organization: 1. Welcome and introduction by session chairs (3 min) ICLS 2020 Proceedings 383 © ISLS 2. Five presentation and short questions and answers between presenters and audiences (11 min for each presentation, in total 55 min) 3. Synthesis and discussions of common interests and issues by the discussant (Dr. Earl Woodruff) (15min) 4. Open discussion with the audience (17 min) (1) Collective reflections, knowledge advancement and emotional well-being of young students Gaoxia Zhu, Marlene Scardamalia, Raadiyah Nazeem, Zoe Donoahue, Zhixin Lai, and Leanne Ma, University of Toronto Knowledge Building is a pedagogical approach that emphasizes students as epistemic agents taking high-level collective responsibility to work on real ideas/authentic problems as they understand the world (Scardamalia & Bereiter, 2014a). The control-value theory assumes subjective controls and values are specifically relevant to achievement emotions (Pekrun, 2006). Subjective control refers to an agent's perceived causal influence over actions and outcomes (Skinner, 1996). Subjective value describes how important and attractive certain actions and outcomes are to an agent (Pekrun, 2006). Theoretically, Knowledge Building would contribute to students' positive emotions as it emphasizes student agency and values their authentic inquiry directions. Collective reflections on the status of community knowledge and promising future directions for inquiry have shown effectiveness for advancing community knowledge (e.g., Resendes, Scardamalia, Bereiter, Chen, & Halewood, 2015; Zhang et al., 2018). This study investigated how students' increasing epistemic agency and collective responsibility for their work influenced their knowledge building and epistemic and activity emotions. We turned over more epistemic agency to 22 grade 2 students by involving them in collective reflections. Furthermore, students proposed future inquiry directions shaped the subsequent inquiry. Specifically, we aim to answer three questions: 1. How does students' engagement in collective reflection (meta-discourse) influence their activity emotions and epistemic em

Emotional and Cognitive Affordances of Collaborative Learning Environments.

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Emotional and Cognitive Affordances of Collaborative Learning Environments.