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Metacognitive awareness is knowing about learners' own thinking and learning, facilitated by introspection and self-evaluation. Although metacognitive functions are personal, they cannot be explained simply by individual conceptions, especially in a collaborative group learning context. This study considers metacognitive awareness on multiple levels. It investigates how metacognitive awareness at the individual, social, and environmental levels are associated with collaborative problem solving (CPS). Seventy-seven higher education students collaborated in triads on a computer-based simulation about running a fictional company for 12 simulated months. The individual level of metacognitive awareness was measured using the Metacognitive Awareness Inventory. The social level of metacognitive awareness was measured multiple times during CPS through situated self-reports, that is, metacognitive judgements and task difficulty. The environmental level of metacognitive awareness was measured via a complex CPS process so that group members' interactions were video recorded and facial expression data were created by post-processing video-recorded data. Perceived individual and group performance were measured with self-reports at the end of the CPS task. In the analysis, structural equation modelling was conducted to observe the relationships between multiple levels of metacognitive awareness and CPS task performance. Three-level multilevel modelling was also used to understand the effect of environmental-level metacognitive awareness. The results reveal that facial expression recognition makes metacognitive awareness visible in a collaborative context. This study contributes to research on metacognition by displaying both the relatively static and dynamic aspects of metacognitive awareness in CPS.

The current study is based on thematic analysis of 21,722 tweets posted under the #wedontwantdistanceeducation hashtag within a month after the start of online distance education in Turkish universities due to COVID-19 pandemic. Our findings have revealed that Turkish higher education students have faced multiple challenges in accessing and benefiting from online education due to the swift transformation from face-to-face to online format. These challenges included universities' poor technical infrastructure, pedagogical and assessment issues, digital inequality in accessing online education, and general negative attitude towards online education. Further, students have expressed issues about financial, health, and social consequences of online education during COVID-19 pandemic. With regards to such challenges and issues, higher education students have criticized government authorities for ignoring their views when making decisions about how online learning is organized during COVID-19 pandemic. Further, students have offered some alternative solutions (e.g. summer courses) to online education.

This study provides an overview of research on teachers' use of artificial intelligence (AI) applications and machine learning methods to analyze teachers' data. Our analysis showed that AI offers teachers several opportunities for improved planning (e.g., by defining students' needs and familiarizing teachers with such needs), implementation (e.g., through immediate feedback and teacher intervention), and assessment (e.g., through automated essay scoring) of their teaching. We also found that teachers have various roles in the development of AI technology. These roles include acting as models for training AI algorithms and participating in AI development by checking the accuracy of AI automated assessment systems. Our findings further underlined several challenges in AI implementation in teaching practice, which provide guidelines for developing the field.

Being aware of the progress towards one's goals is considered one of the main characteristics of the self-regulation process. This is also the case for collaborative problem solving, which invites group members to metacognitively monitor the progress with their goals and externalize it in social interactions while solving a problem. Monitoring challenges can activate group members to control the situation together, which can be seen as adjustments on different systemic levels (physiological, psychological, and interpersonal) of a collaborative group. This study examines how the pivotal role of monitoring for collaborative problem solving is reflected in interactions, performance, and interpersonal physiology. The study has foci in two central characteristics of monitoring interactions that facilitate groups' regulation in reaching their goals. First is valence of monitoring, indicating whether the group members think they are progressing towards their goal or not. Second is equality of participation in monitoring interactions between group members. Participants of the study were volunteering higher education students (N = 57), randomly assigned to groups of three members whose collaborative task was to learn to run a business simulation. The collaborative task was video recorded, and the physiological arousal of each participant was recorded from their electrodermal activity. The results of the study suggest that both the valence and equality of participation are identifiable in monitoring interactions and they both positively predict groups' performance in the task. Equality of participation to monitoring was not related to the interpersonal physiology. However, valence of monitoring was related to interpersonal physiology in terms of physiological synchrony and arousal. The findings support the view that characteristics of monitoring interactions make a difference to task performance in collaborative problem solving and that interpersonal physiology relates to these characteristics.

Purpose: This study aims to explore Twitter posts of Turkish government agencies and the public under a specific hashtag, #NotHolidayButDistanceEducation, specifically related to online distance education during the COVID-19 pandemic. Design/methodology/approach: This study used a thematic analysis on 22,547 original tweets posted by 6,970 users during the first month of online distance education in Turkish K-12 schools. Based on like and retweet counts, the study further explored the extent of stakeholders' engagement with the observed themes. Findings: The findings showed that government agencies and citizens used Twitter to provide technical and psychological support, appreciate and motivate stakeholders, demonstrate sample distance education activities, share information and offer suggestions about the ongoing online distance education. It was also observed that the hashtag has been used for expressing negative views about online distance education and for political purposes. A positive relationship was found between social media engagement and providing technical support or sharing information for online distance education. Practical implications: This study highlights the role of social media in providing practical and emotional support to education stakeholders in times of crisis. Thus, governments can use social media to provide evidence-based psychological and physical health support to their citizens during a pandemic. Social media can serve to improve education practices in schools through the interactions between the public and policymakers. Originality/value: To the best of the authors' knowledge, this study can be considered unique because it demonstrates the civic use of social media for educational crisis management. This study highlights the influence of social media in educational policy and practice development in the contemporary era.

COVID-19 pandemic has caused a massive transformation in K-12 settings towards online education. It is important to explore the factors that facilitate online teaching technology adoption of teachers during the pandemic. The aim of this study was to compare Learning Management System (LMS) acceptance of Finnish K-12 teachers who have been using a specific LMS as part of their regular teaching before the COVID-19 pandemic (experienced group) and teachers who started using it for emergency remote teaching during the pandemic (inexperienced group). Based on the Unified Theory of Acceptance and Use of Technology framework, a self-report questionnaire was administered to 196 teachers (n[subscript experienced] = 127; n[subscript inexperienced] = 69). Our findings showed no difference between the two groups of teachers in terms of performance expectancy, effort expectancy, LMS self-efficacy and satisfaction. However, the experienced group had higher behavioural intention to use LMS in the future, reported receiving higher online teaching support and displayed higher online teaching self-efficacy in terms of student engagement, classroom management, instructional strategies and ICT skills. For the experienced group, the most significant predictor of satisfaction with LMS was performance expectancy whereas for the inexperienced group, it was the effort expectancy. In terms of behavioural intention to use LMS in the future, the most significant predictor was the performance expectancy for both groups. Further, support was also a significant predictor of behavioural intention for the inexperienced group. Overall, our findings indicate that teachers should not be regarded as a unified profile when managing technology adoption in schools.

Gamification has become a popular approach to blending learning with fun and enjoyable experiences. However, gamification research has been criticized for mostly focusing on game mechanics and related outcomes while paying little attention to the psychological processes that mediate the relationship between these mechanics and outcomes. Furthermore, the majority of existing gamification studies have focused on competitive game features. Thus, the full potential of cooperative gamification has yet to be explored. Given this background, the current study compared how gamified cooperation and competition impact task effort, learning achievement, motivation and social relatedness in English vocabulary learning with a mobile application. The study utilized Social Interdependence Theory to explicate the psychological processes in gamified cooperation and competition. 75 participants were randomly assigned to either the gamified cooperation or the gamified competition condition and studied English vocabulary for 14 days. No difference was observed between the conditions regarding task effort, learning achievement and motivation. However, social relatedness in the gamified cooperation group was significantly higher than in the gamified competition group. The current findings emphasize that the positive influence of gamified cooperation on creating meaningful connections amongst learners should not be ignored, even though it facilitates similar learning and motivational outcomes as gamified competition.

This systematic review on data modalities synthesises the research findings in terms of how to optimally use and combine such modalities when investigating cognitive, motivational, and emotional learning processes. ERIC, WoS, and ScienceDirect databases were searched with specific keywords and inclusion criteria for research on data modalities, resulting in 207 relevant publications. We provide findings in terms of target journal, country, subject, participant characteristics, educational level, foci, type of data modality, research method, type of learning, learning setting, and modalities used to study the different foci. In total, 18 data modalities were classified. For the 207 multimodal publications, 721 occurrences of modalities were observed. The most popular modality was interview followed by survey and observation. The least common modalities were heart rate variability, facial expression recognition, and screen recording. From the 207 publications, 98 focused exclusively on the cognitive aspects of learning, followed by 27 publications that only focused on motivation, while only five publications exclusively focused on emotional aspects. Only 10 publications focused on a combination of cognitive, motivational, and emotional aspects of learning. Our results plea for the increased use of objective measures, highlight the need for triangulation of objective and subjective data, and demand for more research on combining various aspects of learning. Further, rather than researching cognitive, motivational, and emotional aspects of learning separately, we encourage scholars to tap into multiple learning processes with multimodal data to derive a more comprehensive view on the phenomenon of learning.

There is a growing body of research on physiological synchrony (PS) in Collaborative Problem Solving (CPS). However, the current literature presents inconclusive findings about the way in which PS is reflected in cognitive and affective group processes and performance. In light of this, this study investigates the relationship between PS and metacognitive experiences (ie, judgement of confidence, task interest, task difficulty, mental effort and emotional valence) that are manifested during CPS. In addition, the study explores the association between PS and group performance. The participants were 77 university students who worked together on a computer-based CPS simulation in groups of three. Participants' electrodermal activity (EDA) was recorded as they worked on the simulation and metacognitive experiences were measured with situated self-reports. A Multidimensional Recurrence Quantification Analysis was used to calculate the PS among the collaborators. The results show a positive relationship between continuous PS episodes and groups' collective mental effort. No relationship was found between PS and judgement of confidence, task interest, task difficulty or emotional valence. The relationship between PS and group performance was also non-significant. The current work addresses several challenges in utilising multimodal data analytics in CPS research and discusses future research directions.

In collaborative learning situations, monitoring is needed to maintain common progress toward shared goals. The present study aimed to analyze group-level monitoring events, as well as groups' reactions to these events, to identify instances of adaptive regulation and maladaptive behavior. Three dimensions of monitoring events were qualitatively coded from video data: the monitoring target, valence, and phase, which provided insight into identifying critical moments during the collaborative process when regulation is needed. By looking at what kind of monitoring the groups engaged in, and how the groups progressed after the need for regulation arose, different types of adaptive regulation and maladaptive behavior were distinguished. In addition, group-level physiological state transitions in the heart rate were explored to see whether changes in regulation (adaptive regulation and maladaptive behavior) were reflected in the state transitions. Nine groups of three students each participated in a collaborative exam for an advanced high school physics course, during which video and heart rate data were collected. The results showed that on-track sequences were the most common, followed by adaptive sequences. The temporality of these sequences was examined, and four categories of group progress are described with case examples. A correlation analysis showed that physiological state transitions were positively correlated with on-track sequences. The opportunities and limitations of using three dimensions of monitoring and heart-rate based physiological state transitions to study adaptive regulation are discussed.

This study investigated the interplay of temporal changes in self-regulated learning processes (i.e., behavioral, cognitive, motivational and emotional) and their relationship with academic achievement in computer-supported collaborative learning. The study employed electrodermal activity and self-report data to capture the dynamicity of self-regulated learning processes during 15 sessions of collaborative learning activities. Our findings revealed that the changes in motivational regulation was related to academic achievement. However, academic achievement was not related to behavioral regulation, cognitive regulation or emotional regulation. Physiological synchrony among the collaborating students was found to be related only to cognitive regulation. The results also showed that the concordance of self-report data among the collaborating students was related to higher physiological synchrony among them in the behavioral, cognitive, and motivational dimensions of self-regulated learning. The findings reflect the complexity of the relationships between self-regulated learning constructs and demonstrates the potential value of physiological measures in self-regulated learning research.

Effective use of technology in educational environments and its successful integration increases the productivity of instructional processes. Constant and good-quality support supposed to be provided for teachers is quite important for technology use in educational environments. Thus, it is necessary to find answers to the question of what kinds of activities could be used to provide teachers with constant support for technology integration in educational environments. In this respect, the present study aimed at determining teachers' views and their suggestions about the process of technology integration into educational environments and about the problems experienced in the process. In the study, the research sample included a total of 21 teachers teaching at Tepebasi Resat Benli Elementary School in the city of Eskisehir. Of all the participating teachers, 11 of them were elementary school teachers, and 10 of them were field teachers. In order to find answers to the research questions directed in line with the overall purpose of the study, the qualitative research method was applied. The research data were analyzed with the help of thematic analysis. The research data were collected via the focus-group interviews held with the teachers, observations and researcher journals. The data collected in the study were gathered under two main themes depending on the open-ended questions directed to the teachers regarding technology use and on the related literature. These themes were "Problems experienced by teachers regarding technology use in class" and "Suggestions for effective use of technology". (Contains 2 tables.)

This study explored sequential patterns in social interaction states for group-level regulation of learning during collaborative learning. The participants were secondary school students (N = 92) performing collaborative physics tasks. The videotaped sessions were analyzed regarding participation, social interaction, and group-level regulation types of co- and socially shared regulation. The results show that group-level regulation emerged most frequently in social interaction state that included cognitive and socioemotional interaction and whole-group participation, which also led to and followed regulation most frequently. The findings highlight the role of joint participation in social interactions for regulation of learning in collaborative group settings. [ABSTRACT FROM AUTHOR]