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This paper presents an implementation of Connected Spaces (CxS)—an ambient help seeking interface designed and developed for a project‐based computing classroom. We use actor network theory (ANT) to provide an underutilized posthumanist lens to understand the creation of collaborative connections in this Computational Action‐based implementation. Posthumanism offers an emerging and critical extension to sociocultural perspectives on understanding learning, by pushing us to decenter the human, and consider the active roles that human and non‐human entities play in learning environments by actively shaping each other. We analyse how students in this class adjusted their help‐seeking and collaborative habits following the introduction of CxS, a tool designed to foster (more inter‐group) collaboration. ANT proposes generalized symmetry—a principle of considering human, non‐human and more than human entities with equivalent and comparable agency, leading to describing phenomena as networks of actors in different evolving relationships with each other. Analysing collaborative interactions as fostered by CxS using an ANT approach supports design‐based research—an iterative design revision process highlighting understandings about design as well as learning—by providing a temporal and informative lens into the relationship between actors and tools within the environment. Our key findings include a framing of technologies in classrooms as bridging agentic gaps between students and becoming actors engaging in different behaviours; learners enacting new agencies through technologies (for instance a more comfortable non‐intrusive help seeker), and the need for voicing and teachers to connect help networks in CxS equipped classrooms. Practitioner notesWhat is already known about this topic Collaborative learning is a valuable skill and practice; opportunities to mentor others are critical in empowering minoritized learners, especially in STEM and computing disciplines.School norms solidify a power and expertise hierarchy between teachers and learners and fail to productively support learners in learning from each other.Additionally, lack of awareness about peers' knowledge is a common hindrance in students knowing who to ask for help and how.What this paper adds An example of a designed interface called Connected Spaces with potential to foster more inter‐student collaboration, especially outside of mandated within‐group collaboration—in the form of cross‐group help seeking and help giving.A design based research study using actor network theory highlighting the limitations of Connected Spaces in sparking notable behaviour change among students by itself but being retooled as a teacher support tool in enabling cross‐group collaborations.Presenting conceptions of collaboration through technologies as bridging agentic gaps and acting with new agencies in performing help‐seeking related actions.Provoking the idea of testing emerging technologies in classrooms along with sharing our analyses and reflections with the classroom as a key idea in computing education—surfacing the gap between designed intentions and the different kinds of extra social work needed in the on‐ground success of different technologies.Implications for practice and/or policy Designers and researchers should create and test more interfaces alongside teachers across different classrooms and contexts aimed at supporting different kinds of voluntary collaborative interactions.Curricula, standards and school practices should further center providing students with opportunities to engage as mentors and build communities of learning across disciplines to empower minoritized students.Researchers engaging in design based research should consider using more posthumanist lenses to examine educational technologies and how they affect change in learning environments. [ABSTRACT FROM AUTHOR]

Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes. The recent development of trace‐based assessment has enabled innovative opportunities to overcome the problem. Despite the potential of a trace‐based approach to study SSRL, there remains a paucity of evidence on how trace‐based evidence could be captured and utilised to assess and promote SSRL. This study aims to investigate the assessment of electrodermal activities (EDA) data to understand and support SSRL in collaborative learning, hence enhancing learning outcomes. The data collection involves secondary school students (N = 94) working collaboratively in groups through five science lessons. A multimodal data set of EDA and video data were examined to assess the relationship among shared arousals and interactions for SSRL. The results of this study inform the patterns among students' physiological activities and their SSRL interactions to provide trace‐based evidence for an adaptive and maladaptive pattern of collaborative learning. Furthermore, our findings provide evidence about how trace‐based data could be utilised to predict learning outcomes in collaborative learning. Practitioner notesWhat is already known about this topic Socially shared regulation has been recognised as an essential aspect of collaborative learning success.It is challenging to make the processes of learning regulation 'visible' to better understand and support student learning, especially in dynamic collaborative settings.Multimodal learning analytics are showing promise for being a powerful tool to reveal new insights into the temporal and sequential aspects of regulation in collaborative learning.What this paper adds Utilising multimodal big data analytics to reveal the regulatory patterns of shared physiological arousal events (SPAEs) and regulatory activities in collaborative learning.Providing evidence of using multimodal data including physiological signals to indicate trigger events in socially shared regulation.Examining the differences of regulatory patterns between successful and less successful collaborative learning sessions.Demonstrating the potential use of artificial intelligence (AI) techniques to predict collaborative learning success by examining regulatory patterns.Implications for practice and/or policy Our findings offer insights into how students regulate their learning during collaborative learning, which can be used to design adaptive supports that can foster students' learning regulation.This study could encourage researchers and practitioners to consider the methodological development incorporating advanced techniques such as AI machine learning for capturing, processing and analysing multimodal data to examine and support learning regulation. [ABSTRACT FROM AUTHOR]

Conversational agents can deepen reasoning and encourage students to build on others' knowledge in collaborative learning. Embedding agents in group work, however, presents challenges where groups may ignore the agents, and this calls for designs where students perceive agents as learning partners. This study examines group interactions with two text‐based agents (ie, chatbots) that posed as an expert and a less knowledgeable peer in a high school marine biology lesson. Student messages (N = 1764) from 18 groups (52 students ages 14–15) received codes for reasoning, building on prior ideas, and responsiveness to the agents. Results indicate no differences between agents in how often each discussion move occurred. Interestingly, sequential pattern mining suggests that the less‐knowledgeable‐peer agent prompted groups to show questioning and building on others' ideas, similar to how students may act as peer tutors to the agent. Meanwhile, sequences with the expert agent resembled student‐teacher exchange, where groups responded to the agent's nudges and then provided reasoning. Findings illustrate the affordances of embedding humanized features in technology designs to promote discussion. Practitioner notesWhat is already known about this topic Conversational agents can facilitate group discussions, but can get abused or ignored by student groups.To engage students, agent designs can simulate the characteristics of familiar classroom figures, such as peers or teachers.There are limited explorations of how student groups adapt their interactions to different agent designs in collaborative settings.What the paper adds Illustrations of the utilities of diversifying agent designs in collaborative learning.Insights into the unique interaction patterns that student groups displayed to different designs, such as questioning and building on others' ideas with a less‐knowledgeable‐peer agent.Implications for practice and/or policy Embedding signs of humanness in classroom facilitation and technology design can foster responsiveness among users.Pedagogy can consider adaptive designs to promote interaction sequences that contribute to learning (eg, questioning, expanding on prior ideas) at opportune moments. [ABSTRACT FROM AUTHOR]