International Journal of Computer-Supported Collaborative Learning

How children blend feedback in a mixed-reality environment for collective embodied learning

1 week ago
With the rapid development of emerging technologies in education, this research explored how children use teacher-, peer-, and technology-provided feedback together toward collective and embodied learning in a mixed-reality environment. In this study, we investigated how young children interact with feedback in a mixed-reality environment, Science through Technology Enhanced Play (STEP), a system that tracks students’ movement and turns their embodiments into characters on a shared screen. We used coding and interaction analysis to analyze data from three episodes from a curriculum about states of matter across two research sites. Our analysis demonstrated that as the curriculum progressed, children engaged with collective and blended feedback, i.e., input that leads to collective sense-making and liminal blending of multiple sources, in ways that enhanced collective agency over their inquiry. First, we focused on how children transitioned from individualized views of feedback to more collective views by blending multiple sources of feedback (from self, peers, teachers/researchers, and technology) to make sense of solid bonds. Second, we found that the children leveraged feedback from their peers, facilitators, and technology-provided representations to explore how the particles must behave collectively to form liquid bonds. Third, we saw how children engaged with feedback differently on the basis of their role (observing versus embodying) in an activity focused on making gas bonds. More than simply demonstrating the sophistication with which young children engage in collective inquiry-based learning through embodied and technology-enhanced play designs, our work also demonstrates how future learning environments with complex feedback structures (i.e., the coordination of multiple sources and multiple modalities by children working collaboratively) can be designed to support student inquiry and young children’s agency in blending feedback sources that they determine enhance their collective sense-making.

Collaboration in virtual and remote laboratories for education: A systematic literature review

2 months ago
Hands-on laboratories are essential to acquire skills in education. However, they can be costly, lack flexibility, and do not allow one to do an unlimited number of experiments. Virtual and remote laboratories represent an interesting alternative to traditional hands-on lab sessions. On the other hand, fostering collaboration between learners and between learners and teachers is an important aspect to develop in these virtual and remote laboratories, as it enhances learning. This systematic literature review presents an extensive overview of previous research about fostering collaboration in educational virtual and remote laboratories. Results of this study show that communication and group awareness tools are generally well integrated into remote and virtual laboratories. These tools foster collaborative learning as they enable users to communicate, to be aware of the presence and the actions of the other members of the group and to share knowledge. However, tools for guiding and regulating collaboration are poorly integrated in the laboratories. These tools are yet useful to foster collaborative learning as they respectively give instructions to collaborate effectively and information about the state of collaboration to regulate it. This review also identified a minority of studies that assessed the quality of collaboration and learning in laboratories. Future research should put more emphasis in investigating guidance and regulation tools, as well as integrating studies to evaluate collaboration and learning in educational remote and virtual laboratories.

Accomplishing collaboration at scale: How professionals jointly frame problems on Stack Overflow

2 months 3 weeks ago
This study investigates how collaboration is practically accomplished on large-scale online platforms, with scale understood qualitatively as asynchronous and fluid participation. Using Stack Overflow as an empirical case, it specifically examines how users collaboratively frame programming problems through questions, comments and iterative edits. Drawing on the practice-based perspective and ethnomethodology, the study uses trace ethnography and sequential analysis of selected Stack Overflow threads. Findings reveal that profession-specific shared objects (minimal reproducible examples) structured within the platform’s dual-space design, consisting of distinct question and commenting spaces, serve as crucial resources, enabling both immediate and future unknown contributors to understand and effectively engage in problem faming and problem-solving processes. Furthermore, the study identifies key interactional methods, i.e., standardized norm-enforcing requests and explicit referencing, which ensure mutual intelligibility of users’ comments and edits, essential for accomplishing collaboration at scale. The findings contribute to theoretical understandings of mass collaboration, offer design insights for platforms to facilitate the coordination of collaborative activities and provide recommendations for professional education to support productive participation in large-scale collaboration.

Optimizing group formation with a mixed genetic algorithm: an empirical study in active reading using marker data

3 months ago
Effective group formation is an indispensable yet challenging aspect of classroom-based collaborative learning. While existing group formation algorithms show promising computational performance in controlled settings, their practical impact on diverse, real-world classrooms remains underexplored. This paper presents a mixed genetic algorithm integrated into a data-driven learning platform designed to accommodate both homogeneous and heterogeneous student characteristics simultaneously. Implemented in a senior high school EFL classroom, the approach leverages active reading marker logs for data-driven grouping. It incorporates a WordCloud tool to enhance educators’ and learners’ understanding of group composition. Empirical results indicate that this system improves vocabulary learning, and the marker-based grouping strategies positively influence group learning dynamics. These findings underscore the algorithm’s practical relevance and highlight the benefits of interpretable, adaptive group formation methods for authentic educational contexts.