An official website of the United States government
Computer-Supported Collaborative Learning (CSCL) environments are often designed to support collaboration within a single digital platform. However, with the growth of technology in classrooms, students often find themselves working in multiple contexts (i.e., a student might work face-to-face with a peer on one task and then move to engaging in an online discussion for homework). We have created a CSCL environment that aims to support student help-giving across a variety of digital platforms. This paper describes three cycles of a design-based research study that aims to design a system to support help-giving and improve interaction quantity and quality across different contexts as well as to better understand whether students benefit by the addition of multiple contexts. The paper shares major refinements across the three cycles that worked to balance research, pedagogical, and technological goals to improve students’ help-giving behavior in a middle-school mathematics classroom.
more »
« less
Investigating Help-Giving Behavior in a Cross-Platform Learning Environment
A key promise of adaptive collaborative learning support is the ability to improve learning outcomes by providing individual students with the help they need to collaborate more effectively. These systems have focused on a single platform. However, recent technology-supported collaborative learning platforms allow students to collaborate in different contexts: computer-supported classroom environments, network based online learning environments, or virtual learning environments with pedagogical agents. Our goal is to better understand how students participate in collaborative behaviors across platforms, focusing on a specific type of collaboration - help-giving. We conducted a classroom study (N = 20) to understand how students engage in help-giving across two platforms: an interactive digital learning environment and an online Q&A community. The results indicate that help-giving behavior across the two platforms is mostly influenced by the context rather than by individual differences. We discuss the implications of the results and suggest design recommendations for developing an adaptive collaborative learning support system that promotes learning and transfer.
more »
« less
- Award ID(s):
- 1912044
- PAR ID:
- 10105663
- Date Published:
- Journal Name:
- International Conference of Artificial Intelligence in Education
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
With the growing integration of technology in the classrooms, learners can now develop collaboration skills by applying them across diverse contexts. While this represents a great opportunity, it also brings challenges due to an increased need to support individual learners across multiple learning activities. We propose a technology-enhanced learning ecosystem called UbiCoS that supports learner help-giving during face-to-face collaboration and across three different digital learning environments: an interactive digital textbook, an online Q&A forum, and a teachable agent. In this paper, we present a first step in the development of UbiCoS: five co-design sessions with 16 learners that give insight into learners’ perceptions of help-giving. The findings provided us with technology-related and curriculum-related design opportunities for facilitating learner interaction across multiple platforms.more » « less
-
null (Ed.)Today’s classrooms are remarkably different from those of yesteryear. In place of individual students responding to the teacher from neat rows of desks, one more typically finds students working in groups on projects, with a teacher circulating among groups. AI applications in learning have been slow to catch up, with most available technologies focusing on personalizing or adapting instruction to learners as isolated individuals. Meanwhile, an established science of Computer Supported Collaborative Learning has come to prominence, with clear implications for how collaborative learning could best be supported. In this contribution, I will consider how intelligence augmentation could evolve to support collaborative learning as well as three signature challenges of this work that could drive AI forward. In conceptualizing collaborative learning, Kirschner and Erkens (2013) provide a useful 3x3 framework in which there are three aspects of learning (cognitive, social and motivational), three levels (community, group/team, and individual) and three kinds of pedagogical supports (discourse-oriented, representation-oriented, and process-oriented). As they engage in this multiply complex space, teachers and learners are both learning to collaborate and collaborating to learn. Further, questions of equity arise as we consider who is able to participate and in which ways. Overall, this analysis helps us see the complexity of today’s classrooms and within this complexity, the opportunities for augmentation or “assistance to become important and even essential. An overarching design concept has emerged in the past 5 years in response to this complexity, the idea of intelligent augmentation for “orchestrating” classrooms (Dillenbourg, et al, 2013). As a metaphor, orchestration can suggest the need for a coordinated performance among many agents who are each playing different roles or voicing different ideas. Practically speaking, orchestration suggests that “intelligence augmentation” could help many smaller things go well, and in doing so, could enable the overall intention of the learning experience to succeed. Those smaller things could include helping the teacher stay aware of students or groups who need attention, supporting formation of groups or transitions from one activity to the next, facilitating productive social interactions in groups, suggesting learning resources that would support teamwork, and more. A recent panel of AI experts identified orchestration as an overarching concept that is an important focus for near-term research and development for intelligence augmentation (Roschelle, Lester & Fusco, 2020). Tackling this challenging area of collaborative learning could also be beneficial for advancing AI technologies overall. Building AI agents that better understand the social context of human activities has broad importance, as does designing AI agents that can appropriately interact within teamwork. Collaborative learning has trajectory over time, and designing AI systems that support teams not just with a short term recommendation or suggestion but in long-term developmental processes is important. Further, classrooms that are engaged in collaborative learning could become very interesting hybrid environments, with multiple human and AI agents present at once and addressing dual outcome goals of learning to collaborate and collaborating to learn; addressing a hybrid environment like this could lead to developing AI systems that more robustly help many types of realistic human activity. In conclusion, the opportunity to make a societal impact by attending to collaborative learning, the availability of growing science of computer-supported collaborative learning and the need to push new boundaries in AI together suggest collaborative learning as a challenge worth tackling in coming years.more » « less
-
Purpose The authors explored shifts in social interactions, content engagement and history learning as students who were studying one pandemic simultaneously experienced another. This paper aims to understand how the Net.Create network visualization tool would support students as they tried to understand the many complex interactions in a historical text in a remote learning environment and how sustained knowledge building using Net.Create would shape student attitudes toward remote learning, collaboration and engagement. Design/methodology/approach This paper explores changes in engagement and learning in a survey-level history course on the black death after a shift to remote learning during the COVID-19 pandemic. The authors used activity theory to focus the adaptation of Net.Create, a web-based collaborative social-network-analysis tool and to understand how it supported group-based remote learning. The authors describe how the redesigned activities sustained engagement with historical content and report coded student network entries, reading responses and surveys to illustrate changes in engagement and learning. Findings The results suggest that students benefit from personal connections to historical content and their peers. Net.Create supported both through collaborative knowledge-building activities and reflection on how their quarantine experiences compared to the historical content they read. It is possible to avoid student frustrations with traditional “group work” even in a remote environment by supporting collaborative learning using Net.Create and a mix of individual and group contributions. Originality/value This is the first use of a collaborative network visualization tool to support large classroom interaction and engagement with history content at the undergraduate level.more » « less
-
Abstract While there is increased interest in using movement and embodiment to support learning due to the rise in theories of embodied cognition and learning, additional work needs to be done to explore how we can make sense of students collectively developing their understanding within a mixed-reality environment. In this paper, we explore embodied communication’s individual and collective functions as a way of seeing students’ learning through embodiment. We analyze data from a mixed-reality (MR) environment: Science through Technology Enhanced Play (STEP) (Danish et al., International Journal of Computer-Supported Collaborative Learning 15:49–87, 2020), using descriptive statistics and interaction analysis to explore the role of gesture and movement in student classroom activities and their pre-and post-interviews. The results reveal that students appear to develop gestures for representing challenging concepts within the classroom and then use these gestures to help clarify their understanding within the interview context. We further explore how students collectively develop these gestures in the classroom, with a focus on their communicative acts, then provide a list of individual and collective functions that are supported by student gestures and embodiment within the STEP MR environment, and discuss the functions of each act. Finally, we illustrate the value of attending to these gestures for educators and designers interested in supporting embodied learning.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1007/978-3-030-23204-7_2
