International Journal of Computer-Supported Collaborative Learning

Improving learning and writing outcomes: Influence of cognitive and behavioral group awareness tools in wikis

1 month 3 weeks ago
Abstract

Group awareness (GA) tools can facilitate learning processes and outcomes by visualizing different social attributes, such as cognitive and behavioral information about group members. To assist learning and writing in social media, combining various types of awareness information may foster learning processes due to challenges, which are difficult to address by one type of GA information alone. The systematic investigation of GA tool combinations is largely unexplored with GA information often being examined separately or intermixed. To reveal both positive and negative (interaction) effects of providing different types of GA information, we conducted a 2 × 2 between-subjects experiment with N = 158 participants. Learners were provided with a wiki learning environment and, except for the control condition, different types of GA tools involving cognitive (knowledge bars) and/or behavioral (participation bars) GA information. GA tool effects were considered at wiki selection, discussion, and article levels. Eye-tracking was used for investigating the attentional effect of the GA visualizations. The results show that both types of GA information have effects on individuals’ selection preference, more strongly with the goal to learn new content than to support other wiki collaborators, which were introduced as within goal scenarios. Also, participants provided with behavioral GA support were more engaged in wiki contributions. However, only the combination of cognitive and behavioral GA information, rather than their separate visualization, had a positive effect on resulting article quality. This highlights the need for a holistic perspective when developing GA tools to improve wiki processes and outcomes.

Net.Create: Network Visualization to Support Collaborative Historical Knowledge Building

1 month 3 weeks ago
Abstract

Students across disciplines struggle with sensemaking when they are faced with the need to understand and analyze massive amounts of information. This is particularly salient in the disciplines of both history and data science. Our approach to helping students build expertise with complex information leverages activity theory to think about the design of a classroom activity system integrated with the design of a collaborative open-source network-analysis software tool called Net.Create. Through analysis of network log data as well as video data of students’ collaborative interactions with Net.Create, we explore how our activity system helped students reconcile common contradictions that create barriers to dealing with complex datasets in large lecture classrooms. Findings show that as students draw on details in a historical text to collaboratively construct a larger network, they begin to move more readily between small detail and aggregate overview. Students at both high and low initial skill levels were able to increase the complexity of their historical analyses through their engagement with the Net.Create tool and activities. Net.Create transforms the limitation of large class sizes in history classrooms into a resource for students’ collaborative knowledge building, and through collaborative data entry it supports the historiographic practices of citation and revision and helps students embed local historical actors into a larger historical context.

Initiating scientific collaborations across career levels and disciplines – a network analysis on behavioral data

1 month 3 weeks ago
Abstract

Collaborations are essential in research, especially in answering increasingly complex questions that require integrating knowledge from different disciplines and that engage multiple stakeholders. Fostering such collaboration between newcomers and established researchers helps keep scientific communities alive while opening the way to innovation. But this is a challenge for scientific communities, especially as little is known about the onset of such collaborations. Prior social network research suggests that face-to-face interaction at scientific events as well as both network-driven selection patterns (reciprocity and transitivity) and patterns of active selection of specific others (homophily / heterophily) may be important. Learning science research implies, moreover, that selecting appropriate collaboration partners may require group awareness. In a field study at two scientific events on technology-enhanced learning (Alpine Rendez-Vous 2011 and 2013) including N = 5736 relations between 287 researchers, we investigated how researchers selected future collaboration partners, looking specifically at the role of career level, disciplinary background, and selection patterns. Face-to-face contact was measured using RFID devices. Additionally, a group awareness intervention was experimentally varied. Data was analyzed using RSiena and meta-analyses. The results showed that transitivity, reciprocity and contact duration are relevant for the identification of new potential collaboration partners. PhD students were less often chosen as new potential collaboration partners, and researchers with a background in Information Technology selected fewer new potential collaboration partners. However, group awareness support balanced this disciplinary difference. Theoretical, methodological, and practical implications of these findings are discussed.

Guidance in computer-supported collaborative inquiry learning: Capturing aspects of affect and teacher support in science classrooms

1 month 3 weeks ago
Abstract

Technology-enhanced collaborative inquiry learning has gained a firm position in curricula across disciplines and educational settings and has become particularly pervasive in science classrooms. However, understanding of the teacher’s role in this context is limited. This study addresses the real-time shifts in focus and distribution of teachers’ guidance and support of different student groups during in-person computer-supported collaborative inquiry learning in science classrooms. Teachers’ self-perceptions of their guidance and affect were supplemented with students’ self-reported affect. A mixed-methods approach using video analyses and questionnaire data revealed differences between teacher guidance and support associated with teacher perceptions and group outcomes. Groups’ prior science competence was not found to have an effect on teacher guidance and support, rather the teachers guided the groups they perceived as motivated and willing to collaborate. Teacher affect was compounded by student affect, suggesting that consideration of the reciprocal perceptions of teachers and students is necessary in order to understand the teachers’ role in collaborative learning.

Social sensitivity: a manifesto for CSCL research

1 month 3 weeks ago
Abstract

Technologies for computer-supported collaborative learning (CSCL) are playing an increasingly prominent role in educational contexts, especially as teachers and students strive to deal with pandemic-related constraints. However, the technologies being used for collaboration on a daily basis are not sufficiently equipped to promote collaborative learning as both a cognitive and a socio-emotional process. They may even run the risk of hindering the constructive exchange of ideas and provoking disputes and negative encounters. In this squib, we argue that the field of CSCL is failing to address this risk, because our research efforts are far too scattered and siloed. We introduce a manifesto of social sensitivity: increasing interdisciplinary efforts to enhance constructively critical, respectful, and cohesive collaborations in technology-supported environments. We call for concrete actions in CSCL research that ultimately contribute to more democratic and equitable collaborations.