Improving Hybrid Brainstorming Outcomes with Scripting and Group Awareness Support

Previous research has shown that hybrid brainstorming, which combines individual and group methods, generates more ideas than either approach alone. However, the quality of these ideas remains similar across different methods. This study, guided by the dual-pathway to creativity model, tested two computer-supported scaffolds – scripting and group awareness support – for enhancing idea quality in hybrid brainstorming. 94 higher education students,grouped into triads, were tasked with generating ideas in three conditions. The Control condition used standard hybrid brainstorming without extra support. In the Experimental 1 condition, students received scripting support during individual brainstorming, and students in the Experimental 2 condition were provided with group awareness support during the group phase in addition. While the quantity of ideas was similar across all conditions, the Experimental 2 condition produced ideas of higher quality, and the Experimental 1 condition also showed improved idea quality in the individual phase compared to the Control condition

A Computational Linguistic Analysis of Learners Discourse in Computer-Mediated Group Learning Environments

Communication, collaboration and the social co-construction of knowledge are now considered critical 21st century skills and have taken a principal role in recent theoretical and technological developments in education research. The overall objective of this dissertation was to investigate collaborative learning to gain insight on why some groups are more successful than others. In such discussions, group members naturally assume different roles. These roles emerge through participants’ interactions without any prior instruction or assignment. Different combinations of these roles can produce characteristically different group outcomes, being either less or more productive towards collective goals. However, there has been little research on how to automatically identify these roles and fuse the quality of the process of collaborative interactions with the learning outcome. A major goal of this dissertation is to develop a group communication analysis (GCA) framework, a novel methodology that applies automated computational linguistic techniques to the sequential interactions of online group communication. The GCA involves computing six distinct measures of participant discourse interaction and behavioral patterns and then clustering participants based on their profiles across these measures. The GCA was applied to several large collaborative learning datasets, and identified roles that exhibit distinct patterns in behavioral engagement style (i.e., active or passive, leading or following), contribution characteristics (i.e., providing new information or echoing given material), and social orientation. Through bootstrapping and replication analysis, the roles were found to generalize both within and across different collaborative interaction datasets, indicating that these roles are robust constructs. A multilevel analysis shows that the social roles are predictive of success, both for individual team members and for the overall group. Furthermore, the presence of specific roles within a team produce characteristically different outcomes; leading to specific hypotheses as to optimal group composition. Ideally, the developed analytical tools and findings of this dissertation will contribute to our understanding of how individuals learn together as a group and thereby advance the learning and discourse sciences. More broadly, GCA provides a framework to explore the intra- and inter-personal patterns indicative of the participants’ roles and the sociocognitive processes related to successful collaboration

Enhancing Free-text Interactions in a Communication Skills Learning Environment

Learning environments frequently use gamification to enhance user interactions.Virtual characters with whom players engage in simulated conversations often employ prescripted dialogues; however, free user inputs enable deeper immersion and higher-order cognition. In our learning environment, experts developed a scripted scenario as a sequence of potential actions, and we explore possibilities for enhancing interactions by enabling users to type free inputs that are matched to the pre-scripted statements using Natural Language Processing techniques. In this paper, we introduce a clustering mechanism that provides recommendations for fine-tuning the pre-scripted answers in order to better match user inputs

Adult Educator Views On Impact And Learner Fit In Integrated Digital English Acceleration (I-Dea) Classrooms

The Integrated Digital English Acceleration (I-DEA) teaching method uses a Flipped Classroom (FC) design to fast-track the English Language Acquisition (ELA) and digital literacy skills development of adults enrolled at Community and Technical Colleges (CTCs) and Community-Based Organizations (CBOs) in the United States. I-DEA projects and programs are in various stages of implementation throughout the U.S., but few accounts of the method’s impact on teaching and learning and fit for adult English language learners (ELLs) have been published. I-DEA is a “flipped” (blended) instructional delivery method for Adult Basic Education (ABE). Evaluation of its impact and fit contributes to the literature on Flipped Classrooms, Computer-Assisted Language Learning (CALL), and Integrated Education and Training (IET). To evaluate the I-DEA method’s impact and fit, an online questionnaire was administered to current and former I-DEA instructors in the United States. Respondents (n=8) provided Likert scale ratings of agreement or disagreement, along with written responses to explain their rating selections. Instructors overwhelmingly agreed that the I-DEA method’s FC design has helped students acquire English at a faster pace than they would in non-I-DEA classes. Support for the method’s learner fit was not as robust: Fifty percent of the sample group voiced concerns about the linguistic complexity of its lessons for beginners (NRS 1 & 2). The results of this small-scale, mixed-methods study provide evidence to support claims about the I-DEA method’s impact, while raising new questions about its fit for adult ELL beginners. Our findings suggest that the Flipped Classroom may be most impactful and suitable for English learners in High Beginner (NRS 3) classrooms. Modifications to IDEA lessons are recommended for classrooms with NRS 1 and 2 level students. Further study, including action research in I-DEA classrooms, is recommended

Promoting Andean children's learning of science through cultural and digital tools

Conference Theme: To see the world and a grain of sand: Learning across levels of space, time, and scaleIn Peru, there is a large achievement gap in rural schools. In order to overcome this problem, the study aims to design environments that enhance science learning through the integration of ICT with cultural artifacts, respecting the Andean culture and empower rural children to pursue lifelong learning. This investigation employs the Cultural-Historical Activity Theory (CHAT) framework, and the Design-Based Research (DBR) methodology using an iterative process of design, implementation and evaluation of the innovative practice.published_or_final_versio

Analysing, visualising and supporting collaborative learning using interactive tabletops

The key contribution of this thesis is a novel approach to design, implement and evaluate the conceptual and technological infrastructure that captures student’s activity at interactive tabletops and analyses these data through Interaction Data Analytics techniques to provide support to teachers by enhancing their awareness of student’s collaboration. To achieve the above, this thesis presents a series of carefully designed user studies to understand how to capture, analyse and distil indicators of collaborative learning. We perform this in three steps: the exploration of the feasibility of the approach, the construction of a novel solution and the execution of the conceptual proposal, both under controlled conditions and in the wild. A total of eight datasets were analysed for the studies that are described in this thesis. This work pioneered in a number of areas including the application of data mining techniques to study collaboration at the tabletop, a plug-in solution to add user-identification to a regular tabletop using a depth sensor and the first multi-tabletop classroom used to run authentic collaborative activities associated with the curricula. In summary, while the mechanisms, interfaces and studies presented in this thesis were mostly explored in the context of interactive tabletops, the findings are likely to be relevant to other forms of groupware and learning scenarios that can be implemented in real classrooms. Through the mechanisms, the studies conducted and our conceptual framework this thesis provides an important research foundation for the ways in which interactive tabletops, along with data mining and visualisation techniques, can be used to provide support to improve teacher’s understanding about student’s collaboration and learning in small groups

The student-produced electronic portfolio in craft education

The authors studied primary school students’ experiences of using an electronic portfolio in their craft education over four years. A stimulated recall interview was applied to collect user experiences and qualitative content analysis to analyse the collected data. The results indicate that the electronic portfolio was experienced as a multipurpose tool to support learning. It makes the learning process visible and in that way helps focus on and improves the quality of learning. © ISLS.Peer reviewe