Andrew Clayphan

Firestorm: a brainstorming application for collaborative group work at tabletops

The tabletop computer interface has the potential to support idea generation by a group using the brainstorming technique. This paper describes the design and implementation of a table-top brainstorming system. To gain insights into its effectiveness, we conducted a user study which compared our system against a more conventional approach. We analysed the processes and results with the goal of gaining an understanding of the ways a tabletop brainstorming system can support the phases of this activity. We found that our tabletop interface facilitated the creation of more ideas and participants tended to create more categories. We observed that the tabletop provides a useful record of the group processes and this is valuable for reviewing how well a group followed recommended brainstorming processes. Our contributions are a new table-top brainstorming system and insights into the nature of the benefits a tabletop affords for brainstorming and for capturing the processes employed by a group.

An in-the-wild study of learning mid-air gestures to browse hierarchical information at a large interactive public display

This paper describes the design and evaluation of our Media Ribbon, a large public interactive display for browsing hierarchical information, with mid-air gestures. Browsing a hierarchical information space is a fundamental form of interaction. Designing learnable mid-air gestures is a current challenge for large display interaction. Our in-the-wild evaluation draws on 41 days of quantitative log data, with 4484 gestures detected, and qualitative data from 15 interviews, and associated video. We explored: whether our design enabled people to learn the gestures; how our tutorial and feedback mechanisms supported learning; and the effectiveness of support for browsing hierarchical information. Our contributions are: (1) design of large public display for browsing of hierarchical information; (2) with its gesture set; (3) insights into the ways people learn and use this interface in our context; and (4) guidelines for designing learnable mid-air gestures.

Seamless and continuous user identification for interactive tabletops using personal device handshaking and body tracking

Touch-based tabletops are a form of embedded device for group collaboration. This work tackles two key problems for effective use of such tabletops: there is currently no easy way for people to identify themselves to the table; and most current hardware does not link a persons touches to their identity. This paper presents a system which tackles these problems as it can identify users and keeps track of their actions around interactive tabletops. To start the user identification, a user puts their personal device onto the interactive surface. Once this is paired with the tabletop, linking the device owners identity to the table, the system continuously tracks any touch by that user. The system seamlessly and continuously associates each user touch with an identity.

ScriptStorm: scripting to enhance tabletop brainstorming

Brainstorming is a widely used method for enhancing creativity. Interactive tabletops offer promise for making brainstorming more effective. This is because tabletops should help collocated people collaborate in natural round-table discussions at a shared digital space. However, tabletops have not been found in and of themselves to improve collaboration. This paper explores how to adapt an approach called scripted collaboration to enhance the effectiveness of tabletop brainstorming. We describe the design and implementation of ScriptStorm in two forms: fixed scripting, where the table enforces a set script that the brainstorming participants cannot alter, in the spirit of a human facilitator; and participant-defined scripting, where the interface gives participants control over the script settings. We hypothesised that: the additional interface complexity of the scripting is acceptable in terms of learning time and usability (H1-usability); both forms of scripting support effective brainstorming (H2-effectiveness); people consider that both forms of scripting help them learn about how to brainstorm (H3-learning); and people would prefer participant-defined scripting for the control it gave them over the script (H4-control). We conducted a user study to evaluate these hypotheses. Our results give support to all four hypotheses, although the relative benefits of fixed scripting and participant-defined scripting are nuanced. Our key contributions are insights into two ways that scripted collaboration can support brainstorming, pointing to the potential benefits of fixed scripting and participant-defined scripting for other classes of collaborative tabletop activities.

Integrating orchestration of ubiquitous and pervasive learning environments

Ubiquitous and pervasive computing devices, such as interactive tabletops, whiteboards, tablets and phones, have the potential to enhance the management and awareness of learning activities in important ways. They provide students with natural ways to interact with collaborators, and can help teachers create and manage learning tasks that can be carried out both in the classroom and at a distance. But how can these emerging technologies be successfully integrated into current teaching practice? This paper proposes an approach to integrate, from the technological perspective, collaborative learning activities using these kinds of devices. Our approach is based on the concept of orchestration, which tackles the critical task for teachers to coordinate students learning activities within the constraints of authentic educational settings. Our studies within authentic learning settings enabled us to identify three main elements that are important for ubiquitous and pervasive learning settings. These are i) regulation mechanisms, ii) interconnection with existing web-based learning environments, and iii) awareness tools.

Multi-touch technology in a higher-education classroom: lessons in-the-wild

Inspired by the promise of tabletops for collaborative learning, and building on the many tabletop lab studies, and a few in-the-wild tabletop classrooms, we designed the first semester-long use of a multi-tabletop classroom for two university subjects, with 105 and 40 students respectively. Surprisingly, we found that with just three applications, designed to meet emerging teaching goals, we could support diverse classroom activities. Our technology also featured key minimalist functions that proved effective in enhancing the teachers management of the class. This points to a research agenda for the applications and functionalities needed to make tabletop classrooms a reality. This paper describes the design process we followed to deploy multi-touch technology as a classroom ecology and the lessons learnt from the semester-long use in two authentic university courses.

An approach for designing and evaluating a plug-in vision-based tabletop touch identification system

Key functionality for interactive tabletops to provide effective collaboration affordances requires touch identification, where each touch is matched to the right user. This can be valuable to provide adaptive functions, personalisation of content, collaborative gestures and capture of differentiated interaction for real-time or further analysis. While there is increased attention on touch-identification mechanisms, currently there is no developed solution to readily enhance available tabletop hardware to include such functionality. This paper proposes a plug-in system that adds touch identification to a conventional tabletop. It also presents an analysis tool and the design of an evaluation suite to inform application designers of the effectiveness of the system to differentiate users. We illustrate its use by evaluating the solution under a number of conditions of: scalability (number of users); activity density; and multi-touch gestures. Our contributions are: (1) an off-the-shelf system to add user differentiation and tracking to currently available interactive tabletop hardware; and (2) the foundations for systematic assessment of touch identification accuracy for vision-based systems.

Open Learner Models to Support Reflection on Brainstorming at Interactive Tabletops

Brainstorming is a widely-used group technique to enhance creativity. Interactive tabletops have the potential to support brainstorming and, by exploiting learners’ trace data, they can provide Open Learner Models (OLMs) to support reflection on a brainstorming session. We describe our design of such OLMs to enable an individual to answer core questions: C1) how much did I contribute? C2) at what times was the group or an individual stuck? and C3) where did group members seem to ‘spark’ off each other? We conducted 24 brainstorming sessions and analysed them to create brainstorming models underlying the OLMs. Results indicate the OLM’s were effective. Our contributions are: i) the first OLMs supporting reflection on brainstorming; ii) models of brainstorming that underlie the OLMs; and iii) a user study demonstrating that learners can use the OLMs to answer core reflection questions.

Towards Providing Notifications to Enhance Teacher’s Awareness in the Classroom

Students often need prompt feedback to make the best from the learning activities. Within classrooms, being aware of students’ achievements and weaknesses can help teachers decide how to time feedback. However, they usually cannot easily assess student’s progress. We present an approach to generate automated notifications that can enhance teacher’s awareness in runtime. This paper formulates the theoretical framing and describes the technological infrastructure of a system that can help teachers orchestrate learning activities and monitor small groups in a multi-tabletop classroom. We define the design guidelines underpinning our system, which include: i) generating notifications from teacher-designed or AI-based sources; ii) enhancing teacher’s awareness in the orchestration loop; iii) presenting both positive and negative notifications; iv) allowing teachers to tune the system; and v) providing a private teacher’s user interface. Our approach aims to guide research on ways to generate notifications that can help teachers drive their attention and provide relevant feedback for small group learning activities in the classroom.

Computational inference of grammars for larger-than-gene structures from annotated gene sequences

MOTIVATION Larger than gene structures (LGS) are DNA segments that include at least one gene and often other segments such as inverted repeats and gene promoters. Mobile genetic elements (MGE) such as integrons are LGS that play an important role in horizontal gene transfer, primarily in Gram-negative organisms. Known LGS have a profound effect on organism virulence, antibiotic resistance and other properties of the organism due to the number of genes involved. Expert-compiled grammars have been shown to be an effective computational representation of LGS, well suited to automating annotation, and supporting de novo gene discovery. However, development of LGS grammars by experts is labour intensive and restricted to known LGS. OBJECTIVES This study uses computational grammar inference methods to automate LGS discovery. We compare the ability of six algorithms to infer LGS grammars from DNA sequences annotated with genes and other short sequences. We compared the predictive power of learned grammars against an expert-developed grammar for gene cassette arrays found in Class 1, 2 and 3 integrons, which are modular LGS containing up to 9 of about 240 cassette types. RESULTS Using a Bayesian generalization algorithm our inferred grammar was able to predict > 95% of MGE structures in a corpus of 1760 sequences obtained from Genbank (F-score 75%). Even with 100% noise added to the training and test sets, we obtained an F-score of 68%, indicating that the method is robust and has the potential to predict de novo LGS structures when the underlying gene features are known. AVAILABILITY http://www2.chi.unsw.edu.au/attacca.