Natural mapping and intuitive interaction in videogames

Videogame control interfaces continue to evolve beyond their traditional roots, with devices encouraging more natural forms of interaction growing in number and pervasiveness. Yet little is known about their true potential for intuitive use. This paper proposes methods to leverage existing intuitive interaction theory for games research, specifically by examining different types of naturally mapped control interfaces for videogames using new measures for previous player experience. Three commercial control devices for a racing game were categorised using an existing typology, according to how the interface maps physical control inputs with the virtual gameplay actions. The devices were then used in a within-groups (n=64) experimental design aimed at measuring differences in intuitive use outcomes. Results from mixed design ANOVA are discussed, along with implications for the field.

Playful interactions for people with intellectual disabilities

For people with intellectual disabilities, there are significant barriers to inclusion in socially cooperative endeavors. This paper investigates the effectiveness of Stomp, a tangible user interface (TUI) designed to provide new participatory experiences for people with intellectual disability. Results from an observational study reveal the extent to which the Stomp system supports social and physical interaction. The tangible, spatial, and embodied qualities of Stomp result in an experience that does not rely on the acquisition of specific competencies before interaction and engagement can occur.

Learning analytics beyond the LMS : the Connected Learning Analytics toolkit

We present a Connected Learning Analytics (CLA) toolkit, which enables data to be extracted from social media and imported into a Learning Record Store (LRS), as defined by the new xAPI standard. Core to the toolkit is the notion of learner access to their own data. A number of implementational issues are discussed, and an ontology of xAPI verb/object/activity statements as they might be unified across 7 different social media and online environments is introduced. After considering some of the analytics that learners might be interested in discovering about their own processes (the delivery of which is prioritised for the toolkit) we propose a set of learning activities that could be easily implemented, and their data tracked by anyone using the toolkit and a LRS.

On secure outsourcing of cryptographic computations to cloud

For the past few years, research works on the topic of secure outsourcing of cryptographic computations has drawn significant attention from academics in security and cryptology disciplines as well as information security practitioners. One main reason for this interest is their application for resource constrained devices such as RFID tags. While there has been significant progress in this domain since Hohenberger and Lysyanskaya have provided formal security notions for secure computation delegation, there are some interesting challenges that need to be solved that can be useful towards a wider deployment of cryptographic protocols that enable secure outsourcing of cryptographic computations. This position paper brings out these challenging problems with RFID technology as the use case together with our ideas, where applicable, that can provide a direction towards solving the problems.

Analysing reflective text for learning analytics : an approach using anomaly recontextualisation

Reflective writing is an important learning task to help foster reflective practice, but even when assessed it is rarely analysed or critically reviewed due to its subjective and affective nature. We propose a process for capturing subjective and affective analytics based on the identification and recontextualisation of anomalous features within reflective text. We evaluate 2 human supervised trials of the process, and so demonstrate the potential for an automated Anomaly Recontextualisation process for Learning Analytics.

Rove n Rave™ development : a partnership between the university and the disability service provider to build a social website for people with an intellectual disability

Rove n Rave ™ is a website designed and created for, and with, people with an intellectual disability. Its aim is to provide them with a user-friendly online platform where they can share opinions and experiences, and where they can find reviews which will help them to choose a place to visit themselves. During the development process, input on design requirements was gathered from a group of people with an intellectual disability and the disability service provider. This group then tested the product and provided further feedback on improving the website. It was found that the choice of wording, icons, pictures, colours and some functions significantly affected the users' ability to understand the content of the website. This demonstrated that a partnership between the developer and the user is essential when designing and delivering products or services for people with an intellectual disability.

Tensor reduction for user profiling in personalized recommender systems

User profiling is the process of constructing user models which represent personal characteristics and preferences of customers. User profiles play a central role in many recommender systems. Recommender systems recommend items to users based on user profiles, in which the items can be any objects which the users are interested in, such as documents, web pages, books, movies, etc. In recent years, multidimensional data are getting more and more attention for creating better recommender systems from both academia and industry. Additional metadata provides algorithms with more details for better understanding the interactions between users and items. However, most of the existing user/item profiling techniques for multidimensional data analyze data through splitting the multidimensional relations, which causes information loss of the multidimensionality. In this paper, we propose a user profiling approach using a tensor reduction algorithm, which we will show is based on a Tucker2 model. The proposed profiling approach incorporates latent interactions between all dimensions into user profiles, which significantly benefits the quality of neighborhood formation. We further propose to integrate the profiling approach into neighborhoodbased collaborative filtering recommender algorithms. Experimental results show significant improvements in terms of recommendation accuracy.

Designing with people with disabilities : adapting best practices of DIY and organizational approaches

Individualization of design is often necessary particularly when designing with people with disabilities. Maker communities, with their flexible Do-It-Yourself (DIY) practices, offer potential to support individualized and cost-effective product design. However, efforts to adapt DIY practices in designing with people with disabilities tend to face difficulties with regard to continuous commitment, infrastructure provision and proper guidance. We carried out interviews with diverse stakeholders in the disability services sector and carried out observations of local makerspaces to understand their current practices and potential for future collaborations. We found that makerspace participants face difficulties in terms of infrastructure provision and proper guidance whereas Disability Service Organizations face difficulties in continuous expertise. We suggest that artful infrastructuring to blend the best of both approaches offers potential to create a sustainable community that can design individualized technologies to support people with disabilities.

Multi-action recognition via stochastic modelling of optical flow and gradients

In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification. This approach models each action using a Gaussian mixture using robust low-dimensional action features. Segmentation is achieved by performing classification on overlapping temporal windows, which are then merged to produce the final result. This approach is considerably less complicated than previous methods which use dynamic programming or computationally expensive hidden Markov models (HMMs). Initial experiments on a stitched version of the KTH dataset show that the proposed approach achieves an accuracy of 78.3%, outperforming a recent HMM-based approach which obtained 71.2%.

Evolutionary game design : automated game design comes of age

The "Humies" awards are an annual competition held in conjunction with the Genetic and Evolutionary Computation Conference (GECCO), in which cash prizes totalling $10,000 are awarded to the most human-competitive results produced by any form of evolutionary computation published in the previous year. This article describes the gold medal-winning entry from the 2012 "Humies" competition, based on the LUDI system for playing, evaluating and creating new board games. LUDI was able to demonstrate human-competitive results in evolving novel board games that have gone on to be commercially published, one of which, Yavalath, has been ranked in the top 2.5% of abstract board games ever invented. Further evidence of human-competitiveness was demonstrated in the evolved games implicitly capturing several principles of good game design, outperforming human designers in at least one case, and going on to inspire a new sub-genre of games.

An internet of social things

The Internet of Things is a vision for a world of interconnected smart devices. We present an alternative vision based on a review of literature that emphasizes the importance and role of objects in social relations. We situate this work in relation to a conceptual understanding of objects and sociality, and note some methodological implications of a more object-centred sociality that may suggest design opportunities alongside the emerging Internet of Things.

Mobile phone use in Australian Indigenous communities : future pathways for HC14D

This paper collates recent research on mobile phone use in Indigenous communities in Australia. Its key finding is that mobile phones are heavily used in these communities, albeit in unique and unusual ways that may be difficult to comprehend beneath 'top-down' measurements. Rather than framing these uses as being compromises made in lieu of appropriate infrastructures or literacies, it is argued that HCI4D (Human-Computer Interaction for Development) would be better served by seriously plumbing into the information they reveal about how mobile phones are constructed and placed in these communities, and what these factors might reveal about local understandings of development and well-being. A consideration of these specific patterns of appropriation is necessary to push the field beyond top-down, rationalist approaches to development towards more flexible, creative solutions that build from local knowledge and competencies.

Instructional objectives to core-gameplay : a serious game design technique

This paper explores a gap within the serious game design research. That gap is the ambiguity surrounding the process of aligning the instructional objectives of serious games with their core-gameplay i.e. the moment-to-moment activity that is the core of player interaction. A core-gameplay focused design framework is proposed that can work alongside existing, more broadly focused serious games design frameworks. The framework utilises an inquiry-based approach that allows the serious game designer to use key questions as a means to clearly outline instructional objectives with the core-gameplay. The use of this design framework is considered in the context of a small section of gameplay from an educational game currently in development. This demonstration of the framework brings shows how instructional objectives can be embedded into a serious games core-gameplay.