Essential features of serious games design in higher education:linking learning attributes to game mechanics

This paper consolidates evidence and material from a range of specialist and disciplinary fields to provide an evidence-based review and synthesis on the design and use of serious games in higher education. Search terms identified 165 papers reporting conceptual and empirical evidence on how learning attributes and game mechanics may be planned, designed and implemented by university teachers interested in using games, which are integrated into lesson plans and orchestrated as part of a learning sequence at any scale. The findings outline the potential of classifying the links between learning attributes and game mechanics as a means to scaffold teachers’ understanding of how to perpetuate learning in optimal ways while enhancing the in-game learning experience. The findings of this paper provide a foundation for describing methods, frames and discourse around experiences of design and use of serious games, linked to methodological limitations and recommendations for further research in this area.

Design and designing:a critical introduction

Design and Designing provides a broad and critical understanding of what is essentially a practical subject. Designing today is less a craft and more a part of the knowledge economy. It's all about knowing how to acquire knowledge and how to apply it creatively. Design and Designing covers the design process, modelling and drawing, working with clients, production and consumption, sustainability, professional practice and design futures. Chapters are written by expert teachers and practitioners from around the globe, each presenting an accessible and engaging overview of their field of design. Every chapter is highly illustrated with a combination of images and information boxes, which extend or highlight key material. Each section concludes with a design project, a hands-on activity for the reader. Design and Designing covers the full spectrum of design types, from graphic communication to product design, from fashion to games design, setting every type in its aesthetic, ethical and social contexts. With this essential book, readers will learn from today's best practice and best thinking in design, they will develop a critical sense, and become the designers of tomorrow.

Agent-orientated auction mechanism and strategy design

Agent-based technology is playing an increasingly important role in today’s economy. Usually a multi-agent system is needed to model an economic system such as a market system, in which heterogeneous trading agents interact with each other autonomously. Two questions often need to be answered regarding such systems: 1) How to design an interacting mechanism that facilitates efficient resource allocation among usually self-interested trading agents? 2) How to design an effective strategy in some specific market mechanisms for an agent to maximise its economic returns? For automated market systems, auction is the most popular mechanism to solve resource allocation problems among their participants. However, auction comes in hundreds of different formats, in which some are better than others in terms of not only the allocative efficiency but also other properties e.g., whether it generates high revenue for the auctioneer, whether it induces stable behaviour of the bidders. In addition, different strategies result in very different performance under the same auction rules. With this background, we are inevitably intrigued to investigate auction mechanism and strategy designs for agent-based economics. The international Trading Agent Competition (TAC) Ad Auction (AA) competition provides a very useful platform to develop and test agent strategies in Generalised Second Price auction (GSP). AstonTAC, the runner-up of TAC AA 2009, is a successful advertiser agent designed for GSP-based keyword auction. In particular, AstonTAC generates adaptive bid prices according to the Market-based Value Per Click and selects a set of keyword queries with highest expected profit to bid on to maximise its expected profit under the limit of conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. The TAC CAT tournament provides an environment for investigating the optimal design of mechanisms for double auction markets. AstonCAT-Plus is the post-tournament version of the specialist developed for CAT 2010. In our experiments, AstonCAT-Plus not only outperforms most specialist agents designed by other institutions but also achieves high allocative efficiencies, transaction success rates and average trader profits. Moreover, we reveal some insights of the CAT: 1) successful markets should maintain a stable and high market share of intra-marginal traders; 2) a specialist’s performance is dependent on the distribution of trading strategies. However, typical double auction models assume trading agents have a fixed trading direction of either buy or sell. With this limitation they cannot directly reflect the fact that traders in financial markets (the most popular application of double auction) decide their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Experiments are conducted under both dynamic and static settings of the continuous BDA market. We find that the allocative efficiency of a continuous BDA market mainly comes from rational selection of trading directions. Furthermore, we introduce a high-performance Kernel trading strategy in the BDA market which uses kernel probability density estimator built on historical transaction data to decide optimal order prices. Kernel trading strategy outperforms some popular intelligent double auction trading strategies including ZIP, GD and RE in the continuous BDA market by making the highest profit in static games and obtaining the best wealth in dynamic games.