Designing and Testing User-Centric Systems with both User Experience and Design Science Research Principles

The User Experience (UX) and Design Science Research (DSR) paradigms have much in common; they both contribute to Information Systems (IS) research by providing guidelines for designing successful Information Technology (IT) systems. We are working toward a research paradigm that combines the best elements of DSR and UX for designing user-centric IT systems with an outstanding user experience. To achieve this goal, we are jointly applying these two paradigms to develop an IT artifact (a sleep app). We will examine what we have learned from applying DSR and the UX principles and explore how these two paradigms individually and jointly can strengthen the design and development process for user-centric systems. Our initial results indicate that jointly using these two paradigms can strengthen the design and development process for user-centric systems and can be of great value to theory and practice

An Ontological Basis for Design Methods

This paper presents a view of design methods as process artefacts that can be represented using the function-behaviour-structure (FBS) ontology. This view allows identifying five fundamental approaches to methods: black-box, procedural, artefact-centric, formal and managerial approaches. They all describe method structure but emphasise different aspects of it. Capturing these differences addresses common terminological confusions relating to methods. The paper provides an overview of the use of the fundamental method approaches for different purposes in designing. In addition, the FBS ontology is used for developing a notion of prescriptiveness of design methods as an aggregate construct defined along four dimensions: certainty, granularity, flexibility and authority. The work presented in this paper provides an ontological basis for describing, understanding and managing design methods throughout their life cycle. Keywords: Design Methods; Function-Behaviour-Structure (FBS) Ontology; Prescriptive Design Knowledge</p

Human-Centric Program Synthesis

Program synthesis techniques offer significant new capabilities in searching for programs that satisfy high-level specifications. While synthesis has been thoroughly explored for input/output pair specifications (programming-by-example), this paper asks: what does program synthesis look like beyond examples? What actual issues in day-to-day development would stand to benefit the most from synthesis? How can a human-centric perspective inform the exploration of alternative specification languages for synthesis? I sketch a human-centric vision for program synthesis where programmers explore and learn languages and APIs aided by a synthesis tool

Towards a user-centric and multidisciplinary framework for designing context-aware applications

Research into context-aware computing has not sufficiently addressed human and social aspects of design. Existing design frameworks are predominantly software orientated, make little use of cross-disciplinary work, and do not provide an easily transferable structure for cross-application of design principles. To address these problems, this paper proposes a multidisciplinary and user-centred design framework, and two models of context, which derive from conceptualisations within Psychology, Linguistics, and Computer Science. In a study, our framework was found to significantly improve the performance of postgraduate students at identifying the context of the user and application, and the usability issues that arise

To Frame or Reframe: Where Might Design Thinking Research Go Next?

Design thinking is gaining widespread attention in the practitioner and academic literature. Successful implementation has been documented, and its value shown in empirical studies. There is little examination, however, of how design thinking practices fit with other approaches from which firms might choose to frame and solve problems such as agile, lean startup, scientific method, Six Sigma, critical thinking, and systems thinking. By digging into the basic capabilities underlying design thinking, academic researchers might better understand problem framing and solving in general and provide insight for practitioners as to where alternative approaches might be applied

Living Innovation Laboratory Model Design and Implementation

Living Innovation Laboratory (LIL) is an open and recyclable way for multidisciplinary researchers to remote control resources and co-develop user centered projects. In the past few years, there were several papers about LIL published and trying to discuss and define the model and architecture of LIL. People all acknowledge about the three characteristics of LIL: user centered, co-creation, and context aware, which make it distinguished from test platform and other innovation approaches. Its existing model consists of five phases: initialization, preparation, formation, development, and evaluation. Goal Net is a goal-oriented methodology to formularize a progress. In this thesis, Goal Net is adopted to subtract a detailed and systemic methodology for LIL. LIL Goal Net Model breaks the five phases of LIL into more detailed steps. Big data, crowd sourcing, crowd funding and crowd testing take place in suitable steps to realize UUI, MCC and PCA throughout the innovation process in LIL 2.0. It would become a guideline for any company or organization to develop a project in the form of an LIL 2.0 project. To prove the feasibility of LIL Goal Net Model, it was applied to two real cases. One project is a Kinect game and the other one is an Internet product. They were both transformed to LIL 2.0 successfully, based on LIL goal net based methodology. The two projects were evaluated by phenomenography, which was a qualitative research method to study human experiences and their relations in hope of finding the better way to improve human experiences. Through phenomenographic study, the positive evaluation results showed that the new generation of LIL had more advantages in terms of effectiveness and efficiency.Comment: This is a book draf

Cloudworks: Social networking for learning design

Can we apply the best of Web 2.0 principles to an educational context? More specifically can we use this as a means of shifting teaching practice to a culture of sharing learning ideas and designs? This paper describes a new social networking site, Cloudworks, which aims to provide a mechanism for sharing, discussing and finding learning and teaching ideas and designs. We describe the development of the site and the key associated concepts, 'clouds' and 'cloudscapes'. We provide a summary of recent activities and plans for the future. We conclude by describing the underpinning theoretical perspectives we have drawn on in the development of the site and in particular the notion of 'social objects' in social networking and a framework for 'sociality' for transforming user practice online

Categorisation of visualisation methods to support the design of Human-Computer Interaction systems

During the design of Human-Computer Interaction (HCI) systems, the creation of visual artefacts forms an important part of design. On one hand producing a visual artefact has a number of advantages: it helps designers to externalise their thought and acts as a common language between different stakeholders. On the other hand, if an inappropriate visualisation method is employed it could hinder the design process. To support the design of HCI systems, this paper reviews the categorisation of visualisation methods used in HCI. A keyword search is conducted to identify a) current HCI design methods, b) approaches of selecting these methods. The resulting design methods are filtered to create a list of just visualisation methods. These are then categorised using the approaches identified in (b). As a result 23 HCI visualisation methods are identified and categorised in 5 selection approaches (The Recipient, Primary Purpose, Visual Archetype, Interaction Type, and The Design Process).Innovate UK, EPSRC, Airbus Group Innovation

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded