Developing Educational Software: a professional tool perspective

The selection, and use of educational software and its impact in schools are still controversial issues. In this paper we present an alternative conceptualisation of educational software based on considering the software as an instrument for teachers’ professional performance. We review previous work in the areas of the design, development and evaluation of educational software and of the process of educational innovation. The review of these four areas converges to demonstrate the need for knowing and considering the context of use of educational software and for understanding users' perspectives about its roles and possibilities and hence supports a consideration a perspective on educational software which sees it as a professional tool for teachers performance of their teaching role

Design environments for Intelligent Systems

There is a need to balance the quality of professionally designed information systems with the end user’s current knowledge of specific decision contexts. This is particularly so for intelligent systems. This paper looks at some theoretical underpinnings for the potential end- user development of intelligent systems. General requirements are characterised and the metaphor of a semantic spreadsheet is introduced. A two level process enabling end user development of knowledge-based systems is described. The first involves the development of a design environment that allows experts to develop the knowledge base. The second involves development within the design environment for the ultimate end users

A collective artefact design of decision support systems: design science research perspective

Purpose - The knowledge of artefact design in design science research can have an important application in the improvement of decision support systems (DSS) development research. Recent DSS literature has identified a significant need to develop user-centric DSS method for greater relevance with respect to context of use. To address this, this study develops a collective DSS design artefact as method in a practical industry context. Design/methodology/approach - Under the influence of goal-directed interaction design principles the study outlines the innovative DSS artefact based on design science methodology to deliver a cutting-edge decision support solution, which provides user-centric provisions through the use of design environment and ontology techniques. Findings - The DSS artefact as collective IT applications through the application of design science knowledge can effectively be designed to meet decision makers’ contextual needs in an agricultural industry context. Research limitations/implications - The study has limitations in that it was developed in a case study context and remains to be fully tested in a real business context. It is also assumed that the domain decisions can be parameterised and represented using a constraint programming language. Practical implications - We conclude that the DSS artefact design and this development successfully overcomes some of the limitations of traditional DSS such as low user uptake, system obsolescence, low returns on investment and a requirement for continual re-engineering effort. Originality/value - The design science paradigm provides structural guidance throughout the defined process, helping ensure fidelity both to best industry knowledge and to changing user contexts

A Metadesign Theory for Tailorable Decision Support

Despite years of decision support systems (DSS) research, DSS artifacts are frequently criticized for lacking practitioner relevance and for neglecting configurability and contextual dynamism. Tailoring in end-user contexts can produce relevant emergent DSS artifacts, but design theory for this is lacking. Design science research (DSR) has important implications for improving DSS uptake, but generally this has not been promoted in the form of metadesigns with design principles applicable to other DSS developments. This paper describes a metadesign theory for tailorable DSS, generated through action design research studies in different primary industries. Design knowledge from a DSS developed in an agricultural domain was distilled and generalized into a design theory comprising: (1) a general solution concept (metadesign), and (2) five hypothesized design principles. These were then instantiated via a second development in which the metadesign and design principles were applied in a different domain (forestry) to produce a successful DSS, thus testing the metadesign and validating the design principles. In addition to contributing to DSR and illustrating innovation in tailorable technology, the paper demonstrates the utility of action design research to support theory development in DSS design

Improving the Efficiency of Mobile User Interface Development through Semantic and Data-Driven Analyses

Having millions of mobile applications from Google Play and Apple's App store, the smartphone is becoming a necessity in our life. People could access a wide variety of services by using the mobile application, between which user interfaces (UIs) work as an important proxy.A well-designed UI makes an application easy, practical, and efficient to use. However, due to the rapid application iteration speed and the shortage of UI designers, developers are required to design the UIs and implement them in a short time.As a result, they may be unaware of or compromise some important factors related to usability and accessibility during the process of developing user interfaces of mobile applications.Therefore, efficient and useful tools are needed to enhance the efficiency of the development of user interfaces. In this thesis, I proposed three techniques to improve the efficiency of designing and developing user interfaces through semantic and data-driven analyses. First, I proposed a UI design search engine to help designers or developers quickly create trendy and practical UI designs by exposing them to UI designs in real applications. I collected a large-scale UI design dataset by automatically exploring UIs from top-downloaded Android applications, and designed an image autoencoder-based UI design engine to enable finer-grained UI design search. Second, during the process of understanding the real UIs implementation, I found that existing applications have a severe accessibility issue of lacking labels for image-based buttons. Such an issue will hinder the blind users to access the key functionalities on UIs. As blind users need to rely on screen readers to read content on UIs, it requires the developers to set up appropriate labels for image-based buttons.Therefore, I proposed LabelDroid, which aims to automatically generate labels (i.e., the content description) of image-based buttons while developers implement UIs. Finally, as the above techniques all require the view hierarchical information, which contains the bounds and type of contained elements, to achieve the goal, it is essential to generalize these techniques to a broader scope. For example, UIs in the design-sharing platforms do not have any metadata about the elements. To do this, I conducted the first large-scale empirical study on evaluating existing object detection methods of detecting elements in UIs. By understanding the unique characteristics of UI elements and UIs, I proposed a hybrid method to boost the accuracy and precision of detecting elements on user interfaces. Such a fundamental method can be beneficial to many downstream applications, such as UI design search, UI code generation, and UI testing. In conclusion, I proposed three techniques to enhance the efficiency of designing and developing the user interfaces on mobile applications through semantic and data-driven analyses. Such methods could easily generalize to a broader scope, such as user interfaces of desktop apps and websites.I expect my proposed techniques and the understanding of user interfaces can facilitate the following research