Client Needs and the Design Process in Web Projects

The nature of Web systems is substantially different from more conventional software systems. They are developed in shorter timeframes, often act as the direct interface between multiple stakeholders, meet a more generic set of requirements, and generally serve a less specific user group. They are often developed very quickly from templated solutions, using coarse-grained authoring tools, and by the efforts of a multidisciplinary team. There is often considerable uncertainty on the part of the client as to their own requirements. The importance of defining the objectives of the system during the early stages of a project are generally acknowledged to be important, but access to the tools and templates can encourage developers to build too early. Often requirements are inadequately documented, or only emerge during development, or change as development proceeds. The immaturity of the industry and the lack of standardised processes in web development have been demonstrated by web-based solutions that in many cases fail to meet fundamental requirements. Specifications for Web systems are consequently very different from those for more conventional software systems. Apart from an increased emphasis on user interactions and the underpinning content, they also reflect a blurring of the boundaries between requirements, specifications and designs in the development process. In this paper we offer an iterative model for Web systems development that incorporates the user of partia

WebML+ in a nutshell: Modeling architectural-level information flows

One aspect of the development of Web-enabled systems that has received increasing attention is information modeling, particularly with respect to aspects such as navigation models and their relationships to the underlying content. These models have, however, typically focused on modeling at a relatively low-level and have failed to address higher-level aspects, such as architectural and even business process modeling. In this paper we introduce a set of formal extensions to an existing modeling language - WebML - that facilitates information modeling at this higher level of abstraction. We argue that these extensions will provide a clearer connection between an understanding of business models and processes, and the lower-level designs typically represented in existing models

Engineering Admissions Criteria: Focusing on Ultimate Professional Success

The majority of Australian Universities use performance in the higher school examinations as the primary basis of admission into undergraduate programs for current school leavers. In 2005 an analysis of academic performance in the UTS undergraduate Engineering program showed a relatively low correlation with Higher School Certificate (HSC) results, particularly for students outside the top performance bands. This led to a rethinking of the admissions processes, and the introduction of a broader admission scheme. This scheme incorporated the results of an admission questionnaire which was designed with substantial input from industry, and which aimed to provide an indication of both likely academic success within the degree program as well as (and possibly more importantly) the likely success as a graduate Engineer. The key criteria related to affinity with, and motivations for, an Engineering career and addressed both the attitude and aptitude of students in terms of emotional intelligence characteristics. In this paper we describe the design and introduction of this scheme, and how input from industry was used to construct a questionnaire. We provide an analysis of early outcomes from the process in terms of student performance, and the extent to which course performance correlates to questionnaire results. We also include recommendations on how these schemes may be used to improve the retention and success of Engineering students and how to better match the aptitudes of engineering graduates with the needs and aspirations of Industry and Business

Adaptive group formation to promote desired behaviours

BACKGROUND There is substantial literature that shows the benefits of collaborative work, though these benefits vary enormously with circumstances. Irrespective of their structure and composition, groups usually exist for a particular reason and implicitly or explicitly target one or more outcomes. The achievements of group outcomes depend on many factors, including the individual behaviour of each group member. These behaviours are, in turn, affected by the individual characteristics, the context and the group composition. Constructing groups in a way that maximises the achievement of a specific outcome is complex with the optimal group composition depending on the attributes of the group members. Previous work has in most cases considered group formation based on one particular attribute, such as learning style, gender, personality, etc. Less common are instances of group formation rules being adjusted systematically to accommodate changes in an individualâs attributes or disposition. PURPOSE This paper considers how the multi-factorial nature of group performance and the variations in desired behaviour across different circumstances can be addressed within a consistent framework. DESIGN/METHOD The methodology consisted of two main stages. In the first stage, a simulation was encoded in MatLab to assess the conceptual approach of progressively updating rules for group formation. The method uses an unsupervised learning algorithm and correlation factors between quantifiable group characteristics (average age, degree of motivation, etc.) and resultant behaviours of the groups that are actually formed (level of dialogue, interface interactions, etc.) to update the rules used for group formation, and hence progressively construct groups that are more likely to behave in desired ways. The second stage involved an evaluation of this approach in a real world scenario using remotely accessible laboratories where engineering students voluntarily participated in a study in April 2012. RESULTS The simulation results show that under certain conditions the desired behaviour chosen with the intention of improving specific learning outcomes can be optimized and that groups can be constructed that are more likely to exhibit desired behaviour. The paper also reports preliminary evidence that shows the feasibility of this approach in selecting group participants in an engineering class to promote a desired outcome in this case independent learning. CONCLUSIONS This study demonstrates the feasibility of using a set of individual characteristics of group members to form groups that are more likely to have desired group behaviours and that these characteristics can be monitored and updated to dynamically alter group formation to account for changes in any individualâs characteristics. This has potential to allow groups formation decisions to be made dynamically to achieve a desired outcome, for example promote collaborative learning