Understanding requirements engineering process: a challenge for practice and education

Reviews of the state of the professional practice in Requirements Engineering (RE) stress that the RE process is both complex and hard to describe, and suggest there is a significant difference between competent and "approved" practice. "Approved" practice is reflected by (in all likelihood, in fact, has its genesis in) RE education, so that the knowledge and skills taught to students do not match the knowledge and skills required and applied by competent practitioners. A new understanding of the RE process has emerged from our recent study. RE is revealed as inherently creative, involving cycles of building and major reconstruction of the models developed, significantly different from the systematic and smoothly incremental process generally described in the literature. The process is better characterised as highly creative, opportunistic and insight driven. This mismatch between approved and actual practice provides a challenge to RE education - RE requires insight and creativity as well as technical knowledge. Traditional learning models applied to RE focus, however, on notation and prescribed processes acquired through repetition. We argue that traditional learning models fail to support the learning required for RE and propose both a new model based on cognitive flexibility and a framework for RE education to support this model

Designing electronic collaborative learning environments

Electronic collaborative learning environments for learning and working are in vogue. Designers design them according to their own constructivist interpretations of what collaborative learning is and what it should achieve. Educators employ them with different educational approaches and in diverse situations to achieve different ends. Students use them, sometimes very enthusiastically, but often in a perfunctory way. Finally, researchers study them and—as is usually the case when apples and oranges are compared—find no conclusive evidence as to whether or not they work, where they do or do not work, when they do or do not work and, most importantly, why, they do or do not work. This contribution presents an affordance framework for such collaborative learning environments; an interaction design procedure for designing, developing, and implementing them; and an educational affordance approach to the use of tasks in those environments. It also presents the results of three projects dealing with these three issues

Spacecraft software training needs assessment research, appendices

The appendices to the previously reported study are presented: statistical data from task rating worksheets; SSD references; survey forms; fourth generation language, a powerful, long-term solution to maintenance cost; task list; methodology; SwRI's instructional systems development model; relevant research; and references

Research questions and approaches for computational thinking curricula design

Teaching computational thinking (CT) is argued to be necessary but also admitted to be a very challenging task. The reasons for this, are: i) no general agreement on what computational thinking is; ii) no clear idea nor evidential support on how to teach CT in an effective way. Hence, there is a need to develop a common approach and a shared understanding of the scope of computational thinking and of effective means of teaching CT. Thus, the consequent ambition is to utilize the preliminary and further research outcomes on CT for the education of the prospective teachers of secondary, further and higher/adult education curricula

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Development of predicting model for safety behaviour based on safety psychology and working environment

The increasing trend of occupational accident due to unsafe act and unsafe condition especially in construction site suggests the need for more proactive safety assessment model. Therefore this research aimed to establish a prediction model of safety behaviour based on safety psychology and working environment factors in construction site. Theory of Planned Behaviour (TpB) was adapted to examine on the prediction model of safety behaviour among construction workers using safety psychology representing unsafe act and working environment factors representing unsafe condition. A modified perception questionnaire named Safety Psychometric Model (SPM) was proposed based on TpB questionnaire and safety attitude questionnaire (SQA). Previously, the approach has successfully applied in health care and manufacturing sector. The questionnaire has been validated by three industrial and academic experts. A total of 554 respondents among 92 construction site were selected as the subjects for analysis. Structural Equation Modelling (SEM) and Statistical Package for the Social Science (SPSS) was use for analysis purpose which involve correlation, regression and structural equation analysis. The results demonstrated that safety psychology and work environment factor was related positively with safety behaviour intention. The elements of workers’ attitude, subjective norm and perceived control that form the safety psychology context found to be significantly has the ability to predict safety behaviour. The demographics variances of personal and education background, working experiences and training background also determine as the factors of safety behaviour of the construction workers. The research also successfully established a safety behaviour prediction model that named Safety Psychometric Model. The model can be benefited by safety practitioners, organizations and researchers to explore the safety behaviour prediction. It also enhanced the knowledge in the area of employee behaviour prediction and modelling

Choice and judgement in developing models for health technology assessment; a qualitative study

Introduction: The role of models in supporting health policy decisions is reliant on model credibility. Credibility is fundamentally determined by the choices and judgements that people make in the process of developing a model. However, the method of uncovering choices and making judgements in model development is largely unreported and is not addressed by modelling methods guidance. Methods: This qualitative study was part of a project examining errors in health technology assessment models. In-depth interviews with academic and commercial modellers were used to obtain descriptions of the model development process. Data were analysed using framework analysis and interpreted in the context of the methodological literature. Results: The activities involved in developing models were characterised according to the themes; understanding the decision problem, conceptual modelling, model implementation, model checking, and engaging with the decision maker. Finding and using evidence was frequently mentioned across these themes. There was marked variation between practitioners in the extent to which conceptual modelling was recognised as an activity distinct from model implementation. Discussion: Methodological approaches to addressing model credibility described in the wider modelling literature highlight the necessity to disentangle the conceptual modelling and implementation activities. Whilst interviewees talked of judgements and choice making throughout model development, discussion indicated that these were based upon skills and experience with no discussion of formal approaches. Methods are required that provide for a systematic approach to uncovering choices, to generating a shared view of consensus and divergence, and for making judgements and choices in model development