Higher education as a portfolio investment: students’ choices about studying, term time employment, leisure, and loans

Recent UK changes in the number of students entering higher education, and in the nature of financial support, highlight the complexity of students’ choices about human capital investments. Today’s students have to focus not on the relatively narrow issue of how much academic effort to invest, but instead on the more complicated issue of how to invest effort in pursuit of ‘employability skills’, and how to signal such acquisitions in the context of a highly competitive graduate jobs market. We propose a framework aimed specifically at students’ investment decisions, which encompasses corner solutions for both borrowing and employment while studying.

Studying the impact of ubiquitous monitoring technology on office worker behaviours: the value of sharing research data

Pervasive computing is a continually, and rapidly, growing field, although still remains in relative infancy. The possible applications for the technology are numerous, and stand to fundamentally change the way users interact with technology. However, alongside these are equally numerous potential undesirable effects and risks. The lack of empirical naturalistic data in the real world makes studying the true impacts of this technology difficult. This paper describes how two independent research projects shared such valuable empirical data on the relationship between pervasive technologies and users. Each project had different aims and adopted different methods, but successfully used the same data and arrived at the same conclusions. This paper demonstrates the benefit of sharing research data in multidisciplinary pervasive computing research where real world implementations are not widely available.

RedGloo: Experiences of developing and using an emerging technology in higher education

Student life has change a lot since 2005 when the idea to create a Social Network Service (SNS) for students in the School of Systems Engineering at the University of Reading was conceived and went live in 2006, called RedGloo.

HMEF: framework to evaluate merging of Higher Education Institutions – application of Enterprise Architecture

Mergers of Higher Education Institutions (HEIs) are organisational processes requiring tremendous amount of resources, in terms of time, work, and money. A number of mergers have been seen on previous years and more are to come. Several studies on mergers have been conducted, revealing some crucial factors that affect the success of mergers. Based on literature review on these studies, factors are: the initiator of merger, a reason for merger, geographical distance of merging institutions, organisational culture, the extend of overlapping course portfolio, and Quality Assurance Systems (QASs). Usually these kind of factors are not considered on mergers, but focus is on financial matters. In this paper, a framework (HMEF) for evaluating merging of HEIs is introduced. HMEF is based on Enterprise Architecture (EA), focusing on factors found to be affecting the success of mergers. By using HMEF, HEIs can focus on matters that crucial for merging.

Enterprise Architecture adoption method for Higher Education Institutions

During the last few years Enterprise Architecture has received increasing attention among industry and academia. Enterprise Architecture (EA) can be defined as (i) a formal description of the current and future state(s) of an organisation, and (ii) a managed change between these states to meet organisation’s stakeholders’ goals and to create value to the organisation. By adopting EA, organisations may gain a number of benefits such as better decision making, increased revenues and cost reductions, and alignment of business and IT. To increase the performance of public sector operations, and to improve public services and their availability, the Finnish Parliament has ratified the Act on Information Management Governance in Public Administration in 2011. The Act mandates public sector organisations to start adopting EA by 2014, including Higher Education Institutions (HEIs). Despite the benefits of EA and the Act, EA adoption level and maturity in Finnish HEIs are low. This is partly caused by the fact that EA adoption has been found to be difficult. Thus there is a need for a solution to help organisations to adopt EA successfully. This thesis follows Design Science (DS) approach to improve traditional EA adoption method in order to increase the likelihood of successful adoption. First a model is developed to explain the change resistance during EA adoption. To find out problems associated with EA adoption, an EA-pilot conducted in 2010 among 12 Finnish HEIs was analysed using the model. It was found that most of the problems were caused by misunderstood EA concepts, attitudes, and lack of skills. The traditional EA adoption method does not pay attention to these. To overcome the limitations of the traditional EA adoption method, an improved EA Adoption Method (EAAM) is introduced. By following EAAM, organisations may increase the likelihood of successful EA adoption. EAAM helps in acquiring the mandate for EA adoption from top-management, which has been found to be crucial to success. It also helps in supporting individual and organisational learning, which has also found to be essential in successful adoption.

Supporting schools in identifying and safeguarding the needs of disabled children: the challenges for data collection

Conceptualisations of disability that emphasise the contextual and cultural nature of disability and the embodiment of these within a national system of data collection present a number of challenges especially where this process is devolved to schools. The requirement for measures based on contextual and subjective experiences gives rise to particular difficulties in achieving parity in the way data is analysed and reported. This paper presents an account of the testing of a tool intended for use by schools as they collect data from parents to identify children who meet the criteria of disability established in Disability Discrimination Acts (DDAs). Data were validated through interviews with parents and teachers and observations of children and highlighted the pivotal role of the criterion of impact. The findings are set in the context of schools meeting their legal duties to identify disabled children and their support needs in a way that captures the complexity of disabled children’s school lives and provides useful and useable data.