Research Articles (DISA)
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Item Revisiting Sensemaking: The case of the Digital Decision Network Application (DigitalDNA)(2017-08) Archer, Elizabeth; Barnes, GlenDuring this age of data proliferation, heavy reliance is placed on data visualisation to support users in making sense of vast quantities of information. Informational Dashboards have become the must have accoutrement for Higher Education institutions with various stakeholders jostling for development priority. Due to the time pressure and user demands, the focus of development process is often on designing for each stakeholder and the visual and navigational aspects. Dashboards are designed to make data visually appealing and easy to relate and understand; unfortunately this may mask data issues and create an impression of rigour where it is not justified. This article proposes that the underlying logic behind current dashboard development is limited in the flexibility, scalability, and responsiveness required in the demanding landscape of Big Data and Analytics and explores an alternative approach to data visualisation and sense making. It suggests that the first step required to address these issues is the development of an enriched database which integrates key indicators from various data sources. The database is designed for problem exploration allowing users freedom in navigating between various data-levels, which can then be overlaid with any user interface for dashboard generation for a multitude of stakeholders. Dashboards merely become tools providing users and indication of types of data available for exploration. A Design Research approach is shown, along with a case study to illustrate the benefits, showcasing various views developed for diverse stakeholders employing this approach, specifically the the Digital Decision Network Application (DigitalDNA) employed at Unisa.Item Re-examining dashboard development: putting the horse back in front of the cart(European Association of Institutional Research, 2015-08-31) Archer, Elizabeth; Barnes, GlenDuring this age of data proliferation, heavy reliance is placed on data visualisation to support users in making sense of vast quantities of information: Finding the signal in the noise (Silver 2012). Informational Dashboards have become the must have accoutrement for Higher Education institutions with various stakeholders jostling for development priority. Due to the time pressure and user demands, the focus of development process is often on designing for each stakeholder and the visual and navigational aspects. Dashboards are designed to make data visually appealing and easy to relate and understand; unfortunately this may mask data issues and create an impression of rigour where it is not warranted. This paper explores an alternative approach to data visualisation and dashboard design. It suggests that the first step should be the development of an enriched database which integrates key indicators from various data sources and then acts as a database for various dashboards. The emphasis is thus on the underlying value-added database which can then be overlaid with any user interface for dashboard generation for a multitude of stakeholders. The enriched central database thus becomes a menu of available quality assured data which can easily be drawn into various dashboards at various levels of granularity ensuring improved data quality management, responsiveness, efficiency and flexibility. A case study is employed illustrating the benefits, showcasing various views developed for diverse stakeholders employing this approach.Item Big(ger) data as better data in open distance learning: some provocations and theses.(The International Review of Research in Open and Distributed Learning, 2015-02) Prinsloo, Paul; Archer, Elizabeth; Barnes, Glen; Chetty, Yuraisha; Van Zyl, DionIn the context of the hype, promise and perils of Big Data and the currently dominant paradigm of data-driven decision-making, it is important to critically engage with the potential of Big Data for higher education. We do not question the potential of Big Data, but we do raise a number of issues, and present a number of theses to be seriously considered in realising this potential. The University of South Africa (Unisa) is one of the mega ODL institutions in the world with more than 360,000 students and a range of courses and programmes. Unisa already has access to a staggering amount of student data, hosted in disparate sources, and governed by different processes. As the university moves to mainstreaming online learning, the amount of and need for analyses of data are increasing, raising important questions regarding our assumptions, understanding, data sources, systems and processes. This article presents a descriptive case study of the current state of student data at Unisa, as well as explores the impact of existing data sources and analytic approaches. From the analysis it is clear that in order for big(ger) data to be better data, a number of issues need to be addressed. The article concludes by presenting a number of theses that should form the basis for the imperative to optimise the harvesting, analysis and use of student data.Item Benchmarking the habits and behaviours of successful students: a case study of academic-business collaboration(Athabasca University, 2014-02) Archer, Elizabeth; Chetty, Yuraisha; Prinsloo, Paul; Ochonogor, Chukunoye EnunuweStudent success and retention is a primary goal of higher education institutions across the world. The cost of student failure and dropout in higher education is multifaceted including, amongst other things, the loss of revenue, prestige, and stakeholder trust for both institutions and students. Interventions to address this are complex and varied. While the dominant thrust has been to investigate academic and non-academic risk factors thus applying a “risk” lens, equal attention should be given to exploring the characteristics of successful students which expands the focus to include “requirements for success”. Based on a socio-critical model for understanding of student success and retention, the University of South Africa (Unisa) initiated a pilot project to benchmark successful students’ habits and behaviours using a tool employed in business settings, namely Shadowmatch®. The original focus was on finding a theoretically valid measured for habits and behaviours to examine the critical aspect of student agency in the social critical model. Although this was not the focus of the pilot, concerns regarding using a commercial tool in an academic setting overshadowed the process. This paper provides insights into how academic-business collaboration could allow an institution to be more dynamic and flexible in supporting its student population.Item Graduate Employability: Conceptualisation and findings from the University of South Africa(Unisa, 2013-11) Archer, Elizabeth; Chetty, YuraishaA major motivation for students of all ages to enter tertiary education is to improve their access to the job market and increase the likelihood of success in their career trajectories (McCune, Hounsell, Christie, Cree, and Tett 2010). This is particularly relevant in the South African context, which unfortunately claims an unemployment rate of 25 per cent (Statistics South Africa 2013). Universities therefore have to balance their broader purpose of producing well-rounded citizens with meeting the demands of the labour market. The University of South Africa (Unisa) is an Open Distance Learning (ODL) institution with more than 320 000 students (Unisa2012). Unisa sees employability as an indicator of student success and the institution’s ability to provide qualifications that are appropriate for the ever-changing demands of the globalised knowledge economy. This article reports on the 2011 graduate exit survey, focussing on the employability and graduate attributes of the 2009 graduates. Whilst this article focusses on employability of Unisa students, it also provides insight into how the complex phenomenon of graduate employability can be studied in the broader global ODL environment. The conceptual framework developed for this study and discussed later is applicable to both local and global higher education contexts. The data provides insight into the black box of student employability and student needs for support to increase their employability.