University of South Australia (AUSTRALIA)
About this paper:
Appears in: EDULEARN13 Proceedings
Publication year: 2013
Pages: 3735-3744
ISBN: 978-84-616-3822-2
ISSN: 2340-1117
Conference name: 5th International Conference on Education and New Learning Technologies
Dates: 1-3 July, 2013
Location: Barcelona, Spain
The diversity of student needs has been shown to impact on their proficiency in the use of digital technologies in numerous studies (Hargittai, 2010; Helsper & Eynon, 2010; Kennedy et al, 2009; Sheely, 2008; Vaidhyanathan, 2008; Wood et al, 2010). These findings problematize the popular rhetoric that students entering university in recent years are already equipped with the digital literacy required to engage in a range of technology enhanced learning activities. The findings from a survey of 812 undergraduates undertaken at the University of South Australia in 2010 demonstrate that there is considerable diversity in the use of digital technologies among International and non-English speaking background (NESB) students, as well as students with disabilities. Personalized learning environments (PLEs) offer great promise in meeting this diversity in student learning styles, digital literacy, English language proficiency, access to technologies, and accessibility requirements.

Learning Management Systems (LMSs) such as Moodle and Blackboard (see Bacus, 2010 for her review of LMSs), while incorporating many tools that can enable students to access learning materials in different formats, have been criticized as being ‘institutionally controlled, content-centric’ (McLoughlin & Lee, 2010). The latest edition of the NMC Horizon Report focusing on higher education (Johnson et al, 2013), in describing the emerging technology enhanced learning (TEL) landscape, highlights personalization of the learning environment as one of the major trends within the next two-three years, with learning analytics (mining LMS data to identify at-risk learners, improve retention and customize the LMS) providing a major source of evidence to support such personalization. A PLE must also incorporate the key elements of inclusive design including: 1) interoperability; 2) accessibility to users with disabilities; and 3) customization and localization features for people from different countries and cultures (Usability First, 2013; World Wide Web Consortium, WAI, 2011).

Although there have been several PLE projects addressing TEL approaches to customizing the sequencing of modules and activities within LMSs, and other projects focusing more specifically on accessibility for students with disabilities (for example Amado-Salvatierra, Hernández & Hilera, 2012), there are as yet no fully adaptable and responsive PLE approaches that take into account the full range of diversity of student needs including preferred learning styles, usability and accessibility considerations (Attwell, 2009). Within this context, as the NMC (2013) report acknowledges, the role of educators continues to change and there is a need to scaffold academics in understanding how to draw on a range of sources of evidence to be responsive to the specific needs of their students.

This paper describes such a holistic approach based on the findings of previously funded research undertaken by the author (Wood, 2010, 2011; Wood & Willems, 2012; Wood & Bloustien, in press). The presentation will consider the diverse needs of the student population, guidelines for personalizing the learning environment to be inclusive of such diverse needs and will describe the conceptual model of a proposed responsive learning system (RLS) based on an existing architectural framework, Global Public Inclusive Infrastructure (Vanderheiden et al, 2012), which has the potential to address the identified needs.
Personalized learning environment, diversity, disability, learning analytics, accessibility, usability, responsive learning.