Students' experiences and expectations of technologies: An Australian study designed to inform planning and development decisions

The pace of technological change accompanied by an evolution in social, work-based and study behaviours and norms poses particular challenges for universities as they strive to develop high quality and sustainable technology-rich learning environments. Maintaining currency with the latest advances is resource intensive, hence the costs incurred in upgrading existing and introducing new technologies need to be carefully weighed up against the potential benefits to students. This calls for a multidimensional approach to planning, with the student voice being an important dimension. Three Australian universities have recently completed a project to gain a better understanding of students' experiences and expectations of technologies in everyday life and for study purposes. The LMS and 25 other technologies ranging from established university offerings (email, learning management systems) to freely available social networking technologies (YouTube, Facebook) were surveyed. More than 10,000 students responded. This paper discusses the development of the survey and presents the broad trends that have emerged in relation to the current use of technologies and desired future use of these for learning purposes. The implications of the survey findings for developing institutional infrastructure to engage students and support their learning are highlighted. © 2013 Australasian Journal of Educational Technology

Using research to inform learning technology practice and policy: A qualitative analysis of student perspectives

As learning technologies are now integral to most higher education student learning experiences, universities need to make strategic choices about what technologies to adopt and how to best support and develop the use of these technologies, particularly in a climate of limited resources. Information from students is therefore a valuable contribution when determining institutional goals, building infrastructure and improving the quality of student learning. This paper draws on a survey of student experiences and expectations of technology across three Australian universities. Analysis of text responses from 7,000 students provides insight into ways that institutional learning technologies and academicled technologies are influencing the student experience. This paper also discusses how the three universities have used this information to develop strategic initiatives, and identifies a need for new strategies to support academic-led use of the available tools. © Australasian Journal of Educational Technology 2014

Leading the evaluation of institutional online learning environments for quality enhancement in times of change

This paper reports on findings from a nationally funded project which aims to design and implement a quality management framework for online learning environments (OLEs). Evaluation is a key component of any quality management system and it is this aspect of the framework that is the focus of this paper. In developing the framework initial focus groups were conducted at the five participating institutions. These revealed that, although regarded as important, there did not appear to be a shared understanding of the nature and purpose of evaluation. A second series of focus groups revealed there were multiple perspectives arising from those with a vested interest in online learning. These perspectives will be outlined. Overall, how evaluation was undertaken was highly variable within and across the five institutions reflecting where they were at in relation to the development of their OLE

Socio-economic status and students' experiences of technologies: Is there a digital divide?

With the widening participation agenda in Australia, more students from low socio-economic backgrounds are being encouraged to undertake university degrees, and will be expected to use digital technologies and demonstrate digital literacies. This paper used data from a 2013 survey of students across three universities, to examine whether there were socio-economic differences in students' access to and use of technologies. There were few differences in access to equipment. There were also no differences in the most common uses of technologies, such as accessing course materials from the LMS, and few differences between students from low, medium and high socioeconomic status suburbs. However students who received government support benefits less frequently used technologies that related to disciplinary skills or to creating rather than receiving content. There may be a subtle digital divide, where financially disadvantaged students are engaging less with technologies that will most benefit their future employment

Evaluation of binomial double sums involving absolute values

We show that double sums of the form $$\sum_{i,j=-n} ^{n} |i^sj^t(i^k-j^k)^\beta| \binom {2n} {n+i} \binom {2n} {n+j}$$ can always be expressed in terms of a linear combination of just four functions, namely $\binom {4n}{2n}$, ${\binom {2n}n}^2$, $4^n\binom {2n}n$, and $16^n$, with coefficients that are rational in $n$. We provide two different proofs: one is algorithmic and uses the second author's computer algebra package Sigma; the second is based on complex contour integrals. In many instances, these results are extended to double sums of the above form where $\binom {2n}{n+j}$ is replaced by $\binom {2m}{m+j}$ with independent parameter $m$.Comment: AmS-LaTeX, 42 pages; substantial revision: several additional and more general results, see Proposition 11 and Theorems 15-1

Asymptotic Properties of Difference Equations for Isotropic Loop Quantum Cosmology

In loop quantum cosmology, a difference equation for the wave function describes the evolution of a universe model. This is different from the differential equations that arise in Wheeler-DeWitt quantizations, and some aspects of general properties of solutions can appear differently. Properties of particular interest are boundedness and the presence of small-scale oscillations. Continued fraction techniques are used to show in different matter models the presence of special initial conditions leading to bounded solutions, and an explicit expression for these initial values is derived.Comment: 27 pages, 2 figure

Student use of technologies for learning â€" what has changed since 2010?

This paper reports on a large longitudinal survey of students and their use of technologies in two Australian universities. The SEET survey is unique in Australia because it includes not just current use, but students' expectations about their future use of technology. The survey was originally run in 2010 and then repeated, with slight modifications to reflect changes in technologies, in 2013. This paper compares the results from 2013 with the 2010 results. Whilst some changes reflect the wider access to freely available open resources and new technologies such as Smartphones and iPads, other results are remarkably consistent with the 2010 results. Overall students are increasingly satisfied with their use of technologies and despite the increase in uptake of freely available technologies, it is evident that the LMS and its inbuilt tools and functions remain a key platform for learning and teaching at universities

Simplifying Multiple Sums in Difference Fields

In this survey article we present difference field algorithms for symbolic summation. Special emphasize is put on new aspects in how the summation problems are rephrased in terms of difference fields, how the problems are solved there, and how the derived results in the given difference field can be reinterpreted as solutions of the input problem. The algorithms are illustrated with the Mathematica package \SigmaP\ by discovering and proving new harmonic number identities extending those from (Paule and Schneider, 2003). In addition, the newly developed package \texttt{EvaluateMultiSums} is introduced that combines the presented tools. In this way, large scale summation problems for the evaluation of Feynman diagrams in QCD (Quantum ChromoDynamics) can be solved completely automatically.Comment: Uses svmult.cls, to appear as contribution in the book "Computer Algebra in Quantum Field Theory: Integration, Summation and Special Functions" (www.Springer.com