151 research outputs found

    The case for a centre for learning and teaching

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    The impact of the Bradley Review, and the Governments response to it, are still continuing to transform the Australian Higher Education sector just as radically as any of the reforms that preceded it in earlier decades. When considered from a market perspective, these reforms have ensured that the sector must increasingly both understand and be able to respond rapidly, and in agile manner, to changing and challenging market conditions particularly where the recruitment and retention of students is concerned. In addition to these changing market dynamics is the evolving and increasing requirement to be able to demonstrably quality assure many aspects of the learning experience, but most particularly those elements that relate to the expression of the curriculum, particularly in terms of learning outcomes and the related assessment and moderation regimes

    A qualitative analysis of an LMS usage by staff

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    The Learning Management System (LMS) has emerged as one of the preferred information and communication technology solutions by which the higher education sector seeks to manage and support the learning experience that it provides to its students. It has also become an increasingly valuable tool which has the ability to record and capture data about users, unlocking the unprecedented potential of data captured for informed decision making and evidence- based strategies. Present literature illustrates a growing interest and increased use of analytics within the LMS to support and enhance the quality of learning and teaching; however, much of the focus has been on student learning and engagement. While educators can greatly benefit from data on learners, there is also a potential value in exploring and understanding the usage and engagement from the teaching staff perspective, as they are the key technological interfaces in the education institutions (Noeth & Volkov, 2004) who provide access to virtual learning content and support to students as part of the enhanced overall student learning experience. In 2008, the Learning Management System (LMS) Usage Framework was conceived by Griffith University and the University of Western Sydney as a joint initiative to undertake a benchmarking exercise to measure the level of uptake of the LMS and the associated tools at both universities This project and its outcomes were reported at ASCILITE 2009; Benchmarking across universities: A framework for LMS analysis (Rankine, Stevenson, Malfroy, Ashford-Rowe). This framework was a dynamic process model designed to define, describe and measure elements common to the online courses at given points in time, which enabled the selection of data according to specified criteria. Its principal elements were Content, Communication, Collaboration, Assessment, and Explicit Learner Support. Each element was then further broken into subcategories with respect to the use of particular online tools and educational content. Since 2008, and in collaboration with Educational Designers embedded within the academic community known at Griffith as Blended Learning Advisors, the framework that was developed in 2008 has undergone an evolutionary transformation to better fit and reflect the current Griffith learning and teaching context. However, its principal pedagogical delivery elements remain as Content, Communication, Collaboration, Assessment, and Explicit Learner Support, noting that each element is further broken into subcategories, which contain data on the use of particular online tools and educational content. In 2011/12 Griffith University initiated a further project, based upon this work, the purpose of which was to measure the level of academic uptake of the LMS. The revised LMS Usage Framework was adopted to develop algorithms capturing the relevant LMS data. This quantitative data was then analysed to measure the level of academic uptake and usage of the tools within the LMS. The data was structured to enable analysis at a range of academic grouping levels (Faculty/Department/School etc.) as well as to illustrate the overall performance of the respective academic element in terms of uptake and usage of technology tools in education delivery. This data extracted provided new and useful insights on the LMS tools usage patterns. This particularly activity was conducted as an exploratory study aimed at building on the previous work in this area, as noted above. However, it also unearthed new possibilities in the gathering and analysis of the LMS data to assist academic teachers, their managers and those administrators tasked with supporting academic professional development, in particular where it relates to evaluating the effectiveness of technological applications and strategies implemented to support an enhanced student learning experience and achievement

    Intensive modes of study and the need to focus on the process of learning in Higher Education

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    In the context of a constantly evolving international higher education sector, this commentary emphasises the need for consilience between basic research on learning processes and observations from intensive modes of study. Following a discussion of conflicting evidence on optimal learning time frames, we advocate for seeking alignment between classroom practices with underlying learning mechanisms. We argue for a unified understanding of effective learning beyond notions of the credit point hour or volume of learning, focusing on processes rather than mere inputs and outputs. A collaborative approach between researchers, educators, and policymakers aiming for consilience has the potential to provide practical insights and strategies to enhance student learning and success. Understanding the mechanisms beneath the impact of intensive modes of study, as outlined in this special issue, has the potential to advance the conversation about quality higher education for the 21st century

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

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    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

    Student use of technologies for learning -what has changed since 2010?

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    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

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

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    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

    Additive scales in degenerative disease - calculation of effect sizes and clinical judgment

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    <p>Abstract</p> <p>Background</p> <p>The therapeutic efficacy of an intervention is often assessed in clinical trials by scales measuring multiple diverse activities that are added to produce a cumulative global score. Medical communities and health care systems subsequently use these data to calculate pooled effect sizes to compare treatments. This is done because major doubt has been cast over the clinical relevance of statistically significant findings relying on <it>p </it>values with the potential to report chance findings. Hence in an aim to overcome this pooling the results of clinical studies into a meta-analyses with a statistical calculus has been assumed to be a more definitive way of deciding of efficacy.</p> <p>Methods</p> <p>We simulate the therapeutic effects as measured with additive scales in patient cohorts with different disease severity and assess the limitations of an effect size calculation of additive scales which are proven mathematically.</p> <p>Results</p> <p>We demonstrate that the major problem, which cannot be overcome by current numerical methods, is the complex nature and neurobiological foundation of clinical psychiatric endpoints in particular and additive scales in general. This is particularly relevant for endpoints used in dementia research. 'Cognition' is composed of functions such as memory, attention, orientation and many more. These individual functions decline in varied and non-linear ways. Here we demonstrate that with progressive diseases cumulative values from multidimensional scales are subject to distortion by the limitations of the additive scale. The non-linearity of the decline of function impedes the calculation of effect sizes based on cumulative values from these multidimensional scales.</p> <p>Conclusions</p> <p>Statistical analysis needs to be guided by boundaries of the biological condition. Alternatively, we suggest a different approach avoiding the error imposed by over-analysis of cumulative global scores from additive scales.</p

    Real World Learning and Authentic Assessment

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    As students increasingly adopt a consumerist lifestyle academics are under pressure to assess and mark more students’ assignments in quicker turn around periods. In no other area is the marketisation shift between student and academic more apparent in the accountability that academics now need to demonstrate to students in their grading and feedback (Boud & Molloy, 2013). When evaluating their higher education experience students are most likely to complain about their grading or feedback (Boud & Molloy, 2013) and National Student Survey results consistently indicate that this category, more than any other, has the highest student dissatisfaction rates (Race, 2014)
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