Melbourne Graduate School of Education - Research Publications

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    Methods and frequency of sharing of learning resources by medical students
    Judd, T ; Elliott, K (WILEY, 2017-11)
    Abstract University students have ready access to quality learning resources through learning management systems (LMS), online library collections and generic search tools. However, anecdotal evidence suggests they sometimes turn to peer‐based sharing rather than sourcing resources directly. We know little about this practice—how common it is, what sort of resources are involved and what impact it is likely to have on students' learning. This paper reports on an exploratory investigation of students' resource sharing habits, involving 338 respondents from the first 3 years of a 4‐year postgraduate medical curriculum. On average, students reported sharing learning resources with other students two or more times per week. They were most likely to share non‐curriculum resources (not available through their LMS) although curriculum and physical resources (eg, printed or handwritten notes and textbooks) were also often shared. Students employed a range of sharing technologies including email (most frequent), social media tools and cloud‐based file services. A cluster analysis revealed four distinct groups of students based on the frequency with which they share, the range of technologies they employ and whether they share both online and physical resources.
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    Immigrants and natives: Investigating differences between staff and students' use of technology
    Kennedy, G ; Dalgarno, B ; Bennett, S ; Judd, T ; Gray, K ; Chang, R (ASCILITE, 2008-12-01)
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    Beyond natives and immigrants: exploring types of net generation students
    Kennedy, G ; Judd, T ; Dalgarno, B ; Waycott, J (WILEY, 2010-10)
    Abstract Previously assumed to be a homogenous and highly skilled group with respect to information and communications technology, the so‐called Net Generation has instead been shown to possess a diverse range of technology skills and preferences. To better understand this diversity, we subjected data from 2096 students aged between 17 and 26 from three Australian universities to a cluster analysis. Through this analysis, we identified four distinct types of technology users: power users (14% of sample), ordinary users (27%), irregular users (14%) and basic users (45%). A series of exploratory chi‐square analyses revealed significant associations between the different types of technology users and the university that students attended, their gender and age and whether the student was local or international. No associations were found for analyses related discipline area, socio‐economic status or rurality of residence. The findings are discussed in light of the rhetoric associated with commentaries about the Net Generation, and suggestions about their implications for teaching and learning in universities are offered.