This paper reports on a study conducted in 2006 with more than 2,000 incoming firstyear Australian university students. Students were asked about their access to, use of and preferences for an array of established and emerging technologies and technology based tools. The results show that many first year students are highly tech-savvy. However, when one moves beyond entrenched technologies and tools (e.g. computers, mobile phones, email), the patterns of access and use of a range of other technologies show considerable variation. The findings are discussed in light of Prensky's (2001a) notions of the 'Digital Natives' and the implications for using technology to support teaching and learning in higher education.

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Over the last 5 years, massive open online courses (MOOCs) have increasingly provided learning opportunities across the world in a variety of domains. As with many emerging educational technologies, why and how people come to MOOCs needs to be better understood and importantly what factors contribute to learners' MOOC performance. It is known that online learning environments require greater levels of self‐regulation, and that high levels of motivation are crucial to activate these skills. However, motivation is a complex construct and research on how it functions in MOOCs is still in its early stages. Research presented in this article investigated how motivation and participation influence students' performance in a MOOC, more specifically those students who persist to the end of the MOOC. Findings indicated that the strongest predictor of performance was participation, followed by motivation. Motivation influenced and was influenced by students' participation during the course. Moreover, situational interest played a crucial role in mediating the impact of general intrinsic motivation and participation on performance. The results are discussed in relation to how educators and designers of MOOCs can use knowledge emerging from motivational assessments and participation measures gleaned from learning analytics to tailor the design and delivery of courses. © 2016 John Wiley & Sons Ltd

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.

These cases indicate that using Facebook as part of learning and teaching is as much of a challenge for many students as it may be for most educators.