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Brown (2009) reports, Recently, the Nielsen Norman Group study of teenagers using the web noted: ‘We measured a success rate of only 55 percent for the teenage users in this study, which is substantially lower than the 66 percent success rate we found for adult users’. The report added: ‘Teens’ poor performance is caused by three factors: insufficient reading skills, less sophisticated research strategies, and a dramatically lower patience level’.

A new generation is behaving fundamentally differently – there seems little real evidence beyond the rhetoric that the net generation is in some way different from its predecessors as a result of having been exposed to digital technologies. There is some moderate evidence that they may have different attitudes. There is a general change in society which has relevance for learning – certainly the overall context is an ICT-rich one, and people are using the Internet for a variety of learning-related activities. People are learning in different ways – although firm evidence of informal learning is difficult to gather, there is much by the way of proxy activity that indicates this is the case. There is growing dissatisfaction with current practice in higher education – there seems little strong evidence for this. Probably more significant to the culture of education has been the shift to perceiving the student as a customer. There is certainly little evidence that the dissatisfaction is greater than it used to be, but what may be significant is that there are now viable alternatives for learners. Universities have lost their monopoly on learning, which reinforces the next point.

Higher education will undergo similar change to that in other sectors – there are some similarities between higher education and other sectors, such as the newspaper and music industries, but the differences are probably more significant. However, the blurring of boundaries between sectors and the viability of self-directed, community-based learning means that the competition is now more complex.

The first is that there is lag between society's acceptance of a technology and then its adoption in higher education. Brown (2009) suggests that in society the stages of technology diffusion can be defined as critical mass (ownership by 20–30 per cent of the population), ubiquity (30–70 per cent) and finally invisibility (more than 70 per cent). If higher education were to wait for the invisibility stage to be reached before it engaged with a technology, then given the time it takes to implement policies and technology, it really will look outdated. For example, in 2007, those using social networks might have been in the minority; now they will be in the majority. This is the problem with waiting for data to determine decisions – if you made a decision based on 2007 data that social networks were largely unused, it would look out of date in 2010. What is significant is the direction of travel, not the absolute percentages at any given time.

Generally, the m-learning project made them more engaged with the content and activities of the course

In addition, some of the SMSes helped them stay motivated,

the SMSes helped them focus on the course, reminded them of important things

When we "teach" students in class in order to help them learn, we don't just help them understand the content of the lesson. We also provide tips, motivate them to do activities that will help move them along in the course, get them to participate in discussions and manage their learning/the course. It was the same with the SMSes. We believe, the will get enough content from the print module provided and from the face-to-face interactions with their tutors. So yes, m-learning was used to help "teach" as well as "manage" the student.

http://api.ning.com/files/U50Z6pDz8PFgpOps4yunShKHnKR0sbgJx7kyRnjI*eMXpEqJSiqz0n0GuUNtY4DBx3-BFMYIGIabLRg8EqkDO9-IevKFm5Bt/questionnairemobilelearningfirstquestion.pdf

citation levels of articles that are published online versus those that are in closed access journals. Hajjem, Harnad and Gingras (2005) compared 1,307,038 articles across a range of disciplines and found that open access articles have a higher citation impact of between 36 and 172 per cent. So publishing in an online, open manner aids in the traditional measures of citation.

This section will look at the most concrete realisation of the open education movement, namely that of open education resources. In particular I want to revisit the notion of granularity and how changes in this, afforded by new technologies, are changing scholarly behaviour.

Zittrain (2008) terms ‘generativity’, which he defines as ‘a system's capacity to produce unanticipated change through unfiltered contributions from broad and varied audiences’. Little OERs are high in generativity because they can easily be used in different contexts, whereas the context is embedded within big OERs, which in turn means they are better at meeting a specific learning aim.

Big OER projects have a variety of models of funding, and Wiley highlights three of these demonstrating a range of centralisation: a centralised team funded by donors and grants (such as MIT), linking it into teaching responsibilities (as practised at Utah State University) and a decentralised collaborative authoring approach (e.g. Rice Connexions, http://cnx.org).

The reasons for this are varied, including technical complexity and motivation. One other reason which the OpenLearn team suggest is that the ‘content provided on the site was of high quality and so discouraged alteration’.

– a great resource that is essentially impossible to reuse, or a really poor resource that you can easily reuse

an interest in providing teachers real-time suggestions about the best way to use their next 10 minutes, are relatively new areas for me.

• Online Self-Organizing Social Systems. http://opencontent.org/docs/ososs.pdf

I would like to invite students to reflect on the practical impact on people they would like to their educational technology / educational research work to have.