For more than a decade, a discussion has been ongoing about changes brought about by the increased availability of a wide range of technologies and mobile devices, the possible differences in the way students learn and study when using new technologies and, in particular, differences in technological skills attributed to generational
attributes. This has sparked the ‘Net Generation Debate’ in educational literature, an ongoing discussion on the impact of age and technology related factors on student learning.
Tapscott (1998) described a new generation of students born since 1977 as the ‘Net Generation’. Tapscott’s premise was that this generation of students had had access to computers and mobile devices since early childhood, and were exposed to digital technologies in every facet of their lives, which impacted on their personalities, attitudes, and approach to learning. Consequently, according to Tapscott, Net Generation students were likely to be more technology savvy than previous
generations with a natural aptitude for using technologies, thus creating a digital divide between students and educators with subsequent implications for teaching and learning. The concept of a Net Generation, and possible generational differences in students’ learning, has since been frequently discussed in the literature with a range of possible traits being attributed to students; for example, multitasking, having an IT mindset, and a preference for collaborative learning (e.g. Dede, 2005; Frand, 2000; Oblinger, 2003, 2004; Rickard & Oblinger, 2003). This proposed new generation of students has also been described by other authors as Generation Y, the Nintendo Generation and Millennials and, depending on the author, assumed to have been born in or after 1980 or 1982 (e.g. Brown, 2000; Howe & Strauss, 2003; Oblinger, 2003; Raines, 2002; Rickard & Oblinger, 2003).
Comparisons of generational differences sparked considerable debate following Prensky’s (2001) description of new generations of students as ‘digital natives’; that is, those who have grown up with digital and mobile technologies. A number of authors have questioned the existence of such a generation due to the lack of theoretical and empirical evidence (e.g. Bayne & Ross, 2007; Bennett, Maton & Kervin, 2008; Kennedy, Krause, Gray, Judd, Bennett, Maton et al., 2006; Sheely, 2008). Prensky’s viewpoint was that digital natives have grown up in a world surrounded by new technologies and mobile devices and are skilled in using new technologies and gadgets, whilst older generations represent ‘digital immigrants’ for whom adapting to the use of new
technologies can present some difficulties. Similarly to Tapscott (1998), Prensky (2001) believed that the presence of the new generation of digital natives required significant change to pedagogy and teaching practices. Prensky’s (2001, p. 1) statements (e.g. “...today’s students think and process information fundamentally differently from their
predecessors...” and “...it is very likely that our students’ brains have physically changed – and are different from ours – as a result of how they grew up...”), and unsubstantiated claims that students have radically changed, have come under much criticism, particularly for being speculative and not evidence based (Bennett et al., 2008; Brown & Czerniewicz, 2010; Jones & Czerniewicz, 2010).
The Net Generation debate continues as educators seek to establish whether there are other generational differences in students beyond simply an increased confidence in using technologies in some students due to exposure to computers and mobile devices. Several research studies have found that that although Net Generation and older generations of students may have different comfort levels with learning
technologies, students of all generations share common values regarding pedagogical practices (Garcia & Qin, 2007; Gorra et al., 2008; Hartman, Moskal & Dziuban, 2005). Garcia and Qin (2007) found that learning preferences and attitudes towards effective learning and teaching activities in university teaching were consistent across age groups and, even though Net Generation students involved in the study were more electronically adept, they were also comfortable with traditional learning models. Furthermore, Oblinger and Oblinger (2005, p. 2.9) suggested that “age may be less important than exposure to technology”, and that a person who has considerable experience with mobile or emerging technologies may exhibit traits that are identical to those attributed to Net Generation students or Prensky’s ‘digital natives’.
Anecdotal reports of increases in students’ use and ownership of new and mobile technologies for learning have prompted a number of formal studies focussing on students’ ownership and access to learning technologies and mobile devices, and how
these devices are used in learning. Several of the studies were conducted specifically in response to the debate about generational differences (e.g. Jones & Ramanau, 2009a; Jones, Ramanau, Cross & Healing, 2010; Kennedy et al., 2009; Kennedy, Judd, Churchward, Gray & Krause, 2008; Oliver & Goerke, 2007).
Studies conducted with first year students in Australia by Kennedy et al. (2008) and in the UK by Jones, Ramanau, Cross and Healing (2010), both showed that, although first year students used a wide range of technologies including mobile devices, their use of these technologies for learning was not homogeneous across groups or clearly
definable by age. However, students in both studies were confident with technology- related learning activities centred on communicating and accessing information. Jones et al. (2010, p. 730) found that, though the vast majority of students made extensive use of mobile technologies and computing facilities for communicating and accessing course materials and resources, it appeared that students’ use of technologies “seem to respond to the requirements of their courses, programmes and the universities”. Overall, the study by Jones et al. indicated that there were individual differences in students’ uses of learning technologies and that students’ engagement in new and mobile technologies for learning may be influenced by institutional contexts and modes of teaching and learning.
These results compare with findings by Conole et al. (2008) who found a mismatch between institutional perceptions of students’ use of technologies and their actual more sophisticated use of emerging technologies, and consequently a mismatch
between the technologies offered to students by educators. Conole et al. (2008) found in their study that students were generally confident in the use of technologies and
created their own social networks, beyond those offered by their course, to meet their personal learning needs.
The study conducted by Kennedy et al. (2009) also attempted to ascertain whether there is evidence of a technological literacy gap between students and lecturers. Lecturers and students participated in a survey and focus groups providing a rich set of data. The study discovered that there was great diversity in students' and lecturers’ experiences with technology, and their preferences for the use of technology in teaching and learning. Both groups relied on technologies mainly for communication and information access, but social networking and Web 2.0 technologies were used for study purposes by only a small minority of students. In relation to a technological literacy gap between students and lecturers, the findings showed no significant differences between academic staff and students with regards to their technology- based activities, though a key finding was that “staff were more sceptical and more unsure about the potential of technologies for supporting teaching and learning” (p. 23).
Beyond the debate about students’ level of experience and comfort with new
technologies being attributed to generational factors, a number of studies in Western countries have shown that students increasingly have access to and utilise mobile technologies, that mobile devices have become more common place in universities, and there is growing evidence of students of all generations increasingly using mobile technologies and tools for learning purposes (e.g. Alexopoulos et al., 2009; Bennett & Maton, 2010; Caruso & Kvavik, 2005; DiGangi, Jannasch-Pennell, Yu & Kilic, 2005; Kvavik et al., 2004; Nagler & Ebner, 2009; Oliver & Goerke, 2007; Salaway et al., 2007;
Salaway et al., 2008; Sharples, 2007; Smith et al., 2009). The studies showed that the majority of students had laptops, mobile phones and access to wireless networks and that the use of these technologies by students was becoming widespread.
For instance, the studies by Jones et al. (2010) and Kennedy et al. (2009) indicated high levels of student laptop ownership (65% and 77%), broadband Internet access (55% and 76%), and showed that almost all students had mobile phones and MP3 players. Though students possessed mobile devices, they were not necessarily used for learning purposes. Similarly, the EDUCAUSE Centre for Applied Research (ECAR) study of students and IT (Smith et al., 2009), a longitudinal study conducted annually in the US since 2004, showed in its findings that there was an increase in students’ ownership of mobile technologies, with most students owning a laptop and mobile phone. These devices were used for studying, social interaction and entertainment. The 2009 ECAR study results showed laptop ownership had increased from 65.4% in 2004 to 88.3% 2009, and more than two thirds (73.7%) of the respondents also owned an Internet- capable handheld device (e.g. smartphone); however, many (35%) did not use the Internet connectivity of their phones.
Although a number of recent studies have indicated that in some university contexts students in the Net Generation age group are not all highly skilled in the use of technology and do not show different learning preferences to previous generations (Gorra et al., 2008; Jones et al., 2010; Kennedy et al., 2009; Selwyn, 2009), several studies have found that, overall, younger people possess a greater range of mobile or networked technologies in their households, are more likely to use new technologies and to use them more frequently than previous generations (e.g. Helsper & Eynon,
2010; Steinbrecher, 2008). MacCallum (2009) identified that students who were experienced with using computers were also likely to be goal oriented and
independent learners, characteristics that resulted in students being more likely to adopt new technologies. According to MacCallum (2009), goal orientation may encompass intrinsically motivated learning goals (e.g. mastering new knowledge) and extrinsically motivated performance goals (e.g. grades).
Gender differences have also been studied extensively with relation to students’ adoption and attitudes towards learning technologies (e.g. Bauer, 2000; Busch, 1995; Carrington & Pratt, 2003; Cooper, 2006; Kuo, 2004; Liff & Shepherd, 2004;
Markauskaite, 2005; McIlroy, Buntinga, Tierney & Gordon, 2001; Whitley, 1997) and, although some gender differences have been found, on the whole, no specific gender dominance is evident. Quite the opposite, there is some evidence of a diminishing gender gap in students’ use of technologies (Kennedy et al., 2009; Liff & Shepherd, 2004; Smith & Oosthuizen, 2006). For instance, Kuo (2005) established that females were found to have more positive attitudes towards wireless computing than males. Others have found a variety of results relating to gender differences in online
communication (Bråten & Strømsø, 2006; Jones, Johnson-Yale, Millermaier & Pérez, 2009), preferences in tasks or activities (Jones et al., 2010; Kennedy et al., 2009), and time spent using computer technologies (Markauskaite, 2005). For example, in Bråten and Strømsø’s (2006) study of first year education students, males demonstrated higher levels of participation in online communication than females, whilst Jones et al. (2009) found that female students tended to use the Internet for communication and study purposes more frequently than male students.
This section discussed the Net Generation debate, and the use of m-learning devices by students. In the past, this use has been influenced by issues such as cost, lack of standards and compatibility (Clyde, 2004; Demb, Erickson & Hawkins-Wilding, 2004). However, as technologies and wireless support infrastructures are continually
evolving, these concerns are diminishing. As discussed, students’ ownership and use of laptops, mobile phones and access to wireless networks is becoming widespread though the range of mobile devices used by students can be variable depending on a number of factors including student demographics. Further studies, specifically focussed on m-learning, are discussed in the next section.
2.4 M-learning Studies: Educational Applications of M-learning