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«1 Digital literacy in higher education: The rhetoric and the reality Lorelle J. Burton, Jane Summers, Jill Lawrence, Karen Noble, and Peter Gibbings ...»

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Prensky (2001) argued that because digital natives know no different way of communicating, current education systems need to accommodate varied styles of thinking and working. More specifically, because digital natives are “active experiential learners, proficient in multitasking and dependent on communications technologies for accessing information and for interacting with others” (Bennett et al., 2008, p. 775), educators need to apply technology in sophisticated ways to support their learning.

Although not seen as a homogenous group, commencing tertiary students coming directly from high school are thought to prefer a different way of studying and to process and use information differently than generations before them. However, these learning preferences might not necessarily align with current teaching practices (Helsper & Eynon, 2010). Today’s students are typically no longer happy with the traditional methods of face-to-face teaching and are seeking a move towards a predominantly electronically based curriculum due to their different ways of learning and their demand for more flexibility during study (Burdick & Willis, 2011).

The reality of digital natives in higher education It is problematic to generalise about the skills of digital natives using an age definition. Evidence indicates that while many young people are skilled in using technology, a significant proportion do not have access to digital technologies or skills to be considered “expert” (Eynon & Malmberg, 2012).

Further, by focusing on the group who are adept at new technologies, those with less skills can be neglected and become isolated in both socioeconomic and cultural areas (Bennett et al., 2008). A further complication in assuming that first year students are homogeneous groups (Prensky, 2001), is that little attention is given to the needs of mature-age or other marginalised groups within these cohorts. Indeed, the Australian context and experience contradicts this assumption of homogeneity, with first year students being represented by diverse demographic and socioeconomic characteristics (Andrews & Tynan, 2012; Conole, 2008; Fitzgerald & Steele, 2008; Kennedy et al., 2009; Wood & Dodd, 2010).

Students can use ICTs for both personal and learning purposes. Digital natives might own a personal computer and/or mobile device, however, many report lower skill proficiencies in relation to learning technologies than might be expected (Kvavik, Caruso, & Morgan, 2004, as cited in Bennett et al., 2008).

Factors such as socioeconomic status, background, and gender can also influence the use and understanding of technologies creating a divide within the group of digital natives themselves. For example, Dahlstrom, de Boor, Grunwald, Vockley, and Oblinger (2011) asked commencing students to reflect on their own technology skills and almost one third believed they didn’t have the skills needed for effective study. A large number of students in the Dahlstrom et al. (2011) study indicated a desire to possess more specialised software skills. Thus, while some scholars believe those born within a certain period have developed technology skills naturally throughout their lives, many digital natives do not feel confident in using technology to support their learning.

There remains a lack of clarity in the use of terms digital natives, Net generation and of generational boundaries (Jones & Czerniewicz, 2010). An Australian study of first year university students showed that while they were considered “tech-savvy”, these skills were limited to use of technologies such as computers, mobile phones, and email (Kennedy et al., 2008). The skill sets of digital natives are uncertain as is the knowledge of what digital natives expect from their studies. Kennedy et al. (2008) questioned the rhetoric of the need to overhaul teaching methods to accommodate the needs of the digital native generation. They argued that educators need to consider the learning needs of a wide variety of generational students before time and money are expended on changing systems or how educators teach. Opportunities to actively engage both digital natives and digital immigrants in learning should be paramount in any pedagogy.

Thus, the digital native discourse does not provide an especially accurate nor objective account of young people and technology. The argument is reductive and implies that young people do not require support to operate effectively in digital learning environments. The true picture is much more complex. Aside from potential inequalities in access and engagement, many young people’s actual use of digital technologies appears rather more limited in scope than the digital native rhetoric might suggest. Some recent studies indicate that children and young people do not necessarily expect or even want to use technology in institutional settings such as schools or libraries in the same manner as they do at home (Lohnes & Kinzer, 2007). Indeed, young people appear to be more discerning in their desire to use (or not use) digital technologies in all aspects of their lives (Selwyn, 2009).

Myth 2: Digital delivery as a panacea Students have a need to feel connected with other students, with their lecturers, and with their university. They might use social media such as Facebook to communicate with fellow students regarding their studies, but rarely use this technology to interact with their lecturers (Echo360, 2012).





Social interaction has been strongly related to online learning enjoyment, effectiveness of learning online, and the likelihood of taking another online class (Muilenberg & Berge, 2005). Online learning offers greater flexibility than face-to-face study, however, course structure and educator support will always be vital to ensuring quality and facilitating positive learning experiences for students. Depending on the design of the course, lack of face-to-face interaction and often limited synchronous exchanges can demand extra time and energy to establish an online learning community.

Online learning environments can also make more demands on students than traditional contexts in terms of expected study behaviours to achieve academic success. Students quickly learn how much they rely on teacher explanations of content and activities in face-to-face classrooms (Howland & Moore, 2002). While the nature of the online environment has necessitated this shift away from reliance on lecturers, it cannot be left to students alone to meet this demand.

Students currently prefer a blended learning platform and evidence indicates it can be more effective than strictly face-to-face or online instruction alone (Akyol, Garrison, & Ozden, 2009; Wold, 2013).

Blended learning combines the benefits of collaborating with other students with the advantage of studying when, where, and how individuals want. Approximately 84% of surveyed American and Australian higher education students believed this preferred method of learning helped them to understand better (Echo360, 2012; Uzan & Senturk, 2010; Wold, 2013;). Blended learning environments are believed to give students more control over their academic experience; blended learning enables students greater flexibility to learn at their own pace and to better manage course demands with other life commitments (Echo360, 2012).

The task of bridging the transition from traditional to individualised, facilitated learning is fraught with difficulties. While face-to-face pedagogy can inform online pedagogy, it cannot automatically be transferred to the online learning environment. Online pedagogy should also be considered to create a successful and meaningful course experience (Gill, 2003; Li & Akins, 2004). Success in meeting the needs of online learners requires new teaching methods and strategies that support knowledge creation and problem solving skills (Quinton, 2010). Any attempt to accommodate the skills and preferences of digital natives will inevitably compel education designers to consider strategies that are in line with students’ expectations and demands. Such strategies might include providing dynamically generated teaching materials that are relative to the current context; search and support tools that enable interactivity among learners; and online assessments that provide immediate feedback tailored to students’ individual performance and learning needs. All students can potentially benefit from this enhanced interactivity and personalised learning journey.

Research indicates that online learning is a medium not superior to traditional class rooms (Means, Toyama, Murphy, Bakia, & Jones, 2009). Online classrooms typically differ from face-to-face contexts in terms of time spent in discussion, curriculum, and pedagogy, and a combination of these elements influences students’ opportunities for collaboration and learning outcomes. Quality interactions among learners, content, and lecturers can help “create a sense of social, cognitive and teaching presence, thereby allowing students to participate in an engaging and cognitively enriching community of inquiry” (Rourke, Anderson, Garrison, & Archer, 2001, p. 3). Quality online learning is not assured, and requires attention to these factors to ensure maximum positive impact.

The potential of a digitally delivered higher education is not being realised. Andrews and Tynan (2012) argued that the promised improvements to communication and interaction are yet to be achieved.

There is a minimal uptake of technologies by lecturers and a general lack of understanding by educators of the potential of digital education technologies in supporting pedagogy (Apperley & Walsh, 2012;

Margaryan et al., 2011). A common theme is that the lecture materials themselves are not changed;

they are merely delivered electronically, with little incorporation of ICTs to promote interactivity.

However, the online delivery of course content often demands a different approach. The course should be redesigned to incorporate opportunities for students to actively engage with others through their learning (Burdick & Willis, 2011).

Students’ expectations can also influence online learning experiences (Howland & Moore, 2002). While it is often presumed that online learning will be easier to fit around existing lifestyle commitments, online learning has very high attrition rates, with both academic and personal circumstances contributing to students dropping out of online courses (Martinez, 2003). The reality is that online learners need to be highly motivated and self-disciplined with great persistence and commitment to experience success. Both confidence and experience with technology can influence students’ online learning outcomes (Muilenberg & Berge, 2005).

Learning in an online environment involves much more than mastery of particular technologies. Student confidence increases the more familiar one becomes with online learning contexts (Muilenberg & Berge, 2005). As experience with technology increases, students perceive it to be easier to use and more useful; in turn, they are more likely to persist (Stoel & Lee, 2003). Students who report positive attitudes about their online learning experiences tend to be constructivist learners, recognising the need to be more independent and self-directed in their learning (Howland & Moore, 2002). Other students can feel overwhelmed by the online learning experience and the need to rely on themselves. Such students typically express a need for more structure, guidance, and feedback from the lecturer. They also desire packaged material to step them through the learning requirements (Howland & Moore, 2002) and are generally unable to self-direct their learning. They typically interpret this need for self-responsibility in learning as “abandonment and feeling isolated” (Howland & Moore, 2002, p. 187). Therefore, while being competent and confident with technology is a clear advantage, learning in the online environment involves much more that being ICT savvy.

Method This study was designed to examine the experience, attributes, and digital learning needs of first year cohorts. The focus was to determine the level of students’ digital literacies. The research design comprised both quantitative and qualitative components.

Firstly, the research employed an online survey to measure students’ perceptions of their digital literacies. A pilot study comprising an online survey of students in Semester 3, 2011 attracted responses from experienced online learners (N= 532). They were asked to describe various aspects of their digital learning experiences, including how often and how easily they accessed various university support systems. The self-report survey was developed to enable tertiary students to identify and build their individual digital learning capabilities. The framework mapped all relevant dimensions of digital literacy, reflecting the argument that technical experience and learning experience are different issues.

A larger-scale study followed in Semester 1, 2012 (N = 652), using the same online survey and focus groups. The aim of these focus groups was to ascertain students’ skills in managing online learning and to receive feedback on an online resource (DART) developed to support students’ digital literacies.

Instrument In the survey, students were required to self-report their level of confidence in using various technologies (1 = not at all confident; 3 = very confident). They were also asked to rate their level of confidence in accessing various supports at the university, and in performing various tasks on the university learning management system (i.e., USQ Studydesk). The quantitative survey data were collated and analysed.

Survey results The demographic characteristics of students in the current sample are summarised in Table 1. The digital learning experiences of Digital Natives (N = 407) and Digital Immigrants (N = 240) are summarised in Table 2.

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