«1 Digital literacy in higher education: The rhetoric and the reality Lorelle J. Burton, Jane Summers, Jill Lawrence, Karen Noble, and Peter Gibbings ...»
Respondents were asked to rate their level of confidence in using, and experience with, a range of technologies both generally and specifically related to their study experience at USQ. This data is presented in Table 3. Some differences were evident in how Digital Natives and Digital Immigrants rated themselves, both in terms of experience and confidence in using specific technologies. For example, the Digital Natives were more confident than Digital Immigrants in using instant messaging and social networking tools. However, although Digital Natives were more experienced and confident than Digital Immigrants, they were only “somewhat confident” in their abilities. Generally, the two groups showed comparable levels of experience and confidence. Respondents were also asked to rate how experienced they were and how confident they were in using a range of technologies on the University’s learning management system (i.e., USQ Studydesk). As the data was non-normal, a Mann-Whitney U test for differences between the means of the two groups was conducted with the confidence interval set at 99% (p.01).
Table 3 Digital Natives and Digital Immigrants Experience with and Confidence in using specific technologies
Results of this study, coupled with the outcomes of the earlier pilot study, support the notion that despite the commonly reported assumption, levels of experience with technology and confidence in demonstrating a range of digital literacies does not appear to be solely age reliant. Our data found small differences in the digital skills and levels of confidence in relation to age but the time spent online, both studying and for other purposes, was consistent across age groups. These findings suggest that this group of students regardless of when they were born (those over 30 generally assumed to have low levels of experience with technology and digital learning tools), are equally literate and confident.
While the myth of age being a factor in digital literacy was not supported by our current findings, some interesting gender differences in experience and confidence with technology were observed. Once again the mean scores were still in the somewhat to very confident range, but our data did show women to be more confident and experienced in using social networking technologies (F = 17.9, df = 1, p.01) and men to be more confident and experienced in using spreadsheets (F=9.489, df = 1, p.01), data bases, and voice and video conferencing (Skype). Whilst this finding was not related to the age of students and thus the myth of digital natives evidencing higher levels of digital literacy, it does support the notion that learning literacies are complex and multi-dimensional and that educators need to consider a range of indicators (i.e., age, gender and experience) when developing curriculum and learning support systems.
All students surveyed indicated confidence in using centrally provided support systems available to them at the University, but very few students indicated that they used these types of support, instead relying more on information from other students and academic staff directly. These findings are summarised in Table 4.
An interesting finding was that the majority of the Digital Natives in our sample opted for on-campus study rather than studying in a digital format. Both surveys found that the majority of USQ students were mature age learners (i.e., not school leavers) and most were also employed while studying. The majority of students reported reliable internet speed and connections (93%) and most have been using the internet for more than 5 years. Both groups of students reported that they rarely accessed support offered by the University, and that they tended more to rely on support from family, friends and other students. Academic matters were the main reason students sought assistance, including the need to understand assessment requirements, course content and key concepts. ICT issues were also rated highly in terms of support requirements.
Discussion: Implications for digitally delivered higher education Many higher education institutions have viewed online learning as the answer to meeting the learning demands of digital natives (Bennett et al., 2008). Whether educators support this view or not, the fact remains that digital technologies are now widely used across higher education settings (Dahlstrom et al., 2011). Dahlstrom et al. (2011) advocated that there are considerable advantages in using technology to
support learning, including:
1. Technology gives students easy access to resources and helps them dispense with administrative tasks and keep track of academic progress.
2. Technology makes students more productive.
3. Technology helps students feel connected.
4. Technology can make learning a more immersive, engaging, and relevant experience (p. 4).
Educational resources provided in a digital form underpinned by a digital pedagogy provide students with positive learning experiences, enabling them to study when and where it is convenient to them (Andrews & Tynan, 2012). This flexibility minimises the need to attend scheduled face-to-face lectures and tutorials. Advantages of digital content over more traditional print includes flexibility to change, ease of keeping materials up to date, and simplicity in searching the content (Nelson, 2006). Given the preference of students to streamline their studying, this digital format enables them to study whenever and wherever they want, more effectively. However, Nelson (2006) outlined two forms of digital
1. Digitised content; developed for traditional print, and following a linear organisation. Content may be scanned or digitised by optical character recognition.
2. Born digital content; originated, developed and produced within a digitally rich context. Content enables various features and capabilities of digital media for nonlinear organisation and interactivity.
Previous research has sought to demonstrate that online learning contexts perform as well as traditional contexts in terms of student achievement and learning outcomes. The principle of “no significant difference” was argued to support the validity and value of online learning and its equivalence with traditional methods (Simonson, Schlosser, & Orellana, 2011; Swan, 2003). The general argument was that “as long as the quality of instruction delivered over distance was as good as the quality of traditional education, there would be no significant differences in learning between them” (Swan, 2003, p. 3). Simonson et al. (2011) asserted that many conditions for quality online learning design are shared
with traditional contexts. These include:
1. The degree of active versus passive learning techniques;
2. The amount of flexibility and variety in how the course is presented and undertaken;
3. The nature, frequency, and quality of feedback;
4. The clarity and explicitness of goals or expectations, and
5. How much contact and guidance is provided by instructors.
However, such a simplistic argument creates the potential for ignoring the many complexities of quality online learning. This includes the need to consider the relative importance of different elements of online course design, such as the characteristics, skills, and practices of both students and lecturers.
Factors such as the degree of structure and transparency, and the communication potential of courses, have much more significance for online learning than traditional classrooms (Swan, 2003). Lecturers and students are separated by time and space, and the need for clarity of meaning becomes essential in online learning. Online learners therefore appreciate consistent, transparent, and simple course structures that support their overall student learning journey (Swan, 2003).
In arguing for the value of online learning, it is also important to consider the learning outcomes that may not be so readily available in traditional face-to-face classrooms. Swan (2003) argued that particular knowledge and skills, including divergent thinking, are better supported via online learning. For example, students who explored complex topics from multiple perspectives through hypermedia programs scored higher on measures of complex understanding than students presented with similar material through a traditional (linear) format (Swan, 2003). Interactive online learning environments enable students to more readily integrate multiple perspectives by interacting with other students’ points of view in asynchronous course discussions. Such online communications enable the exchange of meaningful ideas that promote critical thinking and underpin reflective learning skills (Echo360, 2012).
Guidelines for educators in establishing effective learning management systems Online learning environments typically focus on maintaining social connections with students via asynchronous discussion forums. Many learning management systems are based on students merely receiving information to be learned. However, the focus of online learning should be to provide a fully interactive and integrated learning process, taking full advantage of online flexibility and not merely presenting existing material online (Wold, 2013). Collaboration and social interaction are two very important contributors to effective online learning where students are required to craft, interact with and modify their thoughts based on other student’s feedback and ideas (Uzun & Senturk, 2010).
Understanding the skill levels of students is a major contributor to the success of online learning. The mobility requirements of today’s student means that content needs to be accessible via a variety of devices for study at any time and place by the student (Sheehan, 2012). Without this, students will potentially become disengaged and a barrier between the lecturer and student may be created.
Similarly, ensuring that academic staff are provided with appropriate staff development opportunities and incentives to support online learning are imperative to addressing the gap between rhetoric and practice (Andrews & Tynan, 2012). It is envisaged that ongoing professional development in this area will enable educators to gain confidence in using technologies that students find more engaging and relevant (Dahlstrom et al., 2011). Dahlstrom et al. (2011) also recommended that educators identify and make better use of technologies that are valued by students, integrating them into key learning experiences in transformative ways (such as participatory and collaborative interactions). This involves determining students’ technology needs and preferences and creating an action plan to better integrate technology into their courses. Importantly, students should be able to access this institutional and academic information from their varied mobile devices and platforms. This will help to meet expectations for anytime, everywhere, wireless access on students’ preferred learning devices. Moving towards a blended learning environment will also enable institutions to better meet students’ preferred learning styles and differentiated needs (Dahlstrom et al., 2011). To this end, the institution should establish or refine social media policies to support the application of social media in online learning experiences (Dahlstrom et al., 2011).
Rarely do online learning classrooms promote pedagogical diversity or provide students with the tools to accommodate their individual learning needs (Quinton, 2010). According to Quinton (2010), online learning environments should be based around three core principles: collaboration, self-organisation, and ecological systems. The online learning environment should provide opportunities for social interactions and knowledge transfer in virtual learning communities (Quinton, 2010). For example,
online learning communities should:
1. “Encourage and support students to negotiate learning pathways through a multiplicity of contexts and domains by applying ecological and connectionist design strategies to dynamically assemble clusters of teaching content and information (also useful for evaluation purposes).
2. Devise and apply intelligent feedback and cognitive support systems that interactively empower learner cognition and respond immediately to learner input through the dynamic assembly of content that is relevant to the specific learning needs of the individual.
3. Incorporate “on-demand” tools for facilitating and managing collaborative encounters whenever the need arises” (p. 344).
Thus, a complex array of factors and conditions underpin optimal online learning. Whether high quality interactions within a “community of inquiry” (Rourke et al., 2001) are achieved or not, students’ perceptions of, experiences with, attitudes to, and behaviours within, online learning contexts also influence overall learning experiences. Swan (2003) found that three general factors– clarity of design, interaction with instructors, and active discussion among course participants–influenced students' satisfaction and perceived learning. It is evident that a clear and consistent course structure, an instructor who interacts frequently and constructively with students, and a valued and dynamic discussion, underpin positive learning experiences (Swan, 2003). The authors posit that it is the interplay of these key factors that jointly supports the development of online communities of inquiry. This notion is supported by the work of Rodriguez and Ooms (2005) who found that confidence with technology was related to satisfaction with the online course experience, which in turn was related to perceived quality.
Additionally, motivation to learn more about technology was also related to students’ satisfaction of online learning experiences. Thus students’ perceptions of quality online environments related to their levels of prior experience and confidence in using digital tools in online environments. These perceptions and behaviours are mediated by external factors such as course design, pedagogical, and institutional factors. Efforts to ensure quality online learning experiences need to address both these intrinsic and external factors.