8.1 Introduction

There are a number of models that are used to describe the implementation and use of technology in higher education. These models range from process models (Marshall 2008) through best practice models (Krause, McEwen, and Blinco 2009) to student satisfaction models (Sun et al. 2008). Attempts have also been made at integrating these models into a holistic, multi-dimensional approach. This chapter will use Johan Badenhorst’s SILSTI (student, instructor, learning design, support, technology and institutional) dimensions as an organizing framework (Badenhorst 2013).

The dynamic interaction between technology and society is as present in academia as it is in the rest of the world. While technology enables various new and exciting possibilities, it also presents us with a constant array of new challenges. In an increasingly connected world students are more mobile, resulting in a more diverse student population than ever before. This diversity includes a wide range of digital literacy or the lack of it. Students are not the only ones whose needs have changed. The same goes for instructors, some who see technology as a threat, and others who see it as an opportunity, leading to problems for institutions in dealing with both laggards and maverick early adopters. While there are increasing needs for technological support, technology can also be a valuable conduit for providing support. Then there is the technology itself and the extent to which it strengthens current practice, and the extent to which it is disruptive and innovative. All this needs to be considered in the institutional policies and practices. This chapter will address questions such as what are students’ learning needs, why do some instructors embrace technology while others don’t, what are the design implications of technology for learning, what support do students and instructors need, what technologies are available and how are they best exploited, and what institutional structural and policy frameworks need to be in place?

8.2 Students

What are students’ needs? A report by the Organisation for Economic Co-operation and Development (OECD 2013) indicates that the traditional demographics of university students have changed considerably since 1995. In OECD countries there has been a growth in the percentage of students from 39% to 60%. The average age of students varies by country, from lower than 19 years (Belgium, Japan, and Indonesia) to over 25 (Iceland, New Zealand, and Sweden). There is a strong growth in women entering higher education and generally the percentage of students who study outside their own countries has doubled to 4%. Social sciences, business and law are the most popular fields and science, technology, engineering, and mathematics are the least popular fields (OECD 2013). The main needs of students are related to diversity, flexibility, and learning preferences (Lai 2011).

Aspects contributing to student diversity include the massification of higher education towards the end of the 20th century, which has led to a significant increase in students who enter universities as the first person in their extended families to do so. A further consideration is the internationalization of higher education, with students tending to study in countries other than their countries of origin. Thus the diversity of the student population is of both a socio-economic and a socio-cultural nature and speaks to the challenges of expanding access on the one hand and keeping education relevant to such diverse expectations on the other (Johnson et al. 2014).

The increase in diversity, as well as students’ knowledge of what technology can enable, brings with it a need for flexibility. Students want to be able to attend set lectures if they so wish, but they also want the ability to view (or re-view) those lectures in the form of online videos or online audio podcasts.

Students increasingly demand a flexible learning environment. Many students are self-supporting and need to work to support their studies. The result is that traditional timetable systems no longer accommodate students. Technology-enhanced learning comes into its own by providing numerous points of access. A more nuanced way of recognizing learning is required as well as a ways for students to bank certain skills through a system of badges that might add up to a qualification. According to the New Media Consortium’s Horizon Report (Johnson et al. 2014) games and gamification are two to three years from adoption in higher education.

The prevalence of Internet-supported learning management systems has meant that once they leave the physical classroom every student is a distance student. Andrews and Tynan (2012) identify five themes in discussing distance students: individualness, connectedness, quality, mobility, and resourcefulness.

Individualness calls for students to develop a personal learning environment. Such an environment should cater for students’ individual learning style as well as preferences (Dabbagh and Kitsantas 2012). Connectedness talks to the fact that students are on various social platforms and use various other applications to remain connected not just to each other, but also to their lecturers and to their most important sources of information. Quality refers to the “provision of learning materials; learning design; online interactions; integration of technology into teaching and learning; reliability of technology used for teaching and learning; and staff and student capacity in relation to the use of ICT for teaching and learning” (Andrews and Tynan 2012), while mobility refers to the ways in which students interact with multiple learning technologies as well as with the fact that they are physically mobile as a result of the use of the technology (El-hussein and Cronje 2010).

Much is being written about the current generation of students. They are variously called the net generation (Tapscott 2008), digital natives (Prensky 2012), or the millennials (Howe and Strauss 2009). Regardless of generation, it is clear that students live in a world where there is a major assault on their attention. Evidence shows, however, that students use mainly established technologies rather than innovative ones such as knowledge creation tools or social media (Margaryan, Littlejohn, and Vojt 2011).

In both developed and developing countries students have a well-defined set of expectations of technology, although their level of ownership and access may vary according to socio-economic factors. Student expectations include:

• high levels of access to and ownership of hardware
• a diversity of experience and skill levels: more variation within age-groups than between
• near-universal use of core technologies such as email, mobile phone, and web browsing for information, but low use of emerging ones
• some recreational technologies used more by younger individuals (Gosper and Mckenzie 2013).

Nevertheless, students state a preference for learning in traditional ways such as lectures and discussions with instructors, and their digital literacy cannot be taken for granted (Kregor, Breslin, and Fountain 2012, 1384). It is clear that students will have to be taught how to teach themselves and how to develop their personal learning environments in the context of ubiquitous technology.

8.3 Instructors

Why do some instructors embrace technology while others do not? Instructors (teachers, lecturers, professors, faculty) play a cardinal role in the acceptance of technology and the promotion of its use. Collis and Verwijs (1995) mention three elements that are likely to promote user acceptance of a technology: the extent to which it matches user needs, its ease of use, and its capacity to make work easier (Collis and Verwijs 1995).

In terms of the needs of instructors, there are extrinsic and intrinsic needs. The extrinsic needs relate to satisfying the institutional pressure for efficiency and effectiveness. These are often expressed in the form of institutional performance management systems as well as promotion and tenure policies. The internal needs relate to their performance as lecturers (Wagner, Hassanein, and Head 2008) and cover aspects such as relationships with students and peers, as well as reputation. Some research shows that e-Learning champions at universities have the ability to adapt to new things because they enjoy new and challenging events. Furthermore, they are committed to their students because they want to see positive results (Beukes-Amiss 2011). Academics also need to increase their reach to extend their sphere of influence beyond the classroom (Wagner, Hassanein, and Head 2008).

In terms of ease of use, one needs to determine if users find the system easy to use and easy to learn. Academics are more likely to adopt a learner management system if they have already had some other form of electronic communication with students. There seems to be a progression from emails, through social media (specifically Facebook) to the learning management system (Meishar-Tal, Kurtz, and Pieterse 2012). As these systems become more and more sophisticated they integrate with other systems so that sharing a file may even be as easy as emailing it to the learning management system which will, on its own accord, load it. When one considers if it makes instructors’ work easier it may be a good idea to consider the changing nature of the work of an academic. Research is moving online for literature surveys, conducting research, and the sharing of results. In the same way teaching is moving online.

There is a clear move away from lecturing towards more flexible models of information exchange and facilitation of learning. Blogs, podcasts, and even video-casting are interesting alternatives to lecturing. The role of the academic as instructor has changed (Wake, Dysthe, and Mjelstad 2007). Teachers are becoming writing mentors and orchestrators, rather than stage performers. The key to adoption by academics lies in the creation of “opportunities for concrete experiences capable of generating a personal conviction that a given technology is worth using and an understanding of the contexts in which it is best used” (Kukulska-Hulme 2012). It is essential, though, if a university wants to stay abreast of technology and methodology that it engages in constant professional development of teaching staff. In many universities this function is now done by a professional team of teaching and learning specialists who are dedicated to improving the quality of teaching and learning.

Nevertheless, the Horizon Report still sees the two most serious obstacles to innovation in higher education as the lack of digital fluency of instructors and the perceived lack of rewards for teaching (Johnson et al. 2014).

8.4 Learning Design

For the purpose of this chapter, the term “learning design” (Dalziel 2012) is used rather than the narrower “instructional design” as it encompasses a more holistic approach to teaching and learning with technology, specifically in a blended learning environment. A learning design is defined as “An individual example of a sequence of teaching and learning activities, also called a ‘design’ or ‘sequence’. A learning design is a plan for potential activities with learners, which is to be distinguished from a particular implementation of this plan with a particular group of learners” (Dalziel 2012, 33). In discussing such activities, the Horizon Report speaks of “the integration of online, hybrid and collaborative learning” (Johnson et al. 2014, 10). At the core of blended learning design in higher education is the challenge of creating learning experiences that will meet the needs of a diverse student population with a diverse digital literacy. Any learning design should consider all the technology available throughout the teaching lifecycle. What should students and instructors do to prepare before a class? What should happen in class? What should happen after class?

How do we deal with what the Horizon Report calls “competition from new models of education” (Johnson et al. 2014, 22), and how do we scale these elements of innovation? In this respect much has been done by Erik Mazur and others. The concept of the “flipped classroom” holds that students come to class prepared and then work on peer-learning projects that are modified in real time based on feedback given by the students through their mobile devices. In the flipped classroom the traditional concept of students as passive recipients of information is replaced by the idea that students come to class having prepared for the learning event online. They may have read some documents, taken web-based quizzes, watched online videos, etc. Students are given a question, asked to give an answer and then discuss their answers in groups. They are asked to present a modified answer if they have one. In this way the instructor can monitor progress and adjust the workshop as the students’ understanding develops (Berrett 2012). Students may also be asked to make blogs to help them reflect after lectures, and even to comment on one another’s blogs. In class students work in groups, solving problems related to the preparation, and technology is used to measure their progress in class. The drivers for these innovations are technological, economic and educational. Technology is increasingly enabling asynchronous teaching and individual learning. Economic factors drive institutions to find more efficient and effective ways of working, while educationally flipping a classroom resonates with the move towards student-centered learning (Berrett 2012).

A contemporary learning environment should take note of open courseware and the prevalence of massively open online courses (MOOCs). Open courseware is a response to a number of drivers in higher education, notably:

• globalization and the increased momentum for internationalization in higher education
• world-wide growth and increasing demand for access to higher education, with the projection that there will be 120 million students worldwide by 2020
• changing learner demographics and experience, and the demands of the dramatically increasing numbers of lifelong adult learners
• highly increased access to personal technology and social media
• the need for changes in cost, affordability, and economic models for higher education (Yuan and Powell 2013, 15).

The open courseware movement started in 2002, with MIT taking the lead in making their materials freely available online (Yuan and Powell 2013). MOOCs developed out of the open courseware initiative and have been higher education’s clearest response to the “demands for increased efficiency, more transparent accountability and better performance in both research and teaching” (Lai 2011, 1263). MOOCs have two distinguishing features: first, they are open to anybody and, second, they are designed to accommodate an indefinite number of participants.

There are two types of MOOC: xMOOCs and cMOOCs. The first is content-driven, essentially an extension of the institution’s existing content management system, and may be free or fee-charging. A cMOOC is based on a connectivist paradigm and relies more on the conversations between learners and the development of common understanding than on the presentation of content. The prevalence of free xMOOCs brings into question the use of traditional textbooks, while cMOOCs bring new possibilities to group work and collaboration across institutional boundaries. Both types of MOOC require institutions to rethink their pedagogical practices. Why have lectures when students can follow a cMOOC and learn from other students? Why should we have a library or a bookshop filled with prescribed textbooks when students can obtain content from an xMOOC?

The response to these two questions has precipitated a move away from traditional theories of pedagogy (which means the education of children) towards theories of andragogy (which means the teaching of adults) and self-directed learning or heutagogy (which means teaching yourself). Self-directed learning becomes an even more attractive option when one considers the increased diversity and volatility of the world of work. As a consequence there is a shift in the focus of university teaching and learning from content acquisition to the development of graduate attributes (Bridgstock 2009). Gamification has been defined as “the use of game design elements in non-game contexts” (Deterding et al. 2011, 9). Examples of game design elements include badges, leaderboards, levels, time constraints, limited resources, and turns. Of course the game also has a goal, which should be aligned with the learning objectives of the content or skill that has to be acquired.

A change in learning activities necessitates a re-think of the learning environment. Do we need as many classrooms as before if we can replace lectures with video clips or podcasts? Do we still need so many computer laboratories if students have mobile phones and tablets? Do we still need shelves filled with books when library resources are available digitally?

In a technology-rich environment the learning designer would consider appropriate technologies for guidance, representation, and sharing (Dalziel 2012). Sometimes the question may be how we “deliver” our personality through electronic media. Here is where Twitter, Facebook and LinkedIn may also be useful. Representation may be physical, by bringing the real world into the classroom or a field trip where students are taken to the real place. Alternately, the representation may be by simulation, electronic or otherwise. In a world where digital material is easily duplicated the distinctions between the concepts of sharing and distribution have been blurred. Traditionally a library was the vehicle for sharing scarce resources by lending the elements sequentially to lenders. A digital repository shares content by making it simultaneously available to as many users as may access it at any given time. Essentially it distributes content rather than sharing it. Similarly cloud-based collaborative software allows students and staff to share tasks and engage in them simultaneously, independently of location. Two students from anywhere in the world can simultaneously edit the same document and then share it with the instructor for comment or grading.

Since editing is always possible unless it is blocked, a project never needs to be completed. One such example is ABLEWiki “a publicly accessible, open access repository that documents and also creates awareness of our built environment heritage” (ABLEWiki 2011). This is an ongoing project where students and staff use a Wiki environment to compile a database of buildings of architectural importance in Pretoria, South Africa. In this way information is shared while at the same time students acquire knowledge and sensitivity regarding heritage issues. In this way teaching and learning, research, and community service are integrated.

In designing the learning experience, technology brings with it tools and resources. The tools include timetables, data management, data processing, and simulation. In terms of resources the whole range of media, from text to video, is available electronically, while human resources can be made more available over distance and time. The learning designer in a higher education environment has the task of matching all these means to the educational ends they have in mind. To ensure that these ends have been achieved, the designer has to consider the responses of end users. To what extent was the experience worthwhile? To what extent did technology enhance or distract from the experience? What other technologies or techniques could have been used?

Technology plays an important role in our re-thinking of assessment. Thanks to the constant editing ability, formative evaluation becomes much more possible and, given the students’ need for self-directed learning, formative evaluation and prompt feedback become much more important as students become more reliant on themselves. Much has been written about electronic summative assessment, ranging from multiple-choice grading to computer-based grading of free text.

The emerging discipline of learning analytics is making it increasingly possible to predict outcomes based on comparisons of trends with other learners. At this stage a very useful diagnostic tool under development is the “early warning system” incorporated in many learning management systems. Such a system tracks a number of indicators and then alerts instructors to students who fall outside certain parameters so that remedial action can be taken.

In terms of learning design, it should be possible to develop a framework that can be populated with learning instances of all levels of granularity. The Larnaca Declaration (Dalziel 2012) proposes a mark-up language peculiar to education that would enable instructors and teachers to describe every learning unit in such a way that it can be compared, catalogued, classified, and replicated. Once such objects have been developed they can be stored as learning activities and then incorporated in learning tasks. Various learning tasks would make up a module. These can then be escalated to levels of courses and even years of study. In this way an institution would have a complete catalogue of its learning on which to draw, no matter what the particular needs of a learner or group of learners are. As in all cases of standardization, a major obstacle to such development lies in the high level of cooperation required by academic staff, as well as a high level of top-down regularization. Nevertheless the development of such a standard will make it easier for students to form their own personal learning environments.

Personal learning environments enable students to assemble their own set of tools and resources for self-regulated learning. Students use such a system to mirror the conventional learning environment, to reflect, to showcase their skills, and to network and communicate. As with other digital learning solutions the development of such environments requires that students develop digital, meta-cognitive, and heutagogic skills (Valtonen et al. 2012).

8.5 Support

In a world of information overload and self-directed, learning students need support to cope with their post-school environment, while instructors often need both technological and methodological support.

Following a meta-analysis of the literature Minaar proposed a useful model of student support for e-Learning (Minnaar 2011).

The model is based on a pedagogy of e-Learning and comprises two central elements, technology and human factors. Student support comprises integration and resolution on the one side, and triggering events and exploration on the other. Triggering events and exploration include motivation, relationships with others, face-to-face contact, and critical thinking, while integration and resolution involves orientation, support from the instructor, peer interaction, stress alleviation, and assessment.

From a technology perspective there is the need for support with the integration of multiple tools, technical proficiency, stable networks, and cultural and political issues. On the other hand, the triggering events and exploration talk to an orientation towards technology, a wide range of resources, information being available before the inception of the course, and the importance of technical skills.

Tinto identifies support as an essential condition that enables students to succeed with their studies, particularly when it is paired with high expectations (Tinto 2012). Other elements include frequent assessment and feedback, as well as active involvement with other students and lecturers. He also sees the classroom as the core of student life and education (Tinto 2012). The role of the learning management system and of social software in providing a platform for such support cannot be underestimated.

When it comes to instructor support Beukes-Amiss identifies eight elements that e-Learning champions require from their institutions:

• sufficient technological infrastructure
• a conducive environment to operate in
• direct management buy-in
• an approved and sufficient budget for e-Learning activities
• a dedicated e-Learning team working within an e-Learning unit
• adequate time for champions to engage in their e-Learning activities over and above their other activities
• sufficient opportunities to train and transfer skills to other staff members within their institutions
• budgeting for incentives (Beukes-Amiss 2011, 224).

8.6 Technology

What technologies are available and how are they best exploited? In discussing technology at universities it may be useful to use the entrenched elements of physical universities as a point of departure, and then to see how this is metaphorically paralleled by technology. It may then be necessary to see where the metaphor breaks down as certain disruptive technologies may well be enabling practices that may not have been seen at universities before. At the same time some practices that have died out may now be revived, but in a digital guise. In a certain sense the industrial one-size-fits-all lecture-driven model is beginning to make way for a return to the classical individual scholar–tutor relationship, but with the tutor being technologically enhanced by a learner management system and a personal learning environment.

The first element associated with a university is usually a campus. The campus may or may not be a dedicated space that belongs to the university alone. Some universities have an estate-based campus that can be isolated completely from the surrounding areas. Other universities are part of the fabric of the town in which they are, and essentially are a number of buildings interspersed with other structures of civil society. In much the same way some universities have a dedicated “virtual campus” complete with a username and password that encompasses absolutely everything that a student may need at that university, while others have a minimum presence on the Web, and it is up to students to find their own way in the maze of university software and third party software.

No matter which type of real or virtual campus there is, the university has a main entrance. This main entrance serves the purpose of both inviting people in and keeping out those who have no business there. In the virtual campus that function is fulfilled by the university website with its dedicated login and password for students to access the campus. Inside the campus there are a number of areas: the administrative area, the academic area, and the social area. The administrative area comprises admissions, finance, academic records, etc. These are digitally represented in various computer-based administrative systems both inside and outside the learning management system. The academic area has lecture theatres, studios, laboratories, seminar rooms, and the library. The social are has a cafeteria and student residences. All three of these areas are replicated in a virtual campus. In a formal virtual campus these functions are fulfilled by bespoke software, while in a more informal campus publically available software may be used.

The virtual counterpart of the lecture theatre is played by online study guides, videocasts, and podcasts. In informal campuses the Kahn Academy and an assortment of YouTube videos may form the lecture theatre. Studios and laboratories exist in the form of software such as spreadsheets, word-processing software, digital-image generating or manipulating software, etc. Seminar rooms are replaced by chat rooms in their various guises. Kathy Schrock’s Bloomin Apps (Schrock 2011) website contains the most comprehensive list of websites and mobile applications that are appropriate for use at every level of Bloom’s taxonomy of educational objectives.

On the social front the obvious parallel for the cafeteria and the dormitory room is Facebook. The 2014 Horizon Report indicates the “ubiquity of social media” (Johnson et al. 2014) as one of the key trends to watch in higher education. It is interesting to note that Facebook actually had its origins as a digital catalogue for a university dormitory. While much discussion on Facebook could be trivial, students and their instructors tend to share valuable information resources on their timelines, and students use Facebook as the venue for pre-examination study groups.

The Google search engine is the technological affordance most used by students. In a list of the 10 technologies most used by students, Google appears first and university library databases ninth (Gosper and Mckenzie 2013). This may be explained by the ubiquitous presence of Google and its ease of use. Google has become the library and Google Scholar the reference section.

Where the metaphor breaks down, though, is in the disruptive influence of Web 3.0 technologies on teaching and learning. For the purpose of this chapter Web 3.0 will be defined as those technologies where machines form a part of the meaning-making process. Where Web 1.0 consisted of static web pages and Web 2.0 has user-created content, Web 3.0 is the product of the collaborative wisdom of users and computers. The most obvious example of a Web 3.0 technology is Google’s ability to complete an individual’s search string predictively based on where the user is, what previous searches the user has done, and what searches other people are doing. Gone are the days when one of the biggest problems in finding online help was knowing what to ask. Thanks to Web 3.0 technology, more often than not one simply asks a question the way you would of a colleague, and Google finds an answer.

Closely related to this are connected tools or applications such as the social navigation software Waze. Not only does it act as a satellite navigator, it also tells you who else is on the road, what obstacles they have encountered, what alternative routes there are, and where your friends are. To make matters even more complicated various applications are connected to one another through the cloud, so that should one create a note in Evernote, it uses data from your online calendar to suggest an appropriate heading for the note. Furthermore, thanks to cMOOCs information is increasingly being created collectively by the multiple participants in the course, rather than individually by an instructor.

These disruptions have implications for institutional structure and policy. If, for instance, students co-create their knowledge with their instructors, then to whom does that information belong?

8.7 Institutional Dimensions

What institutional structural and policy frameworks need to be in place? In developing an enabling environment for technology in higher education a technology policy needs to start by changing its culture of teaching and learning (Lai 2011). This change in culture needs to acknowledge from the outset that, thanks to online learning, flipped classrooms, MOOCs, and open resources students are likely to learn progressively more from sources outside the classroom than inside. This means that activities in a classroom need to be structured differently. There is also be the need to balance the task of the instructor in providing links and hints to information, and the task of the student in searching and retrieving information, with students being led towards independent learning as they progress.

Such re-structuring will influence decisions regarding both staff and physical infrastructure. If students learn more outside the classroom than inside, does this mean they need to attend class less frequently? If they do things in the classroom other than sit and listen to traditional lectures, does that mean that the physical layout of the classroom might have to change? Indeed the very structure of the lecture needs to change. If one considers how many students attend to their mobile phones or other devices during lectures the question arises of how to incorporate those devices into the regular lecture.

The prevalence of MOOCs, as well as the development of rhizomatic learning structures, together with the gamification of education is leading to further blurring between formal and informal learning. Where students are able to obtain badges for knowledge, skills, and attitudes attained outside the university, what accommodation is being made to recognize those badges or other evidence of learning inside?

These changes will require much consultation with all stakeholders, including students, instructors, administrators, content providers, technology providers, accreditation bodies, and future employers (Wagner, Hassanein, and Head 2008). If students are more self-reliant with the development of personal learning environments, there needs to be an understanding of their roles and responsibilities. The policy will have to give guidelines to instructors regarding their new roles in an information-rich environment, and will have to pay particular attention to the re-training of current academics as well as the required competencies of new entrants into academia. Furthermore, academics will need to be incentivized to promote innovative teaching with technology. Administrators have to address the balance between the three pillars of academic management: efficiency, access, and quality. Technology can, if applied correctly, widen access and increase efficiency without compromising quality. It can provide off-site access as well as after-hour access. It can supply digital reproductions and storage, as well as automate various administrative and academic tasks. It can keep meticulous records of any events and can monitor progress on a continuous basis.

A teaching and learning policy for a technology-rich university cannot be silent on the role of content providers. With the increase in emphasis on open content, providers of copyrighted content have to be very creative in deciding what kind of value their content adds. The use of electronic content also brings with it interesting new dimensions in terms of its curation. At this early stage of electronic publishing the metaphor of the book is still very much foremost in the minds of lecturers, but increasingly information providers are looking at radical new ways of making content available. A book is no longer a collection of physical pages enveloped between covers. The same chapter may appear in more than one book. Books can be assembled and delivered in real time. Electronic books can have multimedia objects such as sound files and even video embedded in them.

A further issue lies in the pricing and licensing of such content, with considerations such as world-wide rights and inter-institutional collaboration to reduce costs. Then there is the issue of who should bear those costs. Some electronic resources are licensed to the campus and others to individual students or academics. Thus ownership becomes an issue. If the digital artefact is licensed to the campus, then once the student leaves the university the resource is gone. Together with costing comes the problem of the ephemeral nature of technology. When a student buys a physical book it becomes a permanent possession to be kept for life. An electronic resource can expire. An opportunity exists for alumni to continue subscribing to such resources through their alma mater, and universities can use this to strengthen their relationship.

Providers of technology also have a role to play. Once again universities have to decide if they are going to host their own resources or if they will contract third party cloud resources. Similarly, who will provide the computers or tablets? With portable computing becoming cheaper and cheaper it becomes more and more feasible for the university to expect students to bring their own devices, but then the debate extends to other resources such as email.

In a world of open information access, where the university is no longer the sole custodian of knowledge, one can also begin to consider the university’s role in accreditation. Is it correct that the same institution who teaches a student also examines and certifies that student? Increasingly the role of certification has been taken over by professional institutes. The university may offer the degree, but the institute offers the license to practice. Then again, does the university need to provide any tuition at all, or can the university become a body that just assesses and certifies? There is an increasing number of universities who provide a service where prior learning is recognized and where the student’s competence is assessed, but the student is not required to attend class at all. On the other hand, there are a number of tuition-only colleges who affiliate themselves formally or informally to a large correspondence university and provide contact tuition at an additional cost. With open content making information available across universities and across national borders the question of accreditation becomes interesting. Technology-enabled cooperation is bound to lead to more and more joint degrees.

Finally one looks at the end users of a university education: employers. For degrees other than the professional vocations such as nursing and social work there is a constant struggle between what employers see as a “job-ready” graduate and what a university sees as someone who is prepared for an uncertain future. Essentially the outcome should not be a knowledge-based job readiness, but rather the acquisition of the attributes and skills required. In the field of computer science it is often said that good coders teach themselves to code. The same could probably be said of good teachers, good lawyers or many of the other professionals. Once they have graduated they continue teaching themselves as part of their career growth. Maybe that is the key to what universities should be producing: people who are able to use technology effectively to build a future for themselves, whatever that future may be. Universities need to produce digitally literate self-directed learners who can develop their own life-long personal learning networks.

8.8 Conclusion

This chapter took as its point of departure the six elements that need to be considered in a review of technology in higher education: students, instructors, learning design, support, technology, and institutional dimensions (Badenhorst 2013). We are faced with an increasingly diverse and mobile student population whose digital literacy and self-directed learning skills cannot be taken for granted. We have a set of instructors who range from maverick innovators to technologically illiterate laggards, who tend to battle with keeping up to date, and the biggest obstacle with many universities lies in a perceived under-valuing of teaching by management. We need to develop innovative new learning designs that can accommodate rhizomatic learning and allow students high levels of choice so that they can develop their own unique skill sets for increased job readiness. Both students and lecturers need support to cope with the rapidly changing educational and socio-economic environment, and technology seems to be both the cause and the potential solution. In their policy development institutions will have to consider what their own unique strengths and differentiating characteristics will be in a world where technology makes institutional relevance and uniqueness more and more difficult to achieve.

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