1. Introduction

The tertiary education ecosystem is, like nearly every sector, undergoing a period of change influenced by digital, networked technologies, as well as broader social and economic shifts. As a consequence, higher education institutions (HEIs) seek to harness new technologies to better serve current students and also to reach new student populations. Over the past twenty years participation in higher education has been expanding rapidly across the globe (Dohmen 2018), but also the expectations to widen participation in higher education have increased. Fifty years ago such considerations led to the establishment of specific national institutions in many countries (e.g. The Open University, UK), but the expectation is now for all, or at least most, higher education providers to contribute to widening participation. In the context of this expansion and efforts to widen participation, it is vital that people in medium-low and low-income countries are not left behind both in the debate on developments and in their opportunities to participate (Salmi 2017). A key reference goal, for instance, is the Sustainable Development Goal 4.3, which states: “By 2030 ensure equal access for all women and men to affordable quality technical, vocational and tertiary education, including university” (United Nations 2015).

This is a challenging time for the organisational design of universities and colleges. New technologies are facilitating a higher education, which leverages networked and information technology to provide more flexible and more responsive education without the need for the expensive infrastructure of a traditional open university (Daniel 2017). In this, there is considerable rhetoric around disruption in discussions on the impact of ‘game-changing’ technological change to society and business (Brynjolfsson and McAfee 2014; McAfee and Brynjolfsson 2017), but also to higher education itself (Barber et al. 2013). For instance, Christensen took his analysis of the problem of established institutions adopting innovation and applied it to higher education. He suggested that new entrants to the market could serve learners better through less “fussiness” about formal educational prerequisites and more agility (Christensen 1997; Christensen and Eyring 2011). This leads to a dominance of what can be termed a “Silicon Valley narrative” which highlights the potential of technology to revolutionise sectors, without analysis of the actual usage and impact (Weller, 2015).

Such a perspective on technology usage in higher education fails to analyse the ways in which it is currently deployed in a wide variety of global contexts. It also treats universities solely as content providers, whereas they are a more complex type of institution that provides a collection of interrelated services and functions. Moreover, this ‘disruption’ model of technology adoption in higher education, as for example evidenced in the rhetoric accompanying MOOCs, tends to propose one universal solution and application of technology, whereas the reality is likely to be nuanced and involve a variety of models. In the field of higher education research, HEIs are often referred to as hybrid institutions, which are influenced by their external environment, but also isolated from their environment through layers of institutional autonomy (Jongbloed 2015). While they could be described in the past as ‘loosely coupled expert systems’ (Kogan and Becher 1980; Weick 1976), changes to their governance (including autonomy and funding), their place in society, and the need for HEIs to remain financially sustainable means they are moving away from this model. They require organisational strategies, which balance traditional legacy in some parts of the organisation with innovation and extension in others.

This paper explores institutional strategies for leveraging the potentials of digital technology. The problem the paper seeks to address is how to represent the implementation of digital technology in such a way that it captures the wide range of practice globally.

This paper presents research undertaken for the International Council for Open and Distance Education (ICDE), a membership organisation in the field of open and distance education, and supported by a global advisory group. The aim of the research was to uncover key models being used by HEIs when they adopt new technologies, and specifically the role of open, online, flexible and technology-enhanced (OOFAT) modes of operation. The exploratory approach used sought to provide insights into the pattern of implementation in key teaching and learning processes by higher education institutions from across the globe.

2. Conceptual Model

In order to structure the study, it was necessary first to produce a conceptual model of open, online, flexible and technology-enhanced (OOFAT) that could be used to capture the practices of higher education providers. The model needed to provide sufficient structure to enable a synthesis aggregate of OOFAT implementation, while being broad enough to capture all possible use cases. To address this aim, the conceptual model started out from central processes in the higher education enterprise itself.

These are the so-called “bundles”, which make up the higher education provision package. Agarwal (2016) classifies these as: clocks, content and credentials. In other words, provision is made up of how higher education is delivered (“clocks”), what is delivered (“content”) and how achievement is made recognisable to third parties (“credentials”). In an alternative scheme, Mackintosh (2016) identifies six services which make up the university package. Following content services, he refers to teaching and learning as “interaction services” after Moore (1993), and identifies assessment and support services as additional distinct activities, which lead to credentialing services, and these are all supported by technical instruments, which ensure an effective learning environment (Miao et al. 2016). The first scheme can be seen as subsuming these six elements but is formulated on a higher aggregate level, since “clocks” is actually about place, pace and timing, as well as the form of delivery (online versus physical) and, if we follow Moore, “content” addresses the interaction between teachers, learners and content, including learning analytics.

With a slight reformulation for clarity and conciseness, the basic conceptual model used in this research was based on the following three central processes:

• Content – consisting of subject knowledge, support and guidance and learning analytics, which together make up the entirety of all didactical process.
• Delivery – consisting of the qualities of place, pace and timing of delivery of the content; in other words both the extent of physical and online provision and the question of the timing of key events (e.g. start and end points of learning processes) are included in ‘delivery’.
• Recognition – consisting of both assessment and credentialization, which are formal processes leading to recognition of learning achievements. Assessment is a phase of evaluation at certain times in a learning process, while credentials are awarded on completion of formal learning units. In both cases, these evaluative processes entail a formal endorsement of learning and lead to recognition of achievement of the learner by third parties.

But how are these core processes affected by technology? To answer this, two dimensions were used for each of the core processes, which both speak of new types of flexibility made possible through digitalisation.

• Organisational flexibility: The quality of flexibility is a question of “what” and “how” and relies on digital technology to reduce the need for physical presence; from static to dynamic and changing due to specific circumstances. So, each of the three central processes (content, delivery, recognition, and their sub-processes) can also be described by the extent to which they are delivered in a flexible manner, harnessing digital technology, i.e. through online and technology-enhanced learning environments.
• Procedural openness: The quality of openness is a “who” question and relies on how the principle of openness is integrated (in various ways) into the core processes (content, delivery, recognition, and their sub-processes); from closed group to open network. More open processes mean less limitations on who has access to and who delivers or controls content, delivery, assessment and recognition (cf. Hegarty 2015). This quality is not reliant on digital technology, but may be enhanced by it. For instance, an open enrolment to higher education provision can be further enhanced through building a digitally-connected network of peers, who can also develop content and assessment together.

This conceptual model with the name ‘OOFAT’ is represented in Figure 1. It comprises the three central processes of higher education provision at its corners and has the two qualities of flexibility and inclusiveness at its centre. Using this overarching model, each institutional case could be described and differentiated by how it implements the three central processes and by what role flexibility and the principle of inclusiveness play in execution and delivery.

With this comprehensive model of delivery of higher education products and services, a broad selection of providers could be captured and similarities and differences in their provision highlighted for comparison. This marks a difference to the approach taken by other researchers, such as Garrett (2016) for the Commonwealth of Learning, who distinguished his cases based on specific additions to a basic model of open distance learning – e.g. the emerging cases he analysed were additionally for-profit, had a focus on OER and MOOCs or focused on adaptive learning. The intention of our research was to capture a wide range of different types of providers in a standard classification scheme, which especially highlighted how technical flexibility and the principle of inclusion were being implemented.

3. Method

In order to gain a global picture of variances in OOFAT deployment, a survey was chosen as the primary method of initial data collection. The survey was developed using the conceptual model in Figure 1 to derive a set of descriptive elements shown in Table 1. The design of the survey was informed by literature analysis and previous surveys used by the Open University UK.

The survey was designed to elicit responses which would help to classify the different cases. These were closed responses and required the respondent to make a choice within a fixed framework of options (including a business model typology based on Taran et al. 2015). It was designed only in English, and several iterations were tested for clarity with the study’s global advisory group. To counterbalance the element of subjective judgement, the survey also asked the respondent for more detailed justification of the information provided. Figure 2 illustrates this approach: Question 37 asks for categorization on a Likert scale and Q38 invites justification for the judgement made.

In February 2017, the global online survey was launched to capture key information and data from higher education providers utilizing flexibility and inclusive processes in their provision models. Survey participation was promoted through multiple channels, including blog posts, social media and the postings in a newsletter. While the survey aimed for senior staff members to complete, this was not always possible. The ‘universe’ under investigation comprised any university, but due to the focus of ICDE membership and the links of the authors it was particularly focused on established providers of distance and online education, although these were often hybrid providers, mixing campus-based education with distance or blended provision.

Cases were selected from all types of higher education providers according to the following selection criteria:

• Geographic: A global balance with representation from around the world was sought
• Ownership: Cases from both private and public-sector providers and mixed models
• Organisational: Cases which describe collaborations between institutions, singular institutions and organizational sub-units.

While the survey generated a lot of interest, in a large number of cases respondents did not complete all the questions. Therefore, during the field phase, which ran from February until the end of July 2017, the authors also contacted specific institutions to encourage them to provide more complete responses.

4. Respondents

The data set collected over 150 responses from 36 countries. A key criterion for use of the data in this report was that each respondent described their OOFAT model by answering the required block of nine questions on their model of provision. Taking this as criteria for inclusion of HEIs in the main analysis, the 150 responses were reduced to 69 HEIs. This number was further reduced for some analyses, because of the need for responses to specific questions.

Although this sample cannot be assured to be representative, it provides sufficient scope across a broad spread of practices to extract explorative models of adoption. Table 2 shows the mode of studies by size of institution within the sample, where there is a tendency for mega-universities (with more than 100,000 enrolled students) to be primarily online or distance providers, with campus-based HEIs more common in mid-sized institutions.

Table 3 shows the spread between HEIs by funding source. In the sample, publicly funded HEIs are present in all three sectors by delivery modes, while privately funded HEIs are especially common as providers of primarily online programmes.

In terms of the types of technology that were in use, the survey responses shown in Table 4 highlighted some general trends. The three most frequently mentioned technologies are those which can be most directly aligned with the core processes of content, delivery and recognition, i.e. OER for content development, Learning Management Systems (LMS) for content delivery and online assessment for recognition of learning. It is, furthermore, notable that all provider types mention the use of social media and mobile learning as part of their services – this suggests they are using new technologies to improve their interaction with and between learners (see below).

5. OOFAT Models

The survey presented Likert scales (1–5) for the nine dimensions included in the OOFAT model (e.g. see Question 37 in Figure 2 above) and asked respondents to score their institution’s provision according to these. The closer the score is to five, the more flexible or open the dimension is. Diagrammatic representations were created from these responses.

For example, the survey results for the Open University of Korea (with approx. 140,000 students) provide the following model in Figure 3. This shows an institution, which states that content delivery is open (i.e. not only available to those enrolled at the institution, but delivery is not flexible, i.e. it is subject to specific regulations on time, place and pace of the programme of study). According to the respondent, a certain level of organisational flexibility and inclusiveness is offered for all dimensions of its higher education provision. This is consistent with the institution being an open university. In contrast, the respondent scores for Universitas Terbuka in Indonesia (with approx. 40,000 students) highlighted only flexibility in content and support delivery to enrolled students.¹

In general, indeed, the two dimensions where high values in the OOFAT model were found, were in flexible content and support delivery. The ones with the lowest levels were in the area of recognition, with low overall levels of flexibility and openness in terms of recognition.

Looking at individual dimensions in more detail:

• For content delivery nearly 60% of providers characterised organisational access to their course materials as very flexible to highly flexible, meaning there are few constraints to access in terms of time and place for students. The share is similar for access to course support.
• In contrast, assessment and recognition tend to be neither technically flexible (e.g. anytime and anywhere) nor open in terms of who determines the conditions for assessment and recognition. This is not surprising, since higher education tends to be highly regulated for assessment, often as part of external (e.g. state-led) quality assurance procedures. Examples of leaders in making assessment more flexible are Amity Online University from India, the Open University of Tanzania, which is implementing an examination on demand system, and Athabasca University from Canada, which focuses on challenge exams. However, comments to the survey indicate the many HEIs are working on this area and it is an emerging practice.
• The question on content production focused on who is involved in the process – from purely in-house design and implementation, to external collaboration, to some learner-generated ‘personalised’ content (which is an argument often used in connection with OER). The survey shows that around one third of HEIs are generating content in-house, while a larger share collaborates on content design and production. Leading examples are the OERu from New Zealand, oncampus from Germany and the Open University of Nigeria (NOUN), which all focus on OER to provide such open processes of content development. It is noticeable that many of the community colleges from the USA that took part in this study, are moving towards more externally generated materials and combining these with the opportunities for adaptation in-house. Typical for this development was the following comment: “We are in early stages of a shift from centralized publisher produced content to decentralized OER content. At this time, OER is a combination of in-house and external production and sharing. OER is used by 12% of all students. This has doubled in the past year. It is expected to double again this coming year.”

Our data collection method makes it possible to represent and compare organisational approaches visually. The visual representations can be used to reveal distinctive aggregate patterns. The specific aspects of an individual HEI’s model may vary, but their common responses suggest that they have a common strategic direction. This clustering was conducted manually by two persons independently to find patterns which suggest a coherent grouping. Analysis of the responses revealed six different categories of technology usage, which are named to emphasise the dimensions that are strong according to the OOFAT model:

• OOFAT at the centre
• OOFAT for organisational flexibility
• OOFAT for a specific purpose
• Content-focused OOFAT model
• Access-focused OOFAT model
• OOFAT for multiple projects

6. Conclusion and Discussion

Higher education institutions should be viewed as a particularly complex type of organisation, so it is highly likely that reactions to change will be iterative and diverse. This study has elicited responses to a standardised model for describing the take up of digital technologies from 69 universities across all four continents and in doing so was able to provide some insights into this practice.

Based on the explorative results, this study suggests that the majority of HEIs across the world are currently in the process of experimenting with digitalisation and applying new technologies to certain parts of their operation. The analysis reveals that there is no ‘one size fits all’ approach to the implementation of technology for flexibility and openness.

In terms of technology adoption, a pattern of cautious implementation emerges across the board, with a range of educational technology typically being deployed (though rarely all of them). There is a notable persistence of what might be deemed older technology. For example, Learning Management Systems (LMS) are pervasive, and Wikis are still prevalent, especially in campus-based providers. Online providers are by their nature deploying many of the technologies in their core model. The more traditional distance education providers are likely to use technology to supplement their existing model rather than in pursuit of new innovations. Campus-based institutions tend to implement technologies for a specific need, such as trialing MOOCs in a specific discipline. This insight is highly relevant as a caution to interpreting studies, which state how many years until the implementation of a specific technology can be expected. For instance, when in 2017 the New Media Consortium’s Horizon Report predicted that adaptive learning would take less than a year to be widely adopted (Adams Becker et al. 2017) – it should be noted that such statements neglect both context and strategies of individual universities and colleges.

The ‘disruption’ model of technological change in education, which promotes one universal revolution in application does not seem to be borne out, but rather a mixed economy with diverse approaches to OOFAT is observed. Technology adoption is highly dependent on context, institutional structure and is nuanced to meet needs of different learners and aims. It is perhaps fairer not to argue that universities are reluctant adopters of new technology, as some have suggested, but rather that it must be deployed within the context of pedagogic, business and support models to meet specific needs.

Some HEIs may indeed want to achieve the ‘OOFAT at the centre’ model, where digitalisation is being harnessed to give a high level of organisational flexibility and a high degree of procedural openness. In this case, any learner can participate at any time, and part of this learner experience is the development of content for others, supporting others in their learning and contributing to endorsement of others through peer assessment. However, this need not be the goal of all HEIs. Other HEIs might decide that their strategic objective is less radical, and they will focus on making participation more accessible, without new initiatives around recognition.

As well as providing an analysis of the current global context, this research also provides a means of approaching future directions for HEIs as they consider their strategy and operations. HEIs can use the typologies developed in this study either to determine their current position or to decide which type of model they aspire to having. By examining the practice of other institutions with models they aspire to, they can adopt appropriate strategies and engage in peer learning with these respective universities and colleges. The value of this model is in providing a framework that can be used in an HEI as the basis for a discussion around strategy. The discussions the model generates are a key element of this process. It is unlikely for example that all staff will agree on scores when completing the questions in the OOFAT survey, and this can facilitate discussion around different perceptions. Similarly, when deciding where the HEI should seek to move to, the benefit will lie in the debate that use of the models fosters.

This work provides a basis for such comparisons and a common framework, but cannot be considered exhaustive. It should also be noted that throughout the survey, respondents made a self-assessment of their institution, which may not be objective and could be contested by another member of that institution. Furthermore, while in most cases the person filling out the survey was an institutional leader of the HEI s/he was entering responses for, this was not always the case. Therefore, the results should be interpreted as showing the breadth of strategies and practices across the globe and not taken as fully representative of parts of the world or specific types of institution.