Preparing for the Future – Decision making on technological innovation at universities

European IFA Academic Seminar. September 16-19, 2013. Winterthur/Zurich, Switzerland Preparing for the Future – Decision making on technological innovation at universities. 1

Preparing for the Future – Decision making on technological innovation at universities

Guerra, Vania - [email protected]

Lübcke, Maren – [email protected]

aCenter for Innovative Didactic, School of Management and Law, Zurich University of Applied Sciences. Switzerland

Abstract: Higher education institutes face unprecedented challenges and change needs. Drivers of the change are: democratization of knowledge and access, contestability of markets and funding, digital technologies, global mobility and integration with industry. Focusing on digital technologies, the purpose of this paper is to describe the current situation of higher education institutions regarding the integration of emergent technologies in the teaching practice and describe the exploration of already existing and self-organized online communities as foresight research methodology. After describing the complexity of the transformation process of higher education institutions, and the problematic of innovative teachers and institutional teachers’ support centers. Foresight methodologies are used as base to structure a project, which aim to generate a vision of the future of institutional teacher’s support centers, in the knowledge society. In the last section, the structure and general design of the project is described in the frame of foresight models. Key words: higher education teaching, challenges of higher education, foresight in higher education, teaching support centers.

Introduction Universities and Higher education institutions have played an essential role creating new knowledge, transferring it to future professionals and fostering innovation. Historically universities have been the place where philosophy, science and professional education met each other. This role has not dramatically changed, but the demands from society, economy and science did. In most Western countries, student numbers started to increase rapidly in the end of the 1960s and has not stop this tendency until todays. This phenomenon is the result of societal and economical changes, and has unparalleled implication in the organization of modern services and activities offered by higher education. Researchers (Trow 2000)(Trow 1973) have identified three phases in the evolution of higher education: elite system (participation less than 15 % of the age group), mass higher education (participation between 15 - 50%) and universal higher education (participation of more than 50%). The OECD1 (OECD 2009) report that since 1998, tertiary attainment levels among young adults have increased significantly, to 34% among 25-34 year-olds, on average across OECD countries2 . The increase on demand for higher education was primarily driven by changes in economy and by growth in occupations for which secondary school education was no longer enough.

1 Organisation for Economic Co-operation and Development 2 List of OECD countries : Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israël, Italy, Japan, Korea, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States


There was more demand for highly educated people in order to fill the need of the economy. One of the major changes in higher education therefore is a new view on what is its main purpose. The aspirations of the students as well as societal expectations put the professionalization role of higher education at the focus. Another implication of this massification phenomenon relates to funding. Covering the expenses of higher education at mass level is a serious burden on a public budget. Although In most countries public funding in the period of massification increased, it did not keep up with the escalation of student numbers. As a result, funding per student dropped and staff per student ratio declined (Beerkens-Soo and Vossensteyn 2010). Van der Baaren (Van der Baaren 2013) remark that higher education today is too expensive, being one of the largest cost items for most of national budgets. He also notes that education is the only major sector in society that shows no increase in productivity in the past 50 years. On the contrary, cost has risen while the quality of output has remained the same (at best). The author conclude that Higher education has low quality, regarding value for money that students receive, and has low relevance in terms of how prepared are new professionals to face the labor market demands. The importance of supplying labor market as one of the main roles of higher education is the main driver of big European reforms, as is the case of the Bologna process3, the EU reform with major impact in European higher education system. This reform has the focus on incrementing the mobility of researchers, students and professionals around Europe. This mobility would increase the higher education resources accessibility as well as professionals availability, by join efforts among different European institutions. To that end was designed the standardization of the career path from graduate until PhD. This reform was created with the claimed goal of providing responses to issues such the values and roles of higher education and research in modern, globalized, and increasingly complex societies with the most demanding qualification needs. Analyzing the technological trends and looking at the tendency of increasing ubiquity of technology, Bologna process introduce one of the most relevant reforms regarding professional education, it was the change of the focus of curriculum design from content-based to competences-based curriculum. This decision was driven by the increment of more technological skills demanded by the labor market. As (Hüsing et al. 2013) reported, the ICT workforce in Europe has been growing over the past decades and there has been a steady increase in the number of ICT practitioners in the workforce. There is not indication that this trend will change; even throughout the crisis the annual growth of ICT has remained very robust. This strong tendency generated the curriculum reform proposed by the bologna process, which has been, with no doubts, the cornerstone of the professional education transformation.

Demand for Higher education transformation The transition from an elite higher education (that was designed only for a few) to a mass higher education (accessible to a substantial part of the age group), it has an effect on almost all aspects of higher education institutions: on financing, governance and administration, on recruitment and selection of students, on curriculum and forms of instruction, and on academic careers (Beerkens-Soo and Vossensteyn 2010). The new EU Framework Program for Research and Innovation (horizon 2020) echoes another demand of desired transformation of higher education. While Europe seems to be still leading in basic research, this new EU framework program focuses on innovation, “by

3 http://ec.europa.eu/education/higher-education/bologna_en.htm


helping to bridge the gap between research and the market”4. This emphasis on innovation as product developer driver, it is another evidence of the stronger market orientation higher education is facing nowadays. Public higher educational institutions have to learn to compete with R+D departments from private institutions or company departments. As described by Ernst & Young (Bokor 2012), Universities are “a thousand years old industry on the cusp of profound change”. Higher education in general, are nowadays facing tremendous challenges, fostering a historical demand for transformation. Most of these challenges emerge from a heterogeneous demand of different sectors belonging to a society, which appeals to constant transformation and innovation. Different sectors are looking for solutions in higher education institutions, putting sometimes into question the position that they should take in the current and future economic panorama. As still a core societal organization, when generating strategies they have to find the adequate balance between the different interest groups and their representatives, namely:

• Science/research/innovation: higher education institutions are still seen as a source for the generation of new scientific knowledge and independent research.

• Administration/business: the administration head of the institutions have to react to a more competing environment and ensure their success. The definition of success is a problem of its own. Traditionally, there is a big difference between universities and universities for applied science. While the first is looking on measures out of the scientific field (publications, award, grants), the letter one is looking for number of students. But this difference is vanishing nowadays, since the high research quality is usually perceived as a sort of argument to get more students on board.

• Students/professionals: who are approaching higher education to build their personal future. The demands of students might be their longing for knowledge, but more often it is the demand for employability endurance.

• Economy/market: the economy asks for employees and innovations to keep up with competitors. How close this could be linked to the strategy of higher education depends on its Goals and the local or global market.

• Society/Citizens: they ask for responsible citizens and political subjects. Due to the fact, that higher education is still a public task, this debate is not to underestimate.

Higher education challenges are not longer belonging to the academic hegemony. Important actors of the economic spheres are also concerned with the future of this important institution. For instance, Ernst & Young5 have detected three broad lines of evolution for universities (Bokor 2012)

• Streamlined Status Quo — Some established universities will continue to operate as broad-based teaching and research institutions, but will progressively transform the way they deliver their services and administer their organizations — with major implications for the way they engage with students,government, industry stakeholders, TAFEs, secondary schools, and the community.

• Niche Dominators — Some established universities and new entrants will fundamentally reshape and refine the range of services and markets they operate in, targeting particular ‘customer’ segments with tailored education, research and related services — with a concurrent shift in the business model, organization and operations.

4 http://www.nmc.org/horizon-project 5 selfdefined as a global leader in assurance, tax, transactions and advisory services.


• Transformers — Private providers and new entrants will carve out new positions in the ‘traditional’ sector and also create new market spaces that merge parts of the higher education sector with other sectors, such as media, technology, innovation, venture capital and the like. This will create new markets, new segments and new sources of economic value.

Each of the Ernst & Young evolution lines above presented implies different organizational strategies. As the authors remark, although this scene challenges the higher education role, it might also create opportunities for participating on new markets. Economic values and interests evidently drive this vision. To wrap up, higher education institutions, pulled by strong external and internal forces, have to make strategic decisions so as to defend or redefine their position in the societal and economical playground. For that reason, foresight research seems a suitable approach to face the higher education strategy development challenges.

The knowledge revolution Stephen Byers (cited by (Rikowski 2005), who at the time was the UK Trade and Industry Secretary described this revolution to the Confederation of British Industry (CBI) in 1999, saying:

“The first industrial revolution was based on investment in capital and machinery. The revolution we are going through now requires investment in human capital - skills, learning and education.” (Byers, 1999)

It is not a secret the massive growth of open education offers, on-line resource and open knowledge. Knowledge and information are free available and reachable out there just handling a simple internet connection, accessible for everyone who can afford a smartphone. Consequently, higher education institutions are no longer the one central source of knowledge generation. Today and especially in the future, there will be even more competitors challenging this role. The knowledge revolution is the result of an incremental feedback loop between technological developments and scientific advancement (and vice-versa). The development of sophisticated Information and Communication Technologies (ICT), allowed general public and non-scientist to collect, share and create their own knowledge (via online communities exchange, social networks and lately the use of cloud computing for sharing and collaborating). Scientists, to expand their borders and generate scientific knowledge, also use the same tools used by non-scientific general public. Beside of ICT, other technologies are also emerging product of this rapid knowledge access at all levels of society. The more technology evolve, more tools are given for scientific exploration6. New technologies are allowing all scientific fields a deeper and better understanding of natural and social phenomena. The better scientists understand their field; more refined are their technical demands so as to answer more complex scientific questions. This interplay between Science and Technology (S&T) is enabling the unprecedented creation of new materials and processes, which allows the design and implementation of more and more sophisticated technological tools at the service of science and society. The rapid dissemination of existent knowledge and know-how, coupled with the possibility of ideas exchange virtually with everyone everywhere, speed up the generation of new knowledge and know-how.

6 For instance the increasing phenomena of DIY communities: http://hackteria.org


This expansive wave of knowledge generation is expanding scientific field limits to such extent that intersect the expanded limits of other fields. This phenomenon is creating new interdisciplinary territories of research and developments, arising strong demands for inter- and multidisciplinary work. Researchers have no longer the image of the isolated scientist in a lab. The scientific fields are becoming so complex and vast, that teamwork and networks are demanding. Hence, even in the academic area new skills are required in junior researchers so as to be able of better handling the strong economy demands and take the most of the knowledge and technology revolution. The S&T marriage is creating also new markets generating new economical niches. Many of the technological developments created to resolve specific industry demands find their way to the market. As it is the case of the 3D printer, which appears in 1983 to cover a demand for cheap prototyping before steeping to a more expensive production phase7, and it is nowadays entering in the home-printer sector, being at the service of general public. Thus, also new professional profiles are required, either by the new academic research fields or by the new economical niches. The above described expanding S&T dynamics has currently an incremental momentum very difficult to be followed by old and static organizations like big higher education institutions. This is because the entire administrative structure of these extremely traditional institutions has been historically rooted in the division of scientific fields and disciplines. Therefore, the internal structure of higher education institutions does not prepare them for covering the increasing demand of interdisciplinary professionals (either academics or in the labor market). The strong fields and discipline structures, which currently function as the skeleton of their research activity and their career offers, it is no longer the unique framework to define their internal structures. But it reminds unanswered what are those new frameworks to be used.

Educational technologies Universities have long time struggling with the use of digital technologies for educational purposes (Stahl, Koschmann, and Suthers 2006). However, one of the biggest problems faced is that technological changes are going faster than the reaction capacity of the educational institutions. The trends of technological development with potential educational uses are changing faster than the capacity of the institutions of making decisions regarding costs investments and technological infrastructure. As Trow (2000) suggest, the unprecedented speed of technological development in this area is an independent force posing a severe challenge to policy-makers. Unfortunately, defining what technology higher education will adopt, it has become more a marketing issue than a question of enhancing learning. Introduction of emerging technologies in higher education has broader implication than just selecting the kind of technology to be used. Institutions have to make decision on their role in the societal scene and define educational models accordingly. Therefore, even when technologies are there and are constantly changing, until institutions do not make integral decisions on their role and educational model, it will be very difficult to speed up the decision making process. One clear example is this complex decision making process is the arousing trends of MOOCs 8. MIT 9 as the one trend, lead universities to set the questions weather they should hop on the

7 http://www.3dprinterprices.net/history-of-3d-printing/ 8 Massive Open Online Courses 9 Massachusetts Institute of Technology


train and produce some offers themselves. This would mean to open up distance learning units. This might be to approach new target groups. The idea seems to be simple: the content as well as the didactic is already developed, thus the university have to adapt it towards this new technologies. Nonetheless, what that exactly means for the institution is to re-think their educational model, to make decisions on their possibilities of offering distance learning beside of their regular practice (which differs than the blended-learning model). Not all the organization has the enormous structure that MIT has regarding availability of technology and human resources to support the production and distribution of MOOCs. Educational organizations have to make the decisions on where and how they invest their resources (economic, infrastructural and human resources) before defining if they will jump into the MOOCs wave and if, how they will do it. It is evident that massification of education challenges the education system in terms of accommodating alternative study needs and providing more flexible teaching modes, such as online learning activities, individualization of education, self-study activities and so forth. It is also clear that MOOCs seems to be a good alternative to face this challenge, but as in many other potential solutions, the implementation of MOOCs is going beyond the acquisition of technical infrastructure to produce and/or host massive online courses, it also has strong implications on the education model adopted by the institution, which has of course implications on the curriculum development and teaching.

Teaching in the knowledge revolution Digital technologies available to education have already expanded dramatically in recent rears, but it takes more than technology infrastructure to transform a profession. Teaching staff of higher education organizations is hardly trying to understand their new working context. On the one hand, they have to fit their practice with institutional requirements like implementing competence-based curriculum and using pre-defined institutional learning environments and technologies. On the another hand, they are trying to understand what means teaching and learning in the knowledge society, where students has free access to the information what they were meant to deliver. Moreover, their knowledge can be put into question by any student on the base of finding a different perspective in an expert online community. Has part of higher education teaching staff, the question should not be “how should I use the institutional technology?” or “what kind of technology should I look for?”, but “what is my role in the learning process?” or better say “what means teaching in the knowledge revolution?”. (Laurillard 2012) redefines teaching in Higher Education as a science. Technology has expanded the limits of pedagogy, offering opportunities for implementing alternative learning approaches based mostly in constructivist learning theories. These theories are indeed far to be new. Vygotsky already introduced socio-cultural constructivism in the 1930s in western world, but it was only until end of 1970s when become popular with the apparition of its book in 197810. However, the possibilities of put it into practice have opened new research questions related with learning processes in terms of both individual and collective knowledge construction. Historically, higher education teaching staff were used to deliver content and evaluate how much of this content was caught by students. Therefore, while learning contexts are increasingly rich in electronic and mobile technologies, the first approach teachers attempt is

10 Vygotsky (1978), Mind in Society: Development of Higher Psychological Processes


oriented to find different ways of delivering content and evaluate its reception, in a more efficient, effective or even just more enjoyable way. Has (Laurillard 2012) remarks:

“Education could easily be sidetracked into the inappropriate uses of technology if we are not clear what we want from it.” (p. 2)

The author describes very well the current problem of teaching education. They simply do not know what they should expect from technology. Hence, they have to develop a vision of what they want from it. Furthermore, if we consider the rapid evolution of technologies, they should be able to make strategic decisions on where pedagogical models they will go; and which kind of technologies will be the most suitable for it. This capability could be called ‘foresight thinking’. While educational researchers will be understanding better what means teaching in the knowledge society, teachers could use those findings and their foresight thinking to imagine new technologies and pedagogical models. Scenario building seems also to have a high potential to allow teaching staff to make better choices. But teachers are not unattached to the organization, and they must be in line with the strategic plan of it, at the same time, organizations are not able to go forward without considering the teachers ideas. It is demanding a good communication between all the involved sectors and stakeholders, in order to better master the future of higher education organizations (Morrison 1997). Therefore participatory methods are demanding in the case of higher education institutions, including not only experts but also teaching staff and technicians of the organization. The ultimate goal of the foresight process, beside of supporting the strategy development process, it would be rising a foresight organizational culture. As mentioned in the open education 2030 report (OECD 2013): “Higher education may seem to be undergoing disruptive change, but is not yet undergoing radical innovation, at least not at scale”. Foresight methods or alike have been used for recognizing trends and suggest strategies based on those trends. The analysis of emergent trends or scenario building seems to do not have been exploited sufficiently for supporting organizational strategic development in higher education. The Open University of UK, has supported and driven many studies that look at “open education” as a way of overcome the weaknesses of higher education (Hall & Keynes, 2010; Pantò & Comas-Quinn, 2013; Sharples et al., 2012). Van der Baaren (2013) also point out that open education is to be considered at the moment of strategy development of modern higher education organizations. He suggests an inclusion of open education practices as part of a strategic transformation and not the complete transformation of higher education institutions in open education ones. Nevertheless, open education is not the panacea. It has already their own challenges, as for example how to incorporate always-emergent ICTs in their daily practice or how to deliver certifications in the online world (problem related with online assessment). Even when technology is available, as for example social networks analysis for learning analytics, or diversity of social media applications for social learning, there are still open questions about how to use it in an efficient and effective way. There is even the question of “what means efficient and effective when talking about teaching and learning processes in the knowledge society?”

A framework for foresight research Organizational foresight methodologies seek to expand the perception of the strategic options ranges available to an organization. Due to the its capacity of dealing with complex strategic developments, there are diverse groups that have already implemented strategic foresight in


higher education (Andreescu. j et al 2013; UNESCO, n.d.; Wouter, 2013). Voros (CIted by Conway and Futures 2008) indicates that organization foresight requires thinking to move from implicit to explicit, from individual to collective, and from unconscious to conscious, before an organization can begin to think systematically about its future, and use subsequent insights in its strategy development. Strategy development process, as shown in Figure 1, the as three independent steps: strategic thinking, strategic decision-making, and strategic implementation.

Figure 1 Three levels of strategy development process (Conway and Futures 2008)

Foresight methodologies are useful mainly in the first level, seeking to expand the perception of the strategic options range available to the organization as shown in Figure 2

Figure 2 Generic Foresight Model

Since foresight methodologies support the analysis, interpretation and prospection of the data collected in the input step, Voros categorize them according to these four initial levels of the foresight model. The output of the foresight process, according to this generic model, would be the options to be considered in the strategic decision making stage. In this model, the last stage groups strategic decision-making and strategic planning. There is no single set of methods in all foresight future activities. The methods used need to reflect the resources available and the objectives of the exercise. The choice of methods is critical, though it often appears to be based upon what is fashionable or which practitioners have experience in. By far the most popular means of assessing possible future events seems to be literature search and expert opinions, closely followed by scenario studies (Nicolini and Bagni 2012).


Thus the complexity of the current situation of higher education institutions make it clear that foresight could be a suitable approach in the strategic planning of the university

Foresight research in Higher Education teaching It is a fact that not all HE teaching staff is busy with improving their teaching practices, but those who are interested on handling emerging technologies for education are mostly occupied with finding the answers to a bunch of questions like What exactly means a competence in practical terms?, what means to have a competence as learning goal?, how to include the development of XXI century competences in your teaching practice?, What really means collaborative learning environments?, which pedagogical models or educational methods are the most suitable for that?, how to develop specific competences and what is the relation with the content matter?, and so fort. Some of them depart from that questions, while others seek for the role of technology in their personal practice. Regardless where they are coming from, they all are wondering which technology to use and how. These inquiries are leading to put into question their own role as teachers. Should they redefine what teaching means for them? Laurillard (2012) describes this situation as follow:

“It will take a while to work out how best to use the extraordinary collection of technologies available but, with a new perspective on the profession of teaching, education could be discovering a fundamentally different way of developing and sharing human knowledge and skills.”

But ‘Who is there to help higher education teaching staff to figure out their new role in the institutionalized learning process of knowledge society?’. Most of the European and worldwide recognized institution have included in their organizational structure centers for supporting teaching or alike. The knowledge transmission model, oriented to give workshops and courses in a prescriptive way, has historically driven these centers. However, as integral part of institutions, they are currently also immerse in transformative processes. Should these centers still have a prescriptive role in a non-prescriptive teaching context? Are they really covering the current demands of teaching staff or are their services still defined by obsolete ones? Are their services out-of-date and need to be completely redefined or it is only needed to add new ones? They are trapped between teachers’ demands and organizational structures. Their role into the institutional organization and Institutional resources limit them. As result of the transformation period all the organization is suffering, most of these centers are suffering or have recently suffered structural changes (internal restructuring, fusion of different dependencies, redefinition of services and so on). If the profession of teaching would have a new perspective, then how should it be the support that this new teachers would need? Foresight research will be used to look for answers to this question. In the following sections will be described how foresight research has been considered to structuring this project.

Future of higher education teaching support centers -‐ the project For structuring this project, the first four levels of the described generic foresight model (Figure 2) will be implemented. These four levels are all concentrated in the strategic thinking stage (Figure 1), thus this project aim to describe possible “Options” to be used as bases in the decision-making and planning phases. The data collection during the input level will be driven by the following question: Which are the current services offered by higher education teaching support centers and how they are structured in order to deliver them?


The project will be divided in two phases: i) data collection and analysis and ii) interpretation and prospection. In order to have the conditions to intensively use participatory methods during the second phase, an online community of different stakeholders will be fostered during the first phase.

Phase I -‐ input/analysis

During the first phase, data will be collected from a variety of internationally recognized higher education institutions11. The participants in the input level will be mainly representatives of the teaching support centers or groups devoted to this task. Teaching staff related to this centers will be also contacted (when possible). Although there is not scientific evidence in the literature, from the practice it is well known that some of the teachers, who ask for institutional support for integrating emerging technologies in their practice, get usually away from institutional ways and go rapidly by their own becoming independent of the institutional solutions. For different reasons to be discovered, they usually find more effective solution in informal contexts, resources and tools. It is also known, that innovative professors do learn by themselves and find the way to reach whatever they need so as to accomplish their goals. Indeed, it is vox pop as more innovative teaching staff is, farther it goes from the formal institutional solution. It could be that generally the flexibility, pedagogical and/or technical capacities offered by the institutional support centers are not covering the demands required (neither technical nor pedagogic). These innovative teaching staff is the most difficult target group to reach, due to their weak connection with the institutional channels. However, a self-organized community of practice is usually gathering them. Sometimes they are addressed by the support centers, sometimes they are finding their own way, but there is also the tendency to get in contact with other professors or teaching staff, whom are also innovating and have had resolved technical or even pedagogical problems already by themselves. They frequently get in contact with each other by word of mouth. Therefore, it is of vital importance in this project, to use the formal channels to try to connect with those who have gone independent after a failing with the institutional support, with the aim of integrate them to the foresight discussions. Normally these innovative teaching staff has already an intrinsic foresight culture. Hence, they would be of most help in developing this culture in other institutional instances and colleagues. Surveys and questionnaires will allow us to collect general information about the organizational structure, missions and visions, extension of services offered, human and technical capacity, and other internal aspects of teaching support centers or groups. This information will help us to prepare a second round, where personal interviews or focus groups will be performed, aiming to gather more specific internal information regarding the current practical situation of these centers, successful experiences and services, problems encountered, covered and uncovered expectations, demands to the institution, internal organization and so forth. During this stage will be the opportunity to find links and connections with the previously mentioned hide community of innovative teaching staff, who have fell beyond the limits of the institutional support capacities. During this period online communities and social networks used by support centers staff will be also collected. It will be of big help in the next analytical step.

11 Massachusetts Institute of Technology (MIT) and other universities of Boston Area - USA, University Mediterranean - Montenegro, University of Barcelona - Spain, Technical University of Berlin (TU) – Germany, and from Switzerland the Swiss Federal Institute of technology (ETH) and the Zurich University for Applied Sciences - ZHAW).


After collecting enough information, foresight analytical methods will be implemented with the purpose of categorizing the data collected, going beyond trend spotting and looking for existing themes and patterns already evident in the studied field. Participatory methods will be implemented for the analytical step. Similar than the methodology adopted by Davidson & Goldberg (2010), a first draft of the trend analysis will be produced and posted on a online collaborative platform (to be chosen). All the collaborative platform will allow participants to make comments and also edit the document. That way, a collaborative document about trend analysis will be produced. It is to be decided if in this stage will be generated only one online community for all the participant universities or one per each institutions. Both approaches have pros and cons; the final decision will depend on the generated dynamics during the data collection step. The participatory methods will allow going outside the limits of trend analysis and exploring potential emerging issues. As pointed by Data (1989, cited by Conway & Futures, 2008), using emerging issues analysis allows for an exploration of issues before their impact is irreversible.

Phase II – Interpretation and prospection

After collecting answer for the question “what seems to be happening”, it will come the time of looking for “What is really happening?”, followed by “what might happen?”. With these answers in mind, the possible options to be considered will be delivered, so as to be available for the strategic decision making and planning phases. The interpretation methods seek to move beyond categorization of data to determine what system or structural interests are working. Inayatullah, (2004) present it as a research theory and method to explore beyond the surface of the problem and creating transformative spaces for the creation of alternative futures by deepening into different layers that allow to get better understanding of complex situations. CLA is a context-based approach, which enables to see context as multiple layers. These levels are already established, but they serve as guidance and can have some variations depending on the analyzed problem. The challenge is to move down to layers rethinking the implied future at each level. This approach will provide tools for generating long lasting solutions. Although, one of the potential problems this approach has, is the risk of falling into a personal translation of different layers of a determined context. A certain translation of social problems of a defined society from a personal perspective could be different from another personal perspective. To that end, the exploitation of online communities is a powerful tool for avoiding personal bias during the application of this method. For the prospection level, it is intended to generate a view of alternative futures for the support centers in general and for each particular involved institution. One of the most used methods for this is the scenario building. This is a collaborative rather than an individual activity (Oglivy, 2000 - cited by Conway & Futures, 2008). It requires knowledge, expertise and input from staff of the organization to generate the scenarios. At this point of the project, it is expected to have diversity of online communities engaged in this process. During this level of the project it is also important that the scenario building process it is accompanied with scenario planning and considers the existing planning processes present in the respective organizations. Although it is expected that the outcomes will serve as base for following stages as strategic decision making and planning at organizational level, these stages are considered out of the scope of this project. At the time of writing this paper the design of the instruments for implementing the Input step, are being developed.


Conclusions Considering the complex situation and demand for transformation that HE institutions are facing nowadays, as well as the strong influence of the technological, societal and economic changes, organizational foresight and foresight methodologies appear to be very a good solution to steer the strategy development process at organizational level. Higher Education institutes are a fruitful application area for foresight methods. Decisions are complex, the future vague and a lot of stakeholders contribute. But it is a long way to go..

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Preparing for the Future – Decision making on technological innovation at universities

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