1 Introduction

Since the end of the nineteenth century, there have been recurrent calls to reconsider the predominant model of higher education provision given its inadequacies to changing social and economic demands and expectations. Particularly during the pandemic, newspaper pieces, television broadcasts, and a great deal of social media chatter have been showing a growing agreement on the importance of changing the paradigm that is still globally predominant—and most likely will continue to be so when the appearance of radical transformation caused by the epidemic begins to fade. The idea that, if we had not inherited higher education as it is, our current views about education would drive us to construct a vastly different system is already a certainty (Drucker, 1998). Against this context, educational innovation in higher education develops as an investigation geared specifically at redesigning provision and delivery modes.

Many discussions about teaching and higher education assume that the reality of today’s classrooms is populated with highly innovative methods. However, it is difficult to find empirical evidence about how teaching is happening in university classrooms. Two examples show that the most widely used teaching method, lecturing, is hardly in line with the rhetoric of innovation that often populates the discourses about higher education. The first example comes from an examination of the main teaching strategies used in business administration programs in more than 200 European universities. In that domain, where the development of practical skills and competencies in management is so important, it is difficult to understand why the most widely used method is still lecturing, as opposed to problem-solving or the work on case studies (Leon, 2016)—while good lecturing can be inspiring and convincing, it is not appropriate for the development of skills that promote agency and self-regulation whereas a hands-on approach could be far more suitable. A second example comes from the analysis of the evolution of teaching strategies in economics programs in US colleges and universities over the last two decades (Asarta et al., 2021). Again, the expectations are disappointed by facts: the most widely used teaching strategy is lecturing. Furthermore, the examination of the evolution of teaching strategies over the past two decades shows that lecturing has remained the top method increasingly supported by computer-based presentations. The latter has increased at a pace that doubles the rate of increase of strategies that could be easily linked to more interactive or student-centered strategies such as cooperative learning or discussions among students.

Research insistently reminds us that, from the beginning of the nineteenth century, educational innovations have been constant, almost overwhelming at times, yet despite this, formal higher education continues to resemble itself globally because the underlying model is universal (Meyer et al., 1992, 1997). Some analysts have gone as far as to claim that, despite all, higher education has changed progressively in its internal structure, the configuration of procedures, and use of technology. Still, it does not appear that the universal model of higher education has undergone a major shift (Elmore, 2004). In a way, the paradox is that the more things have changed on the surface of higher education institutions, the stronger the classic universal model has become (Sarason, 1996).

2 Conceptualizing Future Skills

Intuitively, the concept of Future Skills refers to the skills that would best equip learners to address the life and work challenges that are likely to be faced by them in the near future, based on our current assumptions. Implicitly, the concept of Future Skills is an assertion of the mismatch between labor markets, projected or actual, and the current educational provision. Therefore, it fully adheres to the assumption that the global economy is undergoing fast transformation due to technical, demographic, environmental, and geopolitical factors (Ehlers, 2020). This transformation will unavoidably alter the character of labor, bringing new possibilities and risks. It is already doing so as the mismatch can already be seen in the unaddressed expectations of companies, particularly those operating in the digital economy or in areas where technology requires new profiles and skill sets.

The conversation about Future Skills has been particularly salient in postsecondary education, notably in technical and vocational training and higher education, given that their outputs are critical in a knowledge economy (Bowles et al., 2019; Ehlers, 2022). The link between labor market needs and Future Skills can easily be seen in a growing importance that this conversation has gained in international for a promoted by economic organizations such as the World Economic Forum (WEF) or the OECD (OECD, 2018). They have contributed enormously to raising awareness that technology and digitalization will strongly impact future employment. To deal with this, some governments have generated strategies, programs, and dedicated units to deal with Future Skills, such as in Canada, England, Japan, and South Korea. In addition to the technical knowledge and experience required for jobs in the digital economy, companies also seek professionals with certain transversal skills, such as creativity, critical thinking, leadership, and emotional intelligence. Those skills benefit companies from perspectives that are also essential for their businesses.

However, the numerous frameworks discussing Future Skills utilize hundreds of phrases to refer to such skills and competences, impeding the debate about education’s future (Kotsiou et al., 2022). One of the most widely quoted comes from the WEF. The WEF estimates that by 2025 some 85 million jobs may disappear due to automation resulting from technological advances, so its experts believe that the best skills for workers in 2025 will be intrinsically human and impossible to replicate in a machine (World Economic Forum, 2022). Thus, critical thinking and problem-solving top the list of skills employers believe will be crucial for professionals in 2025. Other skills on this list include active learning; creativity, originality, and initiative; analytical thinking; leadership and social influence; technology use and control; technology design and programming; resilience, stress tolerance, and flexibility; and reasoning and the ability to shape ideas and concepts. This list openly supports that the mismatch that fuels the discussion about of Future Skills goes beyond economic and labor considerations, as social transformations also require new personal and social skills. However, it remains to be seen whether these skills are sufficiently well developed in the current educational provision. Investment in three foundational social institutions—education, healthcare, and care—would re-start the engine of social mobility across economies, fill unmet demand for healthcare and childcare, increase the quality of education systems and ultimately drive growth (World Economic Forum, 2022).

The concept has also been criticized because the common lists of Future Skills often include some that have to do with personal abilities that, although trainable, are not acquired in a few months. Sometimes not even in years, such as critical thinking, creativity, leadership, the ability to shape ideas and concepts, or technology development and design. In fact, for many of them, in addition to a long learning process, it is also necessary to have a certain innate facility to develop them, as in the cases of leadership or creativity. Then, the question is how far the current learning arrangements provide conducive environments not only for flourishing these skills but, even more so, to avoid their cancellation or suppression after years of traditional educational provision that may kill creativity, for instance (Robinson, 2010). For decades, traditional education promoted a different set of skills, possibly more in line with the needs of industrial societies and economies, thus far from today’s needs.

In sum, the concept of Future Skills openly supports the claim that today’s educational provision does not address the skill development needs of current and future workers and citizens well, either because they are not aligned with labor market demands or social requirements. In this conversation, the future, although elusive and nebulous, serves as a significant orientation for predicting future positive changes, progress, and accomplishments, and thus drive educational reform and innovation (Hall et al., 2022).

3 Conceptualizing Educational Innovation

It is challenging to get a consensus on the concept of educational innovation. In general, innovation is defined as the act of creating and disseminating new tools, practices, organizational systems, or technologies (Foray & Raffo, 2012); therefore, innovation can be equated with the concept of development and contrasted with that of research along a continuum linking research and development. However, innovation differs from development in that the latter focuses on the generation of practice-oriented knowledge. In contrast, innovation results from applying this knowledge to a new product, service, method, or technology (Godin et al., 2021). In this context, the success of innovation would be measured by market adoption; in other words, total success would translate into universal generalization, which would paradoxically lead to the loss of the innovative character that this new product, service, technique, or technology would have had at its inception.

In complex organizations such as higher education institutions, several factors might lead to the acceptance of innovation or its avoidance. From an economic perspective, for an innovation to become ubiquitous, the cost–benefit equation must have a positive balance, i.e., the overall expenses and efforts necessary to embrace the innovation must be compensated by a bigger benefit (Rinkinen & Harmaakorpi, 2018). It is a matter of innovating to increase the company’s overall efficiency or steer the firm toward new goods or services. The higher education industry is reluctant to accept the abovementioned approach for several reasons. On the one hand, there is a denial of any notion of education that includes measuring effort and outcomes. For instance, in certain higher education systems, instructors’ work appears to be significantly impacted by reductive quantification techniques to make their work more accountable (Hardy, 2021). On the other hand, the higher education sector lacks the formalized elements of standardization that exist in other sectors, such as the health sector: much of the knowledge upon which instructors base their professional practice belongs to the domain of the tacit, and socially constructed practice, and is not subject to the same levels of protocolization that are evident, for instance, in an industrial production process or the prescription of medical treatments (Hardy, 2020; Murnane & Nelson, 1984). In the higher education sector, more so than in others, innovation is frequently equated with a change in any of the elements that comprise the essence of the traditional education model. Its success is not measured in terms of widespread adoption based on its greater effectiveness in promoting better learning or learning of a different nature, but rather in terms of the satisfaction of the actors who have made it possible—in particular, its promotors.

Throughout this chapter, however, educational innovation is defined as a dynamic change that adds value to the processes occurring in a higher education institution (both pedagogical and organizational) and that results in improved student learning outcomes or educational stakeholder satisfaction, or both (OECD, 2009). Furthermore, this definition includes the operational stipulation that only changes in procedures that result in demonstrable gains, particularly in learning, qualify as educational innovations. In so doing, the definition acknowledges the possibility of changes without demonstrable effects or even bad impacts, i.e., changes that do not result in genuine innovations.

4 The Imperative for Educational Innovation

The term “university” evokes a remarkably similar image throughout the world, which has its roots in economic rationality that, particularly with the expansion of demand around fifty years ago, seeks to solve the equation of how to provide the benefits of higher education to the greatest number of students at the lowest possible cost, with also clear political implications. However, as stated by Martin Trow over fifty years ago, the university as we know it looks to be only a common-sense answer to the dilemma of providing higher education to the masses (Berger & Luckmann, 1966). Accordingly, the conventional model of higher education provision prioritizes organizational formulae and teaching procedures that optimize the transmission of content or instruction.

The massive financial effort necessary for the massification of higher education might be quickly recouped by the benefits of having a workforce prepared to function as competent management in a manufacturing and industrial environment and, subsequently, in a services world (Tye, 2000). Indeed, the logic of higher education massification is based on the principles that all students should learn the same thing, at the same pace and in the same sequence, and that differences in results are due to the different innate abilities of students and their varying levels of effort; consequently, the best performers are selected to continue studying and will eventually be rewarded with higher-paying jobs, as befits a meritocratic regime. The latter summarizes the reasoning for the traditional paradigm of higher education, which is still in use today.

There is no shortage of literature regarding teaching and higher education, for instance, opposing the traditional learner to the 21st-century learner, saying we are becoming far more active and oriented towards problem-solving (Crisol-Moya et al., 2020; Wilson, 2018). However, innovation is more than a pedagogical imperative. Four drivers have been pushing the quest for more innovative teaching strategies in higher education even before the pandemic.

The first driver is the concept of skills development as a result of a growing trend toward ensuring that higher education programs respond to the needs of the labor market. While there have been many discussions about the exaggerated role that the skills seem to be playing now in the development of teaching strategies and the design of higher education programs, employers expect graduate profiles that not only master the corresponding subject but have well-developed skills in areas such as problem-solving, teamwork, communication or critical thinking (Succi & Canovi, 2020). The issue here is that the traditional approach to higher education is still discipline-led and study programs seem not to consider the need to foster the development of such transversal skills enough. This confidence on skills development assumes that the development of the new economy requires, more than graduates with content knowledge, competent, highly skilled knowledge workers. They will know how to apply content to problem-solving, work in teams in multilingual and multicultural contexts, have a critical sense, know how to communicate, and, above all, are creative to generate, through their work, new knowledge and spur innovations (Barrichello et al., 2020; Heckman & Kautz, 2014). In conclusion, a societal consensus has developed around the notion that it is not enough for higher education to teach content; it must also support the development of transversal and transferable abilities. As a result of the inadequacy of the old education model, it is vital to investigate, via innovation, alternative models that are more adapted to these modern needs, which all indications suggest will increase in the future (Biasi et al., 2021).

The second driver is essentially the demographic and social dimensions of the economic changes, which translate into the need to learn to coexist in increasingly socially, culturally, and linguistically varied and complicated circumstances. In this new environment, classrooms in higher education must explore modes of social interaction and shared learning in which diversity is recognized and appreciated (Schröder & Krüger, 2019) and where Future Skills are promoted. Again, this necessitates that both the organization of the provision of higher education and the processes underlying it provide environments where these learning-focused activities may occur, which is difficult within traditional pedagogical institutions. Moreover, the phenomenon of the diversification of student academic profiles that comes with the massification of higher education can be seen as a corollary. While new populations have been attracted to higher education with different age profiles, the point is that with the massification of higher education, the range of academic profiles among students has been widening. A higher education system that caters only to 10 or 15% of a student cohort can assume that only the cream, that is, the most academically oriented students will be on board. Although many will contest this assumption, the truth is that when higher education systems cater to the majority of a student cohort, as happens to be the case in OECD countries where the net access rates to higher education are already around 70%, inevitably, academic profiles among students will diversify, and with this the needs will also expand in terms of pedagogical strategies if university programs are designed to promote success and not simply to select the most academically endured students. There is some evidence showing that the more students are accepted into higher education, the more diverse their profiles become, and inevitably, as a result also of social changes, the less academically engaged they are, arguably because the provision of higher education is less meaningful for them, not because of their own limitations. An indication of these changes comes from a recent study that compared the average weekly study hours of US college students in 1960 and in 2010 (Babcock & Marks, 2011). In short, over two generations, the percentage of weekly study hours has been cut by half; in other words, today’s students span half the number of weekly hours their grandparents devoted to studying.

The third reason is the recognition of the mismatch between the techniques of communication and work within higher education classrooms and in the real world outside of these institutions. While the trend toward increased use of technology in the classroom, and beyond it, was already apparent well before the pandemic started, there has been a change in attitudes towards digitalization on the site of both teachers and students as a result of the massive experiment that the pandemic has represented when it comes to technology use for teaching and learning. Both teachers and students seem to be far more optimistic about the possibilities of virtual learning as well as hybridization or the potential of digital materials than they were before the pandemic, with the only exception of online proctoring, which is well accepted by students and not so much by teachers according to the latest data available (Johnson et al., 2021). The external demand on universities and instructors to incorporate technology and, incidentally, to adapt their teaching methods, was noticeable well before the pandemic. During the pandemic, technology-supported teaching, under the form of emergency remote education, was the only strategy to ensure pedagogical continuity during closures. Rather than innovating teaching, technology was used to reproduce traditional forms of lecturing under a remote modality. It remains to be seen how much of the cumulated experience on technology-supported higher education by teachers and students alike translates into durable and sustained changes in pedagogy or in the whole student experience. Empirical research has demonstrated that the costs of technology integration are not justified until considerable changes are made to the organization and processes of teaching and learning due to technological advancements (Comi et al., 2016). Thus, technology represents an innovation potential, but its presence alone does not necessarily ensure innovation.

The fourth driver is the need to improve the productivity of higher education. Although many voices would not accept the use of the term, the fact is that many higher education systems worldwide have been suffering from low graduation rates. In some European countries such as Spain or Italy, only 6 out of 10 new entrants in higher education will graduate at some point. In countries such as the Republic of Korea or the United States, where the majority of high school graduates get access to higher education, graduation rates are even lower, down to four out of every ten new entrants. While the causes of dropping out can be very diverse, ditching strategies and lack of significance of what students are meant to learn in higher education can be very powerful drivers for abandonment. This driver can be related to the international pressure that stems from the needs of increasingly globalized economies that rely heavily on science and technology as drivers of innovation and competitiveness, to focus the attention on the capacity of their higher education systems to produce the skills that must feed these economies and generate the virtuous circle of R&D on which knowledge economies are founded.

In conclusion, these four external factors (the demand for high-level skills, social and demographic changes, technological changes, and international competition) explain in large part why there is a growing social consensus globally on the need to promote innovation, which translates into an imperative (Marklund et al., 2009), also in higher education work (Bates, 2012). To these external elements must be added the internal dynamics of higher education institutions, which explains why this social consensus applauds and encourages teachers’ innovative initiatives.

5 Emerging Trends

While many essays provide hints about new pedagogies (Carbonell, 2015), that make a personal synthesis of innovation experiences (Bona, 2016), or that criticize the lack of disruptive innovations in education (Christensen et al., 2008), there is no inventory or international observatory of educational innovation in higher education that provides a clear picture of what the emerging global trends are. Governments and higher education institutions alike frequently struggle to find innovations inside their systems, evaluate their impacts (even for inventions they have funded), and contribute to their spread when there is evidence of their value. There are, however, signs (e.g., Delphi-based research) that education innovations in higher education can be organized along three important axes: innovations in instructional content and design, process innovations, and technology-supported innovations, all of them having important organizational implications. The three axes are analyzed below.

5.1 Innovations in Instructional Content and Design

The first axis is curricular. It should be the most important because it defines the expectations for the entire higher education experience. However, since the control of degrees continues to be centralized in many countries, particularly by quality assurance agencies, universities have fewer opportunities to innovate in this area. In nations where the curriculum is open and allows for substantial variability across higher education programs and institutions, such as in North America, or when it is specified in terms of standards to be attained after each cycle, such as in Southern Europe, curricular innovations are more likely to occur. However, governments and quality assurance organizations approach these developments with extreme caution.

In general, curricula determined by teaching loads of different disciplines or courses are being replaced by flexible formulae that emphasize transversal axes and the development of Future Skills. According to Pietarinen et al. (2017), the belief underlying these curricular changes is that eliminating topics is a requirement for learning centered on developing competencies. For many years, the concept of competencies was contrasted with that of content to emphasize that teaching could not solely focus on information transmission and its corollary, memorization; consequently, the need to develop innovative teaching methods centered on how to help students forge their competencies was emphasized. Due to the misunderstanding caused by a grasp of constructivist ideas, content was eventually vilified (Nordin & Sundberg, 2016). Nevertheless, the successful development of useful skills and competencies also needs the transfer of content, which is ultimately the substance on which competencies work.

Innovations in the curriculum that aim to foster the development of competencies extend beyond the standard university fields. For example, although we speak of mathematical, linguistic, and scientific competencies, there is a growing emphasis on so-called transversal competencies, such as the so-called 4 Cs in the Anglo-Saxon world (communication, critical thinking, collaboration, and creativity) (Partnership for 21st Century Skills, 2016) or 21st century competencies, or Future Skills. Their instruction has been highly suggested globally, especially in Europe, as was the case with the European 2020 Strategy’s priorities. Even though everyone seems to understand what they are intuitively, there is still no universal definition. However, even more than the emphasis on competencies linked to different disciplines, these others increase the difficulty of teaching and put the validity of curricular disciplinary models in jeopardy (Neubert et al., 2015).

This trend translates into a shift from designing study programs based on the content to be taught to a reference to the objectives that the students should achieve in terms of skills and competencies at the end of the courses. The percentage of European universities using an objective-centered approach in study programs has increased dramatically in just five years, which is already the preferred approach to program design in that region (Sursock, 2015). Setting objectives quite often equates with a competency-based approach to program design where the most important element is making explicit what the students should be able to do, often regarding a clearly defined assessment framework using rubrics. In other words, with this competency-based approach also comes a different understanding of how the student learning assessment should work. The critique of this approach comes more from an ideological perspective that is convinced that the role of higher education should not be linked to the development of skills and competencies but rather focus on the generation of critical minds in line with the classical liberal programs. Whether all competencies used to define study programs should be related to labor market needs or can go beyond that is a matter of open discussion worldwide.

The emphasis on skills development has given rise to two new phenomena: the corporate university and micro-credentials. Both are distinctive forms to respond to the requirement of high-level skills development in a more efficient way than traditional universities have been doing in the past. The corporate university can be defined as a model of higher education provision designed by corporations to suit their own needs and, by extension, to the needs of other corporations and firms. It is also a form of engagement of the private sector in higher education that in deregulated contexts can easily evolve as a more cost-efficient model than traditional public universities (Aronowitz & Giroux, 2000). Micro-credentials emerged along similar lines as an attempt to provide cost-effective credentials in response to labor market needs, particularly in technology-related fields, following intensive, short-duration training (Hunt et al., 2020). Micro-credentials are becoming increasingly popular also in traditional universities and are no longer the patrimony of corporate universities.

5.2 Process Innovations

The second axis of innovation is the diversity and richness of teaching and learning activities. This axis highlights two main innovation directions: Project-Based Learning (PBL) (English & Kitsantas, 2013) and the personalization of learning. Both PBL and personalization hold a lot of potential for the development of Future Skills—the former because it creates an appropriate real-like context and the latter because it is the only way by which the learner can receive formative assessment individually.

Internationally, PBL, also known as problem-based learning (English & Kitsantas, 2013), appears to be developing as the new methodological paradigm in higher education. However, the emphasis on developing skills and competencies necessitates a pedagogical framework in which student engagement is both the vehicle and the desired end; after all, competencies are created via action, or “learning by doing” as Dewey defined it in 1916. It is no surprise that the bet for objective-setting and competency development-oriented study programs translates into innovative teaching strategies that would certainly be much more useful in that respect than lecturing. If one of these new strategies seems to be gaining ground, that is for sure Problem-Based Learning, or Project-Based Learning, depending on the context (Gallagher & Savage, 2020). Inevitably for the development of practical skills and competencies such as problem-solving or critical thinking, there is no better way than confronting students with real problems or projects that, on the other hand, can also promote the interdisciplinary approaches that are also so valuable in the eyes of today’s companies in knowledge economies. A survey in the United States showed some years ago that the percentage of undergraduate programs requiring project-based learning is nowadays the majority; in approximately 1/4 of these programs all the students are required to embark on PBL (Hart Associates, 2016).

PBL may take a variety of forms, but its most important characteristics are quite straightforward (Barron & Darling-Hammond, 2008):

  • Students learn through confronting real-world obstacles or problems that they must answer through a project;

  • they have increased autonomy to manage and direct their learning activities;

  • teachers assist them throughout the process, supporting investigation and reflection; and eventually,

  • typically, students produce projects in groups or at least in pairs.

Thus, PBL provides a chance for cooperative learning and, consequently, the development of collaboration skills in a social setting that values difference and solidarity via different groups.

The second trend of process innovations is distinct but not necessarily contradictory: learning personalization or customization. The supporting belief is that improving the results of a class group requires, paradoxically, paying more attention to those students who, throughout the learning process, encounter more obstacles, either because of their starting conditions or simply because, at some point, they may need a specific reinforcement that only individualized attention, through tutoring, or in a small group, can resolve in time (Maguire et al., 2013).

Personalization has had several iterations (Prain et al., 2013). The more recent wave, heavily enhanced during the pandemic, was enabled by the increasing use of technology-supported platforms. The use of platforms has made it possible not only for each student to progress at her own pace and with resources that adapt to her interests or needs but also for teachers to monitor each student’s learning path individually. But, again, it must be emphasized that innovation along these lines is only conceivable if the contractual arrangements associated to the teaching load foresee freeing up the required time and resources.

5.3 Innovations in Technology

The third axis is technological, which is the axis most linked with education innovation in recent years, to the point that innovation and technology are sometimes mistaken for synonyms when they are not. As a result of technologically supported educational innovation, many experiments have been conducted to exploit the potential of digital devices, services, and applications, either to optimize known processes or to enable entirely new ones in teaching and educational administration and management. The growth of this association between technology and innovation is largely attributable to the contribution of the technology providers. All companies in the sector, from hardware makers to services and content providers, ensure that appropriate technologies are available in classrooms. They do so not simply to market their products but also to promote their image of what a university in the twenty-first century should be. In other instances, with some sort of messianism, they have assumed a prescriptive role without considering the actual demands and instructional priorities recognized in higher education classrooms, causing rejection (Williamson, 2017). They correctly assert that universities cannot stay ignorant of technological progress. But not everyone would agree that no one is in a better position than the industry to prescribe how higher education should utilize technology to achieve its goals.

Technology is nothing more than a window of opportunity. Unfortunately, innovative technology uses in the classroom do not always lead to developing innovative methodologies, as they can also facilitate consolidating the traditional pedagogical model. Consequently, it is not surprising that it can be challenging to separate the wheat from the chaff (Falck et al., 2015). On the other hand, certain innovations in content (such as the emphasis on transversal competencies) and, especially, in processes (both in PBL and in the personalization of learning) can benefit from the support provided by technology.

Nevertheless, combining all the experimental avenues that technology-supported educational innovation is pursuing is extremely challenging. In this regard, Cuban’s distinction between first- and second-order pedagogical changes established decades ago is extremely helpful, as it clarifies the true added value of technology in education (Cuban, 1988).

A first-order change happens when the inclusion of new technology enables improving and enhancing processes without substantially altering them. An example of first-order change is the replacement of traditional blackboards in classrooms with digital whiteboards, whose practical advantages and resultant increased efficiency are obvious. However, using digital whiteboards does not always result in a revolution in teaching but the technologization of well-established content-transmission processes. The same could be said about the increasing use of e-learning platforms such as Zoom or Teams or digital teaching resources: even open educational resources are not, in and of themselves, an educational innovation because their use does not necessarily imply a pedagogical change, regardless of the technical benefits, cost savings, or values that their use or sharing entails (Wiley et al., 2014a, b).

A second-order change happens when methods are significantly transformed, allowing for executing different tasks with distinct rewards. The clearest example is the so-called “flipped classroom,” in which students access information outside of class hours, freeing up classroom time for activities other than content transmission or entirely virtual school instruction (Lo & Hew, 2017). The flipped classroom concept, which was first created for teaching science, is fast expanding throughout the globe and has quickly extended from secondary to higher education.

The distinction between first and second-order relates to the magnitude of the changes: although first-order adjustments cannot significantly alter processes, second-order changes can fundamentally do so. First-order technological changes are not innovations, but second-order technological changes are. Indeed, pedagogical techniques appear to have produced much better outcomes, particularly when attempting to shift from a content-centered teaching model to one that emphasizes developing skills and competencies, provided the pedagogical design includes second-order adjustments. However, the necessary pedagogical transformation can only be implemented if the full potential of technology is harnessed. A growing body of empirical research identifies the conditions in which educational strategies supported by technology can yield much better outcomes than those that do not substantially use technology (Arias Ortiz & Cristia, 2014).

Including technology is only an opportunity for instructional innovation that may or may not be utilized. And secondly, improvements facilitated by technology only qualify as educational innovations when technology is employed for at least one of the following purposes (Pedró, 2016):

  1. 1.

    student’s active engagement;

  2. 2.

    cooperative education;

  3. 3.

    quick feedback to student activity; or

  4. 4.

    forging relationships with the world beyond the classroom.

Following the pandemic hybridization, that is the use of technology-based solutions to enhance the learning experience of students in the classroom or beyond lectures, has emerged as a promising avenue. The reference to hybridization comes from the fact that this approach would maximize the opportunities of face-to-face learning with the possibilities offered by synchronous and asynchronous teaching, particularly through dedicated e-learning platforms. Again, there is evidence that this trend existed well before the pandemic, and in the post-pandemic higher education landscape, student preferred teaching methods are now pointing to their expectation of increased use of more digital resources and materials, even in face-to-face instruction. Moreover, many students seem to be willing to follow some of their courses online even if they are in a residential campus. It all comes down to flexibility, a motto that business schools, in particular, have already adopted during the pandemic and plan to elaborate on increased flexible approaches to ensure that connectivity’s benefits translate into adaptability in different student contexts (Avent & Richardson, 2022). A good example of the possibilities of hybridization is the flipped classroom, whose success depends on several factors, including student engagement (O’Flaherty & Phillips, 2015; Sosa Díaz et al., 2021).

The pandemic made distance higher education compulsory for all students. Institutions and faculty consistently developed their capacities to transition from emergency responses, most of the time generated without any prior experience of distance education, to more mature approaches to distance higher education that involved more sophisticated use of e-learning platforms and applications and more refined instructional designs. It is not easy to see at this point whether distance education for undergraduate students is going to be on the rise in the coming years. However, there is certitude about the fact that when it comes to post-graduate education, particularly in the case of professionals, distance education will become the preferred approach by students because of the flexibility and increased quality of the student experience (Miller et al., 2021). Massive Open Online Courses or MOOCs generated a true hype and are entering now in a more mature status where well-established universities are the real players. If coupled with micro-credentials, MOOCs can become a new channel for the delivery of higher education particularly to graduated professionals seeking for quick and reliable ways of upscaling their skills (Goglio, 2019). With or without MOOCs, there are already several countries where students in distance undergraduate programs will soon become the majority, such as Brazil (Red Indices, 2021). Interestingly, in the United States, where the demand for distance higher education programs was declining well before the pandemic, it seems now to be on the rise according to the latest data (Cheslock & Jaquette, 2022).

Some of the pioneers in learning sciences research are also pioneers in investigating how technology might help transform instructional designs. These relationships are not coincidental. As scientists have come to a better understanding of the fundamental characteristics of learning, they have realized that the structure and resources of traditional classrooms often provide little support for effective learning. In contrast, when used to promote second-order changes, technology can enable teaching methods that are much better suited to how students learn.

Technology will continue to evolve and create new opportunities, some of which are only now being explored. Considering the potential of virtual reality, artificial intelligence, or the application of Big Data and learning analytics is sufficient to conclude that these windows of opportunity will expand dramatically in the future. However, this does not imply that new technology opportunities will always result in second-order modifications and, consequently, genuine innovations (Selwyn, 2015). UNESCO has frequently emphasized the need for improving digital teaching abilities as a means to dispel this common misconception (UNESCO, 2011).

6 Organizational Consequences

Innovations in content, processes, and technologies, when they affect an institution as a whole and not just a course, a program, or a single instructor, necessitate significant organizational changes. Unfortunately, some of the most common organizational adjustments target the old paradigm based on the premise of one instructor per course. Thus, for instance, the objective is to make the parameters for the configuration of class groups more flexible, both in terms of the number of students and their respective instructor assignments, as well as the duration of classes, which have been transformed into work sessions, paving the way for block-teaching. This can lead to times during the day when a relatively large group of students, equivalent to two or three traditional class groups, can be left under the supervision of a single instructor to engage in a low-demand activity, such as watching a video, in exchange for the opportunity to work in much smaller groups, each with its instructor.

Herein lies the significance of instructional leadership in higher education. In this context, leadership should be understood as a particular way of managing human resources at the department or school level that makes it possible to generate significant work priorities for educational improvement that the entire faculty also share; to direct the work of the department or school by these priorities, making the appropriate decisions; and, finally, to review the progress of the team by these priorities, and to evaluate their performance (Fowler & Walter, 2020). Therefore, there must be leadership in a department or school with a cohesive team, but this leadership should not always be mirrored in a single individual who would acquire all decision-making authority. International forums insistently refer to distributed or networked leadership, specifically to indicate that it should be exercised from different levels, personal and group, and to avoid placing all expectations and responsibilities on the leader at the center (Vuori, 2019).

At first look, this conceptual shift may appear to be the product of a transitory trend, such as the preference for the word leadership over coordination. Nevertheless, the reference to leadership suggests a paradigm shift: instead of supervising compliance with regulations external to the department or school and internally coordinating the actions derived from their mandatory compliance as traditionally deans and department chairs do, the reference to leadership includes an important nuance: the capacity to manage, motivate, and professionally develop human teams, while facilitating the economic and material conditions necessary for them to carry out their teaching responsibilities. Thus, there is a shift from a paradigm centered on the absence of regulations and standards in a context of full autonomy and freedom to teach by the individual, tenured professors, to one characterized by an emphasis on leading teams to execute a project in which research and innovation will inevitably play a central role.

Research has demonstrated that pedagogical leadership is essential for the formation of effective teaching teams and their ongoing motivation, as well as for fostering an institutional learning climate and environment that enables, guides, and acknowledges innovation efforts to enhance learning. In addition, research has revealed, not unexpectedly, a correlation between the quality of educational leadership and the quality of student learning (Leithwood & Jantzi, 2005; Smith, 2008).

7 Risks

At first look, the fact that there is currently a favorable social environment for educational innovation and multiple projects is encouraging. Nonetheless, the innovation imperative must confront some hazards. These dangers are associated with the system’s fairness, the evaluation of the effects of innovations, and teacher professional burnout.

In terms of equity, there is a paradox in which institutions or programs that work in highly complex contexts or serve a large number of diverse, vulnerable, or first-generation higher education students, which should receive more resources to enable significant innovations, are in a worse position to innovate unless the system considers them a true priority in this regard, which is not the case everywhere. It is not just a problem of acquiring additional resources to innovate but also having the best conditions to find the time to innovate (Raffo, 2014). High rates of faculty turnover in complex contexts and their lower average levels of experience and qualifications make it challenging to cultivate an environment conducive to innovation in institutions serving vulnerable or at-risk students. Moreover, it should come as no surprise that the frequency of innovative programs is lower in these contexts (Wilcox et al., 2017).

Second, the innovation imperative does not appear to have yet made the essential shift in the educational paradigm consistent with the requirement for systems to progress toward more social justice. The pedagogical discourse on innovation is not explicitly concerned with equity but focuses on fostering change that emphasizes achieving greater learning gains. Today, innovation is required most in equity, but the literature on that is scarce. For example, little effort is made to correlate innovations with reducing student dropouts or improving student achievement (Nichols, 2022) compared to the growing body of research that advocates for using learning analytics and artificial intelligence for that same purpose (Perrotta, 2021). When innovation is restricted to adopting technology-supported activities, the discussion regarding equitable implications focuses nearly solely on access and connectivity. In addition, inclusion often clashes with innovation since, to compete for middle-class students, some higher education institutions promote creative approaches above inclusive ones and sell them as their “institutional brand” (Baena et al., 2020). In developing contexts, where innovation in the provision of higher education is frequently equated with some forms of privatization (Lumadi, 2020; Verger et al., 2018), equity discussions rarely challenge the implications of alternative or innovative instructional strategies and instead focus on the neoliberal policy principles upon which the corresponding regulatory arrangements are based. In other words, the innovation rhetoric is more frequently associated with the need to disrupt the system than with the necessity of a fairer higher education provision from a social justice perspective.

The gap between innovation and equity discourses in higher education significantly influences the lack of desire and capacity for innovative initiatives to demonstrate their impact on enhancing learning outcomes. Innovators seem to be persuaded that national and (almost nonexistent) international assessments in higher education are incapable of quantifying the benefits of new models. This belief stems from a degree of ignorance regarding these assessments, which are erroneously charged with the original sin of evaluating only several indicators of public prestige, often associated with fundraising or research impact, and not the degree of development of the complex and transversal competencies, such as teamwork or problem solving, that the innovations seek to promote (Solomon & Lewin, 2016). Therefore, the argument arises that the innovations’ intended outcomes cannot be evaluated using existing methods.

Thus, the second paradox is that the innovation imperative is acknowledged, but any attempt to analyze its consequences is denied so as not to distort the process; in other words, it is as if it were a question of continually inventing, but without regard for its results (Carrier, 2017). Higher education sector seems to take innovation as if it were just another buzzword but does not appear to have acquired the significance that innovation has had for decades in both the private business sector and the provision of public services (Sandamas, 2005). Indeed, in this larger context, innovation appears to be “the design and implementation of new procedures, products, services, and methods of delivering (public services) that result in significant advances in efficiency, effectiveness, or end quality” (Mulgan & Albury, 2003, p. 23).

Contrarily, educational innovation could be defined as a dynamic change that adds value to the processes that take place in an educational institution (in both the pedagogical and organizational fields), and that translates into improvements in student learning outcomes or the satisfaction of educational stakeholders, or both (OECD, 2010). This definition includes the operational nuance that only changes in procedures that result in demonstrable gains, particularly in learning, qualify as educational innovations. This entails acknowledging the presence of first-order changes without demonstrable effects or even bad impacts, i.e., changes that do not result in genuine innovations. However, the moral commitment that higher education institutions and instructors have to provide a learning environment that optimizes opportunities and contributes to its enhancement by relying on current knowledge and creating new evidence is disregarded by deliberately engaging in blind innovation (Bryk et al., 2015). Therefore, genuine educational innovations must utilize empirical research to establish their efficacy (Coburn et al., 2016). On the other hand, an innovation that cannot demonstrate the improvements it produces is merely a change whose effects are unknown and, in the worst case, chaotic or haphazard management of resources that could put student learning at risk.

Finally, higher education leaders should pay attention to innovation fatigue among teachers (Hargreaves & Shirley, 2009). This multidimensional phenomenon stems either from an overwhelming external need for change (e.g., expressed in continual changes in program prescriptions or internal restrictions) or from the incapacity of innovation to win the uphill struggle for sustainability. Ultimately, this exhaustion reflects the mismatch between rising expectations for innovation and the actual organizational, professional, and resource capacity of higher education institutions and faculty (Coburn et al., 2016). The result of external pressure that is not accompanied by mechanisms of recognition and support for the efforts that instructors make can be a resistant attitude that is determined to maintain the fundamentals of the traditional higher education model because, quite simply, it is more comfortable than the uncertainty of a continuous and not necessarily recognized effort.

8 Concluding Remarks: Towards Systemic Innovation

This examination of emerging trends suggests that, except for technological developments, innovations in content and methodologies and their organizational implications cannot be considered new in the strictest sense. It is possible to find precedents for each of the elements that currently dominate the landscape of innovation in higher education in a substantial portion of the progressive education initiatives of the 19th and early twentieth centuries: peer learning (Girard, 1835), the active method (Marion, 1888), project-based learning (Kilpatrick, 1918), interest centers (Decroly, 1907), and individualized teaching (Dewey, 1916).

Two conclusions can be drawn from the fact that the same innovations have persisted for over a century. On the one hand, the traditional model of higher education is solid and has served its purpose so well thus far that it is difficult to replace it (Darling-Hammond, 2010). Nevertheless, on the other hand, innovations continue along the same lines as they did a century ago, likely because they are the ones that make the most sense. They persist because we don’t have the collective resources, financial, political, or cultural, to change them. Think about the model of how education is delivered through school: based on a nineteenth century factory model and unfit for purpose, often seriously questioned but remaining unchanged. The same can be said for higher education. However, whereas in the twentieth century, they did so due to the ideological conviction of their promoters, in the spirit of social reformism, they make more sense today because they are more in tune with the new demands of the economic and social context than the traditional higher education model.

Two different rationalities coincide in the imperative of educational innovation: the first seeks to respond to the needs derived from the new economy and an increasingly globalized and technology-dependent society; the second seeks to dignify the student as an actively and socially learning subject, placing her at the center of the learning process. Although contextual conditions change very rapidly, the broad global avenues of educational innovation appear consistent across the globe and, except for technology-related innovations, have been regarded as open and explored options for more than a century. If they are now receiving a more favorable social response and seem to be progressively adapted to previously unheard-of levels, it is because they meet the requirements of a new emergent social consensus on what and how to study in higher education.

To transform this impetus into a reforming force, we must consider how to disseminate not only the phenomenology of innovations (describing what they are like) but also their effects through empirical evaluations (demonstrating their added value); we must emphasize that innovations promote equity and improve educational opportunities for the most disadvantaged and vulnerable students in higher education; and, in short, we must be able to distinguish between the phenomenology of innovations and their effects.

Unfortunately, not every higher education institution is positioned to be innovative, and not every policy climate, both at the national and institutional levels, is favorable to educational innovation. In addition, research on educational innovations over the past few decades helps to identify the crucial variables that make an educational environment conducive to sustained innovation and that speak primarily to the capacity of educational institutions to absorb new ideas (Zahra & George, 2002). Institutional policies may help in promoting by, for example, incentivizing the establishment of educational leadership models that stimulate innovation (Knapp et al., 2014), or enhancing the stability of faculty, hence lowering their turnover.

In the health sector, a field with many parallels to education, remarks such as those just expressed would not be novel (Willingham, 2012): can anybody conceive of an advance in medical procedures or the prescribing of pharmaceuticals that would not be founded on comprehensive evaluation studies of their effects? More work is likely required in the higher education sector to bring the world of empirical evidence, with all its limitations, closer to classroom teaching practice so that the imperative of innovation does not seek change for its own sake but rather promotes change because it enhances students’ learning opportunities. If this were to be accomplished, the higher education sector would have more tools to foster systemic innovation as opposed to spawning idiosyncratic breakthroughs that are, in the end, little more than summer flowers.

On the few occasions this has been carried out rigorously, the findings gained have been encouraging. For instance, comprehensive research by the U.S. National Academy of Sciences revealed the effectiveness of active approaches in developing scientific, engineering, and mathematics learning abilities (Freeman et al., 2014). More recently, another experimental investigation has revealed irrefutable proof that project-based learning improves learning outcomes (Duke et al., 2021). Of course, it could be argued that this is not new, as evidence accumulated even through research reviews long ago indicated this (Thomas, 2000). Unfortunately, evidence appears to be available only in restricted, specialized academic circuits where practitioners are rarely present, and no great effort is made to reach them—not to mention the lack of incentives for faculty to spend much effort on improving their teaching.

The most important question when talking about innovations in higher education is whether they work or not. Unfortunately, the pedagogical discourse about educational innovation is not very prone to the empirical assessment of results. However, the existing evidence, while scarce, points to some interesting facts. The attached Table 5.1 summarizes the existing evidence on assessing the results of the innovative trends.

Table 5.1 Summary of existing empirical evidence on the learning gains and estimated costs of some innovations in higher education
Full size table

The evidence on learning gains has been supplemented with reference to the cost estimate because what would be the point of promoting innovations that cannot be sustained over time because of the high cost they represent. In short, except the change in the orientation of study programs from content-based to competency-oriented, the three other innovative trends tend to have higher costs than traditional teaching and learning methods in higher education, spanning from two times to up to five times—and this increase comes as a result of the much-needed interaction that seems to be key for student success. Other than this, PBL seems to be worth the effort, given the benefits for learning results and student satisfaction. More mixed is the evidence about hybridization or distance education as it all comes down to one recurring problem, technology per se does not make a difference: what makes the difference is the teaching strategy.

The first implication is that educational innovation and empirical research must be brought closer together (Pedró, 2015). It is a process that necessitates policies supporting this reconciliation and promoting real empirical research for teaching improvement in higher education. It explains with evidence the added value of the many innovation avenues and the elements that define their relevance and effect. However, it also requires policies that provide faculty members who wish to innovate with the tools of empirical research and the professional skills that allow them to translate evidence into improved teaching practices (Bryk et al., 2015).

There is a pending agenda for higher education institutions and teachers. There is no shortage of empirical evidence about what works, with many dedicated academic journals. Unfortunately, these journals seem to serve more the interests of academics working on teaching and learning from various perspectives rather than the professional interests of teachers themselves. There is probably a need to introduce a new culture that promotes that faculty with teaching responsibilities understand the importance of accepting that they need to undergo a professional development process because being an excellent researcher does not equate to becoming an acceptable teacher. A passionate researcher can be an excellent role model. However, even the most experienced academic could benefit from a better understanding of the scientific laws that govern learning and from joining forces with other colleagues to learn in a collegial community about what works in teaching in higher education and why and how to translate that research-based knowledge into better practices. Educational innovation needs to move from the current stage of blind testing into a more scientific approach for those expected to promote a scientific approach to problem-solving, precisely.

Today, the word “higher education” or “university” evokes the same mental image everywhere in the world: that of a structure with classrooms where students await their professor’s lecturing. Moreover, there is a wide societal belief that this old model no longer serves the interests and demands of the twenty-first century. However, the fact is that we are still unsure of the mental picture of higher education that will replace the one that still populates our minds. This likely explains why there are so many parallel paths of innovation, none of which have ever produced an alternative image with sufficient strength to be universally accepted. Twenty-five years have passed since Sarason (1996) said that it was time to replace intuitions and reasoning as much as possible with reliable, usable, and pertinent data. Only when we have substantial evidence on the many avenues of educational innovation will we be able to jointly determine what higher education in the twenty-first century should be like and make it a reality for every student. We are already late.