Ayer, Alfred Julius. 1952. *Language, truth, and logic*. New York: Dover.

Bernstein, Richard. 2010. *The pragmatic turn*. Cambridge: Polity.

Boltanski, Luc, and Eve Chiapello. 2007. *The new spirit of capitalism.* London: Verso.

Wittgenstein, Ludwig. 1953. *Philosophical investigations*. New York: Macmillan.

Zeppelin University, ed. 2022. *Creativity & performance.* Available from https:// www.zeppelin-university.com/chairs/kunsttheorie/creative-performance. php.

## **Personal Sustainability**

*Oliver Parodi, Christine Wamsler, and Marc Dusseldorp*

#### **Definition**

During the last decade, the concept of personal sustainability and similar approaches, such as inner transition or inner transformation, have received increasing attention in sustainability science, education, policy, and practice. Personal sustainability is a highly transdisciplinary field and approach that deals with the human being and its relationality in the context of sustainable development. This applies particularly with regard to (1) human beings as bodily, conscious, and rational subjects, (2) their inner worlds, and above all (3) their relationships and interdependencies with the external world (see Parodi and Tamm 2018b).

As a conscious and rational subject (1), the *human being* is seen as a responsible and capable agent in the struggle for sustainable development. The human body is addressed, too, not only in terms of health but also as an essential condition and expression of human life. *Inner worlds* (2) include individual and collective mindsets, values, beliefs, attitudes, worldviews, emotions, and sensations and associated cognitive, emotional, and relational barriers and capacities (Wamsler 2020; Wamsler et al. 2020, 2021; cf. Hunecke 2023). These inner worlds must not only be described intersubjectively or scientifically from the outside, but essentially have to be explored and experienced individually. Those (inner) human dimensions are intrinsically linked to the *"outer" world* (3) in the context of sustainable development in many respects: as sustainable or unsustainable acting and behavior (e.g. consumption, lifestyles); or as affected by outer factors (e.g. climate anxiety); as drivers or barriers for adequate action; or as root causes for sustainability crises and deep leverage points for change – and as such as fundamental to the solutions to the world's greatest challenges (IPCC 2022a, 2022b; Wamsler and Bristow 2022).

Personal sustainability is thus about addressing inner human dimensions to enable a deepening and expansion of human consciousness, awareness and connectedness (to self, others, and nature) and to nourish inner human potential and capacities to care for a better, more sustainable life across individual, collective and system levels (Wamsler et al. 2021, 2022; cf. Hunecke 2023; Parodi 2018). Personal sustainability thus includes a profound shift in perspectives towards a more relational paradigm, by emphasizing and expanding interdependency and connectedness. It is based on the understanding that strengthening the relation and connectedness to ourselves, and the world we share, is leading to an increasing circle of identity, care, and responsibility, and hence to a more ethical, more prosocial, compassionate life – in alignment with what is needed for an (outer) sustainable development (Wamsler et al. 2021, 2022).

The concept of personal sustainability is immediately related to the concept of sustainable development. At least three relations can be differentiated (Parodi and Tamm 2018a, 2018b). First, personal sustainability is an integrated *part* of sustainable development that complements the current sustainability discourse, which is focused on outer aspects. Second, personal sustainability is a *condition* for sustainable development, as an outer sustainability transformation is not fully feasible without an inner transformation. And third, personal sustainability is an independent *end in itself* of sustainable development, which is important since it would contradict the idea to use personal sustainability as a mere instrument for "outer sustainability" purposes or achieving utilitarian aims.

To gain access to this too often ignored part of the sustainability discourse and efforts, academic concepts and methods, e.g. from psychology, anthropology, philosophy, neuroscience, behavioral economics, education, health sciences, and (micro)phenomenology, but also practical approaches of consciousness and relationship work such as contemplation and meditation techniques, perception exercises, and held conversations are applied. The academic and practical approaches are often interlinked and complementary.

The transdisciplinary character of personal sustainability relates to both the macro- and the micro-level. At the macro-level, relevant knowledge and competencies for personal sustainability are not only coming from scientific fields, but also from implicit and indigenous knowledge or contemplative and wisdom traditions. Acknowledging and integrating them is crucial. On the micro-level, personal sustainability condenses transdisciplinarity in one person: a scientific approach is combined with self-ref lection, exploring and personal experience and action. In parallel, approaches with a similar focus, like *inner transformation*, *inner transition*, *inner change*, *personal development*, and *personal spheres of transformation* have been developed.

#### **Background**

Sustainable development as global guiding principle has been present in the political acting and scientific discourses for more than 30 years (Dixson-Declève et al. 2022; Schultz et al. 2008; WCED 1987). But, despite wide-ranging actions at transnational, national, and sub-national levels, sustainability problems like poverty, unequal income, climate change, environmental pollution, exploitation of natural resources, the massive loss of biodiversity and fertile grounds are still getting worse and challenges are increasing globally. Policy approaches as well as new technologies have failed so far to generate change at anywhere near the rate, scale, or depth that is needed (IPCC 2022a, 2022b). At the same time, the knowledge required for a sustainable development has increased massively over the past 30 years – in all dimensions: system knowledge, target knowledge, and practical knowledge. From a natural-scientific and technical point of view, we have known what to do for decades. But the gap between knowledge and action is increasing dramatically.

So, what's going wrong? If one looks at (un)sustainable development as a cultural phenomenon, where culture and cultural change is carried out in the interplay between the collective and the individual (Hansen 2011), one can recognize that almost all effort for sustainable development so far has been located at the *collective* side of culture (technology, legislations, rules, economic mechanisms, political strategies, etc.). This focus on collective and outer aspects is part of modern societies' scientific and mechanistic worldview – and, as a result, climate change, loss of biodiversity, and other sustainability problems are generally framed as *outer* – technical or political challenges which are addressed with a "fixit mindset", and less as a matter of human consciousness, worldviews, associated disconnectedness, and alienation (Leichenko and O'Brien 2019).

While the role of individuals and their inner worlds were initially largely ignored, over the past two decades they have been increasingly considered in the sustainability discourse, but from an external, and instrumental perspective (e.g. nudging). Inner, and relational perspectives, capabilities, and interdependencies remain largely ignored however (Parodi 2011; Wamsler et al. 2022). This, in turn, narrows the possibilities for deeper change that requires tackling the human and inner root causes of global challenges. Put together, personal sustainability involves a change of perspective and as such is not an alternative but a complement and should be an integrative part to the common discourses, theories and practices of sustainable development.

As for etymology, the term *personal sustainability* is translated from the German term *Personale Nachhaltigkeit*. It was invented and introduced in 2008 in the course of the formation of the School of Sustainability at the Karlsruhe Institute of Technology as a search term and working title for new ways of understanding, teaching and practicing sustainable development (Parodi 2011; Parodi and Tamm 2018b). The attribute *personal* seemed to be best suited to describe the intended focus on human, individual, and inner human aspects of sustainable development. Thereby the term *person* describes a human being as a relational individual in its specific character of being conscious, responsible, and able to act reasonably. In this sense, *personal sustainability* is also always to be thought of as *trans*personal sustainability.

Although personal sustainability is a new field of transdisciplinary research, it has antecedents and roots in earlier fields and concepts. At the least, s*ustainability science, environmental psychology, behavioral economics, systems theory, human ecology*, and *socio-ecological research* have to be mentioned here. *Deep ecology* (Naess 1972) and *ecopsychology* (Roszak et al. 1995) can be seen as precursors of a kind. Another practice- and change-oriented root lies in the field of *sustainable* or *ethical leadership* and at the interface between arts and sciences in the context of sustainable development. Finally, in the sphere of the ecological movement and community-building there are a lot of efforts that bring together ecology and personality, as well as communal and individual sustainable development (e.g. Joubert and Alfred 2007).

#### **Debate and criticism**

Personal sustainability is still an emerging field of transdisciplinary sustainability science and action, and still a search term for a huge field of unexplored phenomena and interdependencies. the publication *Personal Sustainability* (Parodi and Tamm 2018a) was a first important step to grasp and map the research field, and it was accompanied by further advances, reviews, and theoretical developments (Wamsler et al. 2021, 2022). The latter include, for instance, "the inner–outer transformation model" (Wamsler et al. 2022), "the three spheres of transformation model", and conceptual ref lections on paradigm shifts in consciousness from an I–I, I–it to an I–We World (Parodi 2018; Siegel 2022). The number of publications on personal sustainability and related discourses is growing rapidly, and researchers' networks like the international *Inner Transition Group* conduct cooperative research and produce collective publications; they also exchange ideas on related teaching tools (Woiwode et al. 2021).

A recent literature review systematizes the current linkages between inner and outer transformation in different research disciplines (Wamsler et al. 2021). It shows that in *psychology*, mental health and related applied sciences (including leadership, personal, and adult development), diverse context-sensitive frameworks have been developed for understanding individuals, their (cognitive) drivers, and the motivations that can inf luence sustainability. However, they tend to give little consideration to wider societal or systemic issues. Related exceptions come predominantly from the field of environmental psychology.

Contributions in the discipline of *behavioral economics* tend to focus on individuals (or consumers) and the cognitive, motivational, and contextual factors that affect their decisions and choices. Within this context, approaches are limited with respect to: (1) psychological mechanisms; (2) the emphasis on quantitative assessments (mostly via experiments); and (3) their instrumental approach (Wamsler et al. 2021, 4).

Studies from *sustainability science* and *education* tend to emphasize the importance of systems change and the lack of individual agency due to structural constraints. They focus on systems analyses of wider socioeconomic structures, dynamics, and technology, often based on interdisciplinary and mixed-methods approaches. The role of individuals is, in this context, perceived to be of little importance (see *agent–system dichotomy*, Wamsler et al. 2021, 5).

At the same time, there is increasing recognition and associated *systems theory* that inner dimensions are deep leverage points for change (Ives et al. 2020; Wams-ler et al. 2021, 7-8). They are more difficult to inf luence, but lead to more substantial transformation, as it is from this level that the system's goals, structures, rules, and parameters emerge. Despite the urgent need to better link inner and outer approaches for sustainability and climate action, related knowledge is still scarce and fragmented (Meadows 1999, 7–8).

One central question in the current personal sustainability debate is the relevance of relations, connection, and interdependency. There is mounting evidence that the human story of separation, disconnection, and alienation is the underlying common thread of interlinked social, socioeconomic, and environmental crises and, in general, of today's global unsustainable way of life (Leichenko and O'Brien 2019; Wamsler and Bristow 2022; Wamsler et al. 2021). Separation, dualism, and disconnection form parts of the modern worldview – and are part of the success story of modern civilization: abstract thinking, science, predicting, controlling, and exploiting our environments via technology are achievements that allow and support wealth and security. At the same time, the massive and life-threatening destruction of the human environment and of humans' own basis of life is a direct consequence of this separation. The world seen as a pure object, free for human use and unrestrained access has led to the present excessive overuse and alienation. With the rise of science and technology, humans have become increasingly removed from nature, from each other, and even from themselves (Wamsler and Bristow 2022, 4–11). Climate change and all other sustainability problems can thus also be understood as an unintended – albeit deeply inscribed in culture – consequence, a subconscious manifestation of the globalized disconnected modern way of life, or, pointedly, of human *being* (Wamsler and Bristow 2022, 5).

In consequence, one crucial sustainability challenge is to "know thyself" (Niehaus et al. 2018, 51) to become aware of ourselves, our individual and collective inner worlds, worldviews, emotions, and attitudes. And then, to work on (reestablishing) our relations and connections to the world in and around us. In essence, personal sustainability work essentially means relationship work – regarding how we relate to ourselves, others, and the world at large.

For personal sustainability as a scientific endeavor, an important (transdisciplinary and methodological) question is about how to link and integrate knowledge from the increasing number of studies that look at personal sustainability topics, especially at the linkages between inner and outer (systems) change. However, related approaches are segregated across multiple disciplines that use heterogeneous terminology, with different ontological, epistemological, and ethical underpinnings. In addition, most studies adopt a narrow scope. They look at the link between individual and systems change from a one-directional perspective (Wamsler et al. 2021).

To actualize its transformative potential, personal sustainability has to become more inter- and transdisciplinary, and become common practice (e.g. in the course of relationship work). In addition, it is important to highlight that sustainability is *not only* a scientific endeavor. Engaging with inner human worlds requires introspection, self-perception, and experience that are to a high degree individually and not easily accessible for traditional scientific approaches.

Consequently, personal sustainability is also normative and programmatic, because (1) on the micro-level it is about experiencing and being involved, to perceive, feel, and be as a human being – and not only to think and learn about inner worlds from a scientific mediated third-person perspective; and (2) on a macro-level, following the proverb "You can't solve problems with the same mindset that created them". In fact, current worldviews and scientific approaches are at the root of our unsustainable way of live, and thus we have to challenge them – without ignoring or rejecting them completely.

All in all, despite advances, more interdisciplinary discourses, and theory and method formation, are needed to advance the transdisciplinary field of personal sustainability. This includes exploring aspects, phenomena, and practices of personal sustainability in diverse and new ways. The latter is linked to a call for a "personal sustainability science" that works in a connected way and includes more first-person research and methods such as micro-phenomenology. More investigation into different forms of education and practices is needed (Parodi and Tamm 2018a, Wamsler et al. 2021).

#### **Current forms of implementation in higher education**

In the context of transdisciplinary learning, personal sustainability puts emphasis on self-knowledge, relationship work, and people's potential as change agents to support individual, collective, and systems change. Courses in this field differ in their foci regarding: (1) the individual, collective, or system level; (2) their transdisciplinary and transformative substance: more cognition-, experience-, or action-oriented; and (3) their closeness to and occupation with sustainability science and concepts.

A review of evidence-based academic literature by Wamsler et al. (2022) suggests four interrelated categories of practices that can contribute to personal sustainability: (1) contemplative practices and interventions; (2) psychological- and cognitive– behavioral-based interventions; (3) transformative facilitation, communication, and coaching tools; and (4) transformational education and leadership approaches.

Over the past five years, scholars and practitioners have increasingly combined and adapted such practices for personal sustainability to develop transformative education and leadership approaches in higher education. They have combined complexity and systems and design thinking with various practices, and come up with a certain theory and pedagogy for linking inner and outer change (Wamsler et al. 2022). Transformative education is increasingly offered by universities all over the world, but only few explicitly address personal sustainability and inner transformation in a comprehensive way. One example comes from the Waterloo Institute for Social Innovation and Resilience (WISIR, Canada). Their "Decolonial Systems Thinking & Resilience" courses offer a series of seminars and professional development courses that help to foster the capacity for in-depth work and cross-cultural capabilities for broad, systemic change. Through decolonial practices and methodologies, these courses – held by a couple of scientific and Indigenous knowledge holders – support the cultivation of new skills and capacities required for sustainability transformations.

Another example, the "Sustainability and Inner Transformation" course at Lund University Centre for Sustainability Studies (LUCSUS, Sweden), runs every year over three months and includes lectures, seminars, councils, and a practice lab that are designed to explore the role of inner dimensions, to support individual, collective, and systems transformation toward sustainability. Knowledge, tools, and practices from sustainability science, social neuroscience, psychology, behavioral economics, contemplative studies, climate policy integration, and inner–outer transformation theories are systematically integrated. A further recent example from the University of Natural Resources and Life Sciences Vienna (Austria) consists of a course on "The Inner Dimension of Sustainability: The Role of Values, Emotions and Worldviews". Over two weeks, students explore the inner dimension of sustainability on both theoretical and practical levels.

At Karlsruhe Institute of Technology (KIT, Germany) there have been courses and seminars explicitly focused on personal sustainability since 2008. These courses address the individual and systemic level, are self-experience and relation-oriented, and link inner aspects closely to the common theory, concepts, and debates of sustainable development. Further courses at KIT, like transformative project seminars (since 2015), include self-experiments and address inner psychological resources of sustainable development.

In addition, the Principles for Responsible Management Education (PRME), a United Nations-supported initiative, engages worldwide in personal sustainability education and offers related train-the-trainer programs ("The Sustainability Mindset Action Lab").

Aside from higher education, a growing number of private and nonprofit organizations offer or support adult development and leadership courses all over the world that include aspects of personal sustainability. Examples of organizations working in Africa, Asia, Latin America, Europe, the US, or Australia include The Work That Reconnects, Pacific Integral, The Inner Green Deal, The IDG Initiative; RTLWorks, and CChange. And an increasing number of guidelines provide an overview of different practices (Wamsler et al. 2022).

Overall, transdisciplinary settings are particularly fruitful for supporting sustainable development and associated education, as transdisciplinary methods have inherent didactic qualities (Dusseldorp and Beecroft 2012, 11–35). Personal sustainability can and should become an integrated part of related endeavors. Ivanova and Rimanoczy (2022) present examples across five continents and over 150 student voices depicting transformative experiences and shifts in mindsets. Put together, this shows that personal sustainability education is urgently needed and possible.

#### **References**

Hansen, Klaus P. 2011. *Kultur und Kulturwissenschaf t*. Stuttgart: UTB.

Hunecke, Marcel. 2023. *Psychology of sustainability*. Cham: Springer.

Meadows, Donella. 1999. *Leverage points: Places to intervene in a system*. Hartland: The Sustainability Institute.

Næss, Arne. 1972. *Shallow and the deep.* Oslo: Inquiry.

## **Real-World Lab**

*Oliver Parodi, Anja Steglich, and Jonas Bylund*

#### **Definition**

In the pursuit of accelerating and extending sustainability transformations, an experimental turn has occurred in sustainability research since the 2000s. Around the globe, more and more transdisciplinary laboratories and workshops like *living labs*, *transition labs*, etc. are established in real-world contexts, which foregrounds experimentation for more sustainability (McCrory et al. 2022; Turnheim et al. 2018). However, in Germany, a specific form of transdisciplinary experimental lab was developed during this time: real-world labs (German: *Reallabor*). These models are elaborate and impactful in terms of promoting change in everyday settings, with a focus on transdisciplinary and transformative sustainability research at the intersection of science and society at large. Against the background of increasingly pressing sustainability challenges and a necessary change in science (Schneidewind and Singer-Brodowski 2014; WBGU 2011), the concept of real-world labs found its way into academic research discourse and practice in the early 2010s (Parodi 2011; Schneidewind and Scheck 2013). Real-world labs are places and incubators to develop and research sustainability solutions, or, in a nutshell, to experiment and examine desirable societal futures by scientific means.

Real-world labs can be set to explore a wide range of issues. This can be, for example, regenerative energy supply, socially responsible environmental protection, sustainable consumption, climate protection, or even the sustainable development of a city district. Many examples can be found on the real-world lab network website (2023). The crucial common aspects in how real-world labs are realized is that researchers and problem-owners enter into dialogue, share goals, and collaborate in practice. Researchers and (other) societal actors proceed transdisciplinarily and cooperatively, learn from each other, ref lexively minimize risks, and jointly initiate and shape contributions to sustainable development (Bergmann et al. 2021).

In terms of content and concept, the recent term *real-world lab* still remains open to interpretation. Its definition is the subject of scientific and political debate (Schäpke et al. 2018) and does not meet with consensus. However, a widely

shared sense of what real-world labs are has emerged in theoretical, conceptual, and practical discourse: a real-world lab describes a transdisciplinary research and development facility and setting that serves to conduct experiments in a spatially delimited societal context, initiate sustainable transformation processes, and support scientific and societal learning processes respectively (Parodi et al. 2017, 80). Although definitions may vary, these aspects are ref lected in them (see de Flander et al. 2014). Based on this understanding of real-world labs, a set of nine constitutive core characteristics can be identified (Parodi et al. 2016):

Ideally, one would only speak of a *real-world lab* when all these characteristics are present. Beyond that, real-world labs are closely related to other kinds of co-creative labs – such as *living labs*, *transition labs*, or *green urban labs* (Aßmann et al. 2017; JPI Urban Europe 2023). The explanation of the term and the list of constitutive core characteristics can also be used to distinguish real-world labs from related concepts and labs. For instance, living labs are similar to real-world labs regarding characteristics 1, 2, 4, 6 and 8 but not necessarily to the characteristics of 3, 5, 7, and 9.

Etymologically, the term also refers to the decades older term *real-world experiment* and the related notion of "society as laboratory" (German: *Gesellschaf t als Labor*) (Krohn and Weyer 1989, own translation). It draws upon the critical discourse on the risks of technically advanced societies and the (inadequately perceived) role of science in the 1980s but turns it into a constructive approach.

#### **Background**

The development of real-world labs as hybrid entities at the intersection of research and society ties in with different, partly convergent schools, concepts, and currents in science and society (Parodi et al. 2017). It is the combination of these that bestows on real-world labs their novelty and originality. The central problem background is the increasingly destructive side effects of modern lifestyles and economies, endangering the continued existence of humanity. The concern for a good, humane life for all in the future and the corresponding efforts towards sustainable development (Dixson-Declève et al. 2022; Schultz et al. 2008) is the main motivational and innovation driver for real-world labs. Historically, the idea and first implementations of real-world labs originate from transformative sustainability research (Schneidewind and Singer-Brodowski 2014; Wiek and Lang 2016).

The urgency of societal crises, such as climate change and its effects on ecosystems, habitats, and societies, also makes clear the need for action in sustainability research and calls on the research community to move from knowledge to action. Thus, real-world labs can be seen as a contemporary practical and applied form of sustainability research. With the transformative approach of real-world labs, transdisciplinary research has been expanded to the effect that the goal is no longer only to gain knowledge – the production of *knowledge* for sustainable development – but also to develop practical impulses: contributions to sustainable development in the course of the research. These take place in the form of (transdisciplinary) experiments. Real-world labs are both a specific case of applying transdisciplinary research *and* its further development. With their direct design mission, real-world labs leave the sphere of conventional academic research and become a force to change and reshape societies. They are at the same time knowledge producers as well as practical actors outside the academic context and in this respect *trans-scientific*. This ambivalence does not imply that they are non-scientific. However, they do *not only* proceed scientifically – which in turn gives rise to specific potentials, but also to challenges.

Thus, real-world labs operate also in the tradition of those forces of inter- and transdisciplinarity that try to broaden, renew, and reform research and science

(Bergmann et al. 2021). In general, their aim is to bring the cognitive processes of research closer to the issue at hand in order to be able to grasp and describe them more accurately. In the case of real-world labs, the issue is the transformation of an unsustainable society into a sustainable way of life and economy. Real-world lab research – and also teaching – approaches these transformation processes from an inside perspective. Real-world lab researchers are part of the change and gain their knowledge from an active and participating perspective. Real-world labs and the idea of the "Great Transformation" (Polanyi 2001) introduced into scientific and political debates, develop in parallel and relate to each other (WBGU 2011, 2016). As "institutions of change" (Parodi 2019, 8, own translation), real-world labs are intended to support, research, and accelerate the transformation of settlements in particular (WBGU 2016).

Alongside sustainable development, transdisciplinarity, and transformative research, the democratization of science forms another ideal root of the real-world labs. Against the background of a democratic society, in real-world labs the knowledge-producing process of research is more closely linked to the legitimized subject of knowledge: the population, the citizens, and the diversity of social actors. Thus, participation, the involvement and co-determination of many actors – if possible from the beginning – is an essential part of real-world lab work (Parodi et al. 2018). As many levels of participation as possible, from information to consultation, cooperation, and empowerment are to be realized (Meyer-Soylu et al. 2016; Parodi et al. 2018). Science communication and bidirectional knowledge transfer play a central role in the work of the real-world labs: not only research should be communicated to different actors in popularized or non-technical jargon. Similarly, impulses from non-academic actors should be equally incorporated into the real-world lab activities in order to generate scientific and societal resonance and effectiveness (Steglich et al. 2020). Furthermore, a democratization of research takes place directly through an (equal) participation of non-academic actors in the entire transdisciplinary process: from agenda setting to co-design and co-production to the utilization of the results.

The orientation on civil society also expresses the democratization of science. Extensive and far-reaching cooperation between science and private sector actors, especially in technology and product development, is widespread. The inclusion of citizens, (local) government, and civil society groups (including nongovernmental organizations) in real-world lab work broadens the social base of people participating in science. In this process, civil society grows into a new role that is crucial for transformation: through the direct participation in knowledge production made possible by real-world labs, civil society is recognized as a full partner in research.

Historically, both the term and the first real-world labs launched originated in transformative sustainability research: Schneidewind and Scheck (2013) introduce the term in the context of a transformative science, which not only conducts

research on transformation processes but also actively supports them. Real-world labs have developed into a research format in their own right that methodically condenses and practically concretizes transformative sustainability research. From the very beginning, real world labs – directly linked to urban development, urban research, and urban transformation – were conceived as a framework for societal research, transformation, and learning processes (de Flander et al. 2014). Already at the beginning of the real-world lab discourse, the above characteristics 1, 2, 3, 4, 8 are programmatically linked to the real-world lab concept. Almost at the same time, first proto-real-world labs emerged apart from the conceptual debate, such as the *District Future – Urban Lab* (2023; and see Parodi 2011), whose objective is the sustainable transformation of an existing urban district in Karlsruhe by means of a long-running transdisciplinary and participatory process (Parodi et al. 2018). To date, the establishment and spread of the term and concept have been accompanied by a semantic diversification and partial reinterpretation of the term.

#### **Debate and criticism**

Are real-world labs really new? The concept, discourse, and practice of real-world labs are undoubtedly new, especially in the context of academic research. However, real-world labs build upon many strands of discourse and practice, some of them decades old, combine them, and develop them further (JPI Urban Europe 2023). Since real-world labs are essentially about the concretization, operationalization, and ideally institutionalization of transdisciplinary sustainability research, the debates about real-world labs focus predominantly on aspects of transdisciplinarity and transformative research. Some of the real-world lab characteristics are controversial, such as the question of whether and how real-world labs are to be aligned with the guiding principle of sustainable development (for a critical appraisal, see Defila and Di Giulio 2018).

The term combines and merges *reality* and *laboratory* and thus points to a immanent epistemic tension between, on the one hand, the highly controlled environment of a laboratory, with which the attempt is made to create a stringent framework for the production of knowledge out of delimited experiments, and, on the other hand, the non-academic everyday practices full of complexity and contingency. In order to achieve impact, real-world labs must be based in everyday life settings and are therefore context-bound. This in turn makes it difficult for them to generate transferable knowledge. In this respect, real-world labs often run the risk of merely producing case studies while comparative analysis between them still needs to be done, bar a few rare occasions.

The role of the participating researchers in real-world labs is sharpened by the dual objective and strong proximity of research and design. Thus, in addition to being the "honest broker" and "issue advocate" (Grunwald 2019, 170–76), the academic researcher is potentially also present in the role of designer, mediator, and process organizer. Hence, in addition to (individual) conf licts between roles and interests, the researcher involved may be overtaxed. However, some of these role conf licts are due to the hitherto unbalanced sponsorship of real-world labs.

Ideally, the f low of funds and sponsorship corresponds to the types of real-world lab activities. Hence, real-world labs should be supported and financed by research funding *and* other areas of society, but in reality, they have so far mainly been financed by the research funding system (in contrast to other labs internationally financed from a diverse range of funders; see Bylund et al. 2022). This distortion of funding and sponsorship hinders the development of transformative potential and discredits real-world labs as research ventures. Thus, it is not the task of academic research to shape society directly or to pursue societal transformation. A real-world lab financed exclusively by research funding misuses research resources for design purposes. On an individual level, the scientific sponsorship of real-world labs leads to conf licts and double burdens, as researchers have to manage research as well as design (processes). The necessary, often costly non-scientific activities such as the conception, initiation, and support of transformation processes, event organization, communication, etc. are rarely rewarded in the academic research system.

A major potential of real-world labs is to institutionalize them as actors of change (Karvonen 2018; WBGU 2016). Real-world labs, which – similar to engineering or natural science laboratories – would be established for 30, 50, or 100 years, would be a true innovation in the science system and would entail new framework conditions and unprecedented possibilities for transdisciplinary and transformative research. Transformation processes could be stimulated, accompanied, and researched over the long term, and evaluated ex post. So far, with few exceptions, real-world labs have been designed as research projects with durations and funding periods of about three years. However, far-reaching social and cultural transformation processes do not take place within a few years, but take decades. In addition, setting up a real-world lab can take a great deal of time and money: exploring the social context, identifying relevant actors, building trust and networks, acquiring real-world lab skills and premises, synchronizing research, practice, and teaching. The multifaceted and intense set-up work in a project lasting only a few years becomes disproportionate to the actual experimental work and its evaluation.

Current research questions for the further development of real-world labs are "What impact do real-world labs really have?", "How can we scale them up?", and "How can real-world labs contribute to a to sustainable technology transformation in a ref lexive and responsible manner?" (Parodi et al. 2022).

#### **Current forms of implementation in higher education**

Real-world labs aim to implement and perpetuate scientific and social learning (Singer-Brodowski et al. 2018), and are thus didactic undertakings per se. Through the coupling of research, teaching, and practice, as well as the involvement of many often very different kinds of actors (Parodi et al. 2018; Steglich et al. 2020), real-world labs form rich learning environments and are, at least implicitly, educational institutions (Beecroft 2018). Education can occur at all scales: from individuals to groups, organizations, and society at large. Dialogue, resonance, and ref lexivity are central aspects of learning. As a framework for transdisciplinary and transformative research, they enable precisely those didactic aspects of transdisciplinary and transformative research.

The forms of didactic implementation in the real-world lab are as diverse as the constellations of topics and actors within the lab or its social and spatial contexts. They range from self- and group experiments, conventional or transformative seminars incorporating student projects, service learning, lecture series, training courses, practical or scenario workshops, to self-experience of personal sustainability (Parodi and Tamm 2018) or serious gaming forms such as planning or learning games in which the actors involved swap roles (Beecroft 2018). In addition to the obvious and often established connection with university teaching (see Beecroft 2018; Steglich et al. 2020), real-world lab educational activities are also finding their way into primary, secondary, and vocational schools. An established link between real-world lab research and university teaching can be found for example at Leuphana University Lüneburg, ETH Zurich, TU Berlin, and the Karlsruhe Institute of Technology, where lab activities are integrated in the accompanying studies in sustainable development as transdisciplinary student projects. Related labs are also being directly integrated into higher education outside Europe, such as Cité-ID in Montreal, Canada. As real-world labs are showing signs of transformative potential and impact, other universities are currently expanding their offerings related to this approach.

 However, they only work if they are adapted to and integrated in the local social and cultural context.

#### **References**

Aßmann, Katja, Markus Bader, Fiona Shipwright, and Rosario Talevi, eds. 2017. *Explorations in urban practice: Urban School Ruhr Series*. Barcelona: Dpr-Barcelona.

Singer-Brodowski, Mandy, Richard Beecroft, and Oliver Parodi. 2018. Learning in real-world laboratories: A systematic impulse for discussion. *GAIA* 27 (1): 23–27.

## **Research Integrity**

*Marie Alavi and Tobias Schmohl*

#### **Definition**

*Research integrity* refers to the conduct of research in accordance with accepted research norms and practices as well as ethical values. It is helpful to examine the term's constituent parts in order to define this concept more precisely.

In general, *research* refers to a methodologically sound and critically minded scientific investigation: It is a process of exploring the new or unknown according to methodological standards usually derived from domain-specific contexts and under the premises of objectivity, reproducibility, and reliability. Students and research professionals must adhere to their discipline's standards, codes, and guidelines as well as those of their institutions (universities, businesses, or research organizations) and their respective governments' laws, rules, and regulations. The importance of disseminating findings to other researchers (*science to science*), practitioners who apply their findings in practice (*science to business*), or to the general public (*science to society*) is also growing. Given the societal, ecological, political, and economic significance of research findings, one of the most important requirements to all research actors, fields, and disciplines is "to ensure the highest levels of integrity in research" (OECD 2007, 1), to maintain society's trust in research, to protect the reputation of researchers and institutions, to ensure the reproducibility of research results, and to prevent fraud and misconduct (Science Europe 2017, 2-5).

The word *integrity* is composed by the Latin prefix *in*- (not) and the verb *tangere* (to touch). Its adjectival form, "integer", refers to the state of an entity that is "in no way touched, affected, altered [or] corrupted" (ten Have et al. 2021, 641). In this sense, research integrity consequently carries moral implications: There is widespread agreement that research should be conducted ethically and in conformity with the established norms in order to generate honest and reliable research results. In this context, the term "integrity" refers to the disposition of researchers to conduct research in accordance with appropriate ethical, legal, and professional frameworks, obligations, and standards. This relates to several levels of accountability, including those of individual researchers, their institutions, (potential) clients, the government, and the general public.

Between individuals, structures, and systems, research is conducted on a multilateral scale. Therefore, all parties involved in or inf luencing the research process are expected to generate scientific knowledge in an honest, valid, and trustworthy manner, ideally independent of ideological, economic, or political motives. Individual researchers, collaborative teams (institutional, inter-institutional, international, corporate), research performing organizations (such as universities and non-university research institutions), research funding organizations, scientific journals and publishers are parties involved in research. Moreover, public authorities, "university administrations, ethical review institutions, [and] legislation" (Helgesson and Bülow 2023, 118) are expected to establish the conditions necessary for the achievement of research integrity in its entirety.

Research integrity encompasses both external and internal research norms: external norms in the form of laws or regulations, guidelines, codes, or rules that guide the conduct of researchers, and internal norms in terms of internalized standards or desired behaviors. The research integrity framework addresses research *actors*' behavior and responsibility (a, c), as well as the conduct and impact of the *research itself* (b, c).

research integrity and research ethics should be understood holistically as complementary perspectives that relate to a situation, problem, or strategy to varying degrees.

Research integrity transcends disciplinary, thematic, cultural, and national boundaries by incorporating all of these factors and multiple viewpoints. Therefore, a transdisciplinary approach to research integrity education offers a promising means of effectively communicating pertinent aspects of research integrity across disciplines.

#### **Background**

Research integrity is not an enshrined construct, but has been a topic of ongoing activities of the research community for two decades. It spans national, institutional, and disciplinary boundaries in a "global effort to foster integrity" (Steneck et al. 2017, 3). Numerous guiding documents, conferences, studies, or educational resources have emerged in this context. Fifty-two nations are currently represented at the World Conferences on Research Integrity, held in Lisbon (2007), Singapore (2010), Montreal (2013), Rio de Janeiro (2015), Amsterdam (2017), Hong Kong (2019), and Cape Town (2022), as a result of initial work by the United States Office of Research Integrity and two members of the Organisation for Economic Co-operation and Development, Canada and Japan. The European Code of Conduct for Research Integrity (ESF and ALLEA 2011), which was intended to serve as an umbrella standard for Europe (revised and published in its final version in 2017), or the Montreal Statement on Research Integrity (3rd World Conference on Research Integrity) are some of the concrete reference documents for research standards that have emerged primarily in the last decade. The conclusions of the Council on research integrity (Council of the European Union 2015) was another significant document because it placed an emphasis on ethical principles in addition to integrity. This was followed by the Hong Kong principles (Moher et al. 2019), which emphasize researchers' behavior. On the global landscape, there are several other guidelines. To implement them on the institutional level, they are either imposed on institutions by government mandates or by making their establishment a requirement to receive funding. However, most higher education institutions implement the standards on the basis of their commitment (Steneck 2006, 67), with the demand for easy access and dissemination among their researchers, employees, and students emphasized.

These efforts paved the way for further initiatives promoting and safeguarding research integrity and ethics and creating an interplay of various types of expertise and methodologies. Among such initiatives are science-led infrastruc-

tures like the ombuds system as well as reproducibility networks, research integrity offices and research ethics committees, which serve as platforms for the dialogue between organizations and professionals and provide advisory services for the investigation of misconduct or ethical aspects. In addition, several guiding, mentoring, and training initiatives as well as studies thereof have emerged. The different instructional, methodological, and content-related programs for professionals, educators, students at different levels of qualification, institutions, policymakers, and ideally industry stakeholders show the different angles from which we can approach a comprehensive culture of research integrity and meet the current needs of specific communities.

The reason for many initiatives regarding research integrity are breaches in research. The research community places particular emphasis on serious misconduct like *fabrication* (creating data and reporting them as if they were real), *falsification* (the manipulation, modification, withholding, or elimination of data), and *plagiarism* (taking others' statements, data, ideas with inadequate or no citation of the source; Bouter 2020, 2364). Moreover, so-called *questionable research practices* exist in the gray area between scientifically desirable practices and those to be rejected (Fanelli 2009, 1). Among many others, such practices include *cooking* (giving ordinary observations extraordinary character), *mining* (highlighting a discovered statistically significant relationship as the true intention of the analysis), selective reporting or citing (only if it meets one's own expectations), etc. (Bouter 2020, 2364). Predatory and hijacked journals (Abalkina 2022) and AI-based paraphrasing tools or text generators pose new challenges to research integrity.

#### **Debate and criticism**

The need for trustworthy and high-quality research is the main driver in the establishment of research integrity, while persistence of misconduct and questionable research practices demonstrates that research integrity is not firmly established in the field. Especially the latter are considered to be remarkably detrimental due to their greater prevalence (Bouter et al. 2016, 2363). John et al. even assume "that some questionable practices may constitute the prevailing research norm" (2012, 524). Therefore, there is a great need for a multi-perspective approach of enabling, empowering, mentoring, and training across disciplines, actors, and institutional structures. These include the implementation of codes of conduct as guiding documents for institutions and the monitoring of their observance, the establishment of peer review systems, the introduction of ethics committees, the conduct of misconduct investigations, and strengthening the position of whistleblowers (e.g. ORI 1995). In addition, the concept of *open science* represents an opportunity to make research findings "more traceable and verifiable" (Haven et al. 2022, 2), also for the benefit of citizens as recipients of research results (Priess-Buchheit et al. 2020, 30).

Kalichman points out that research integrity involves "socialization, incentives, and culture" (2016, 785). All actors are therefore called upon to work together in order to develop a structural, institutional, financial, and political environment that is conducive and stimulating for a responsible conduct of research (Sørensen et al. 2021, 2). The most problematic criticism, however, is that the research system creates incentives that work against research integrity such as funding and publication pressures (Bouter 2020, 2364) and that there are situations when the opportunities and obligations of each research actor are not entirely transparent or well-defined (Horbach and Halffmann 2017, 1464).

Consistent efforts to intensify training are therefore required from the educational sector. However, the effectiveness of interventions is the subject of ongoing research. The various requirements of research integrity in single disciplines (for example, data management or ethics codes in medical sciences versus humanities) raise the question whether a generic approach of the training or a more specialized, discipline-specific one should be chosen (Sørensen et al. 2021, 2), which didactic method is the most productive, and which content should be taught. Another aspect is the challenge to transmit or evoke values and an inner orientation in the sense of a scientific habitus, in addition to teaching concrete knowledge (such as rules or methods). This challenge can be addressed through a transdisciplinary approach, where learners can gain experience in other contexts, be confronted with insights from other disciplines or new theories, and thus enrich their inner attitude towards their research activity.

Since research results stemming from the private sector also affect society, it is necessary to investigate the extent to which research integrity is taught and practiced in the economic realm. Given that academic research integrity faces the behavioral, institutional, and infrastructural challenges outlined above, and that research, its funding, and its dissemination involve numerous, potentially very diverse interests, the assessment of responsible conduct of research in industry and the private sector is a crucial issue. This leads to the conclusion that research integrity education should be accessible not only to students, but also to researchers and educators at all career stages. A certain level of training should be available as well to non-researchers (such as funders, reviewers, journals, policy makers; Fanelli 2019, 5, 11) who are involved in the research process in different contexts. Considering that society's ability to understand research outcomes is a prerequisite for the trust in science, citizens should also be educated in research integrity (Priess-Buchheit et al. 2020, 30).

#### **Current forms of implementation in higher education**

The claim that "integrity in research should be developed in the context of an overall research education program" (Institute of Medicine and National Research Council 2002, 84) is highly pertinent and an ongoing effort of educational institutions. Key findings from the training program Path2Integrity (2019–2022) show that students at lower qualification levels are less motivated to engage in research integrity training lacking relevance for them (Valeva et al. 2022, 530). Whereas it is precisely during their university studies that learners are introduced to research activities and required to apply scientific methods such as literature review, responsible elaboration, and report of data, but also to be accountable and open for critical ref lection (Steneck 2006, 56).

While universities offer various courses on individual research integrity topics (such as scientific writing, research methods, etc.), there are several educational programs, mostly developed in the academic context, which are applicable at an international level and which enrich the educational landscape both thematically and methodologically. These include, for example, the toolbox Standard Operating Procedures for Research Integrity, which assists institutions in developing a Research Integrity Promotion Plan (SOPs4RI) or the wiki-platform The Embassy of Good Science, which serves as a repository for comprehensive information on educational resources worldwide. By 2020, Pizzolato et al. have collected 237 mostly online and freely accessible domain and non-domain-specific educational resources consisting of videos, online (self-processing or collaborative) courses, textbooks or case study collections covering primarily misconduct-related content, followed by publication ethics, data management, and others such as research procedures or collaborative working. Examples of these are VIRT2UE, INTEGRI-TY, and Path2Integrity. While all of them make their training available worldwide, VIRT2UE addresses mainly educators from all disciplines and aims to strengthen the learners' attitudes towards research integrity. INTEGRITY is a modular training mainly for high school students, stimulating their critical awareness by mostly socially relevant (real or fictive) cases that are considered to be interesting for this target group (from activism to usage of mobile devices). Path2Integrity offers various modular and dialogue-based learning materials for citizens, undergraduates, graduates, and early career researchers that address the content fields of the European Code of Conduct for Research Integrity and are thus applicable across disciplines. Formal and informal learning pathways (learning materials, campaign, and role models) are used to address learner awareness. Additionally, it offers several evaluation instruments like a feedback sheet or a pre- and post-test survey in order to assess possible learning gains (Zollitsch et al. 2021).

Several recommendations and findings from training conducted can be gleaned from the available literature. Nonetheless, they do not constitute universal guidance and must be evaluated in light of the particular context and learning objective. Katsarov et al. (2022, 951) outline that voluntary courses have a more positive impact on learning outcomes. The much-needed learner attitude for research integrity, however, is partially hampered by learners with lower qualification levels who question the relevance of research integrity for them (Valeva et al. 2022, 530). The design and effectiveness of interventions, in addition to the question of an (effective) instructional approach, depend on the different statues of learners, such as prior knowledge, research experience, skills, and qualifications.

It is noteworthy that most of the trainings (especially the latter two) tend towards a learner-centered dialogical approach, allowing learners to experience research integrity through role-play, discussion, storytelling, or the presentation of concrete research-relevant scenarios (Hermeking and Priess-Buchheit 2022, 112). This, together with the cross-disciplinary topics and the aspect of formal and informal learning (Path2Integrity), is a useful example of how education in research integrity through a transdisciplinary teaching–learning setting is an effective way to teach and learn many aspects of research integrity.

#### **References**

## **Research-Based Education**

*Tibor Koltay and László Z. Karvalics*

#### **Definition**

Research-based education, leaning on Elliott Seif's (2021) outstanding summary, is "a specific approach to classroom teaching that places less emphasis on teacher-centered learning of content and facts and greater emphasis on students as active researchers", preparing them to be lifelong inquirers and learners. Research-based education orients students' performance through five stages, beginning with active search for and then use of multiple resources in order to explore important, relevant and interesting questions and challenges that lead to clarification and identification of a personal research topic. Gradually, they *"*find, process, organize and evaluate information and ideas … learn how to read for understanding, form interpretations, develop and evaluate hypotheses, and think critically and creatively". During this research process they can also understand how to generate contexts, setting a hierarchy of research questions. Through sharing the results, students are developing "communication skills through writing and discussion" (Seif 2021).

From a student's perspective it is common to talk about research-based education (also as inquiry-based learning, research-intensive learning), which "should help motivate them to become experts in their self-described field. And the more often a student gets a taste of what it feels like to be an expert, in however small a concept, the more they will want that feeling later on in life" (Wolpert-Gawron 2016). Again from a teacher's perspective, it is necessary to call the "other side" research or inquiry-based instruction or research-engaged teaching. From a complex educational and organizational culture perspective the overall framework is regularly designated as research-based environment.

Research-based education gradually consolidated as a well-founded methodological-didactical direction, developing special "teaching the teachers"-type courses, and came closer to citizen science initiatives, channeling open scientific crowdsource projects into higher education. This development could progressively improve lifelong learning, transforming its certain terrains to lifelong research (Z. Karvalics 2013). Lifelong research is an extension of research-based education, transplanting "research skills and academic productivity in a feasible and sustainable approach" to the post-university life of the former students (Himelhoch et al. 2015, 445). However, research-based education is not about supporting the reproduction of scientific reinforcements, nurturing new scholars – it is about producing scientifically literate generations from higher education.

### **Background**

It is a common supposition that children are natural-born scientists, since the process by which children turn experience into knowledge is identical to the process that we call scientific knowledge, produced by scientists (Holt 1989 1989). An example of this thinking is described by Alison Gopnik (2012), who found that "young children, in their play and interactions with their surroundings, learn from statistics, experiments and from the actions of others in much the same way that scientists do" (Yaffe 2022, 10). Francis (2012) evaluates this popular approach as a mixture of truth and falsehood, as researchers' thinking has its sources not only in their natural curiosity and mental plasticity, but it is a learned skill. However, as Shanahan (2011) underlines it, science is not just a grown-up version of a child's curiosity.

While children have the fertile beginnings, becoming a scientist requires that they learn and skillfully practice many abstract skills that are far from intuitive. When students struggle with scientific thinking later in life it isn't because they have unlearned or lost the ability, it's because they (for any number of reasons)did not get to take the next steps to developing those skills and understandings (Shanahan 2011).

This mission has never been completed in elementary and secondary schools. Basic disciplinary science education is a fundamental feature, sometimes with its advanced discovery-based forms which challenged and changed the traditional instruction-based pedagogical culture (Mirzoyan 2021). However, the research environment is simply simulated or emulated into talent management solutions and forms. Now, it is not the child prodigies or wunderkinds, but "child scientists" (McCartney 2011) are the best proofs that there would be several reasons to teach scientific literacy and research skills already to age groups of 12–18 and 8–12. When wanting to complete this unfulfilled mission, it is the role of higher education to provide and practice elementary research skills for all – from the birth of modern universities in the late 19th century.

In medieval universities science making was on the periphery. After the Humboldtian turn, "research (as a process of searching for truth) became a system-forming element of university education, since students, interacting with teachers, acquired not only formal knowledge, but also certain value imperatives that formed

their professional vocation and personal position"(Islomovich 2021, 75). To be able to compose a dissertation became a ritual precondition of graduation, as a metaphor of an intellectual initiation process. Science today is apparently not a privilege of the small number of elected, outstanding people. Moreover, there are enormous differences between three different levels of research-based education practice.

The main goal of the introductory (typically undergraduate) level is to foster student awareness and motivation, making them familiar with scientific thinking, mediating research-related forms of literacy and skills. The outcome is some learnt elements of the scientific method, picking up as many abilities from the research literacy complex as students can. On the medium level, the challenge is to be able to use these skills, capacities, and sensitivities for an inquiry-based practice, solving a research problem while acquiring new disciplinary knowledge in a given field. It is nothing else than the rediscovery of existing scientific knowledge, while students are completing micro-research cycles and learning intensively. Finally, at a high level, the students can become producers of new scientific knowledge. Unfortunately, today this training philosophy is not a strict requirement for research-based education practitioners.

Healey and Jenkins (2018, 54) draw a distinction between four overlapping ways in which students may engage with research. The first one is the *research-led level*, where students learn about current disciplinary research. This is followed by (2) the *research-oriented level*, where they develop research skills; (3) the *research-based level*, where the focus is on undertaking research; and (4) the *research-tutored level*, where they engage in discussions on current research. These "stratifications" come into view in the same way in the most popular typology of citizen science, composed by Haklay (2012), ref lecting the level of scientific profundity of personal involvement in research processes from the simple *crowdsource* logic, followed by *distributed intelligence* practices, reaching the *participatory science* stage, and finally the *extreme citizen science* projects, where full-value contribution is expected and required from the group members.

In order to reinvent the research-based education environment, it is necessary to accept that education and research are equally important and bridge divides between research and teaching staff. These staff members should excel in both research and teaching. Positive attitudes towards research by students should be strengthened among staff and students. Resources to do research must be available for students, among others by involving libraries in teaching information literacy to students. There should be opportunities and incentives for teachers for further development of their research-based teaching competence and excellence, including the creation of opportunities for dissemination of successful practices. This cannot be done without recognizing teaching excellence and monitoring the growth of research-based teaching. Inter alia, introducing an undergraduate student research award may help in achieving goals that can be solidified if there

is more research initiated and financed on the nexus between teaching and research, as well as of research-based teaching and learning in particular (Dekker and Wolf 2016, 10–11).

#### **Debate and criticism**

The analysis of research-based education and learning became a popular scholarly field after the millennium. "More than half of the studies were published since 2010, [which] suggests an increasing interest in disseminating the outcomes of incorporating RBL [research-based learning] practices in Higher Education courses" (Camacho et al. 2017, 4192). However, in the forge of the discourse today is living dialogue, debate, and shared experience of the practitioners through textbooks, special reports, methodology exchange forms, blogposts, and comments. This semi-formal ecosystem of ideas gives account of the advantages and disadvantages of research-based methods.

Many teachers mention the greater interest of students during the whole learning and activity cycle, generating more attention, emphasis, engagement, and ambition, discussing the key topical issues in an open way. It is often highlighted that intensive problem-solving focus and the acquired teamwork routine prepares for real-world situations like few others. Practitioners recurrently testify that the retrieval, recall, and reuse of information in the afterlife is strongly supported by research-based forms of education, enhancing long-term knowledge retention (Lindsey et al. 2014).

The list of disadvantages begins with the ambiguous and shaky feedback. The lack of proper assessment creates confusion and anxiety, and the standardized testing performance is missing or poor quality. The risk of students' embarrassment and reluctance is high. Slow thinkers, introverted students, and the ones with learning disabilities are not prepared for the f lexibility and freedom assigned to this kind of activity. A majority faces difficulties in collaboration, teamwork, and a culture of sharing results. Their overall readiness and responsibility are characteristically low. The lack of reinforcement f low is also a typical problem. The first steps can be attractive and alluring, but later, unravelling the higher skills of participants' than what is needed for, even an eager student quickly become bored. The lack of such skills can be undermining, and can easily frustrate the students. Unprepared teachers produce disorganized teaching, with vague requirements, and a lack of guidance and task personalization*.* The result is a sloppy classroom.

The methodology of research-based education was developed in multifarious ways by researchers and practitioners. The long-standing, literature-hunting desk research was stepwise enhanced by varied quantitative and interpretive disciplinary methods (Slater et al. 2015), and action research in education (Efron

and Ravid 2017). One of the most intensive and engaging forms of action research is community-based research, which is "collaborative and change-oriented and finds its research questions in the needs of communities", combining "classroom learning with social action in ways that can ultimately empower community groups to address their own agendas and shape their own futures. At the same time, it emphasizes the development of knowledge and skills that truly prepare students for active civic engagement" (Strand et al. 2003, 1).

Methodologies were also enriched by disciplinary endeavors. As a part of the development of general art-based research methodologies (Leavy 2020), universities were early adapters, building the experiences fruitfully into their curricula, creating an independent field, art-based research in education (Cahnman-Taylor and Siegesmund 2017). Alongside the design thinking paradigm, its approaches and considerations were transferred easily to research-based education praxis, as design-based research in education (Philippakos et al. 2021).

The latest frontier is challenge-based research and learning. Challenges are for competing student groups to solve problems. Today it seems to be one of the most efficient and motivating frameworks for learning while solving real-world problems through research. This method develops "student transversal competencies, knowledge of sociotechnical problems, and collaboration with industry and community actors" in a versatile way (Gallagher and Savage 2020). This approach is obviously popular in *research-intensive universities*, where the increase of knowledge f low and the production of new knowledge across diverse disciplines are deeply embedded in the education practice (Njuguna 2015), thus directly creating value for society. There are mingled versions of these methods, too. It is easy to mix artbased platforms with other approaches, and design thinking regularly meets with challenge-based projects (Charosky et al. 2018).

#### **Current forms of implementation in higher education**

Healey and Jenkins (2018, 67) collected comparative examples of implemented policies and cases in different higher education institutions all over the world. The updated and improved list below also represents further possibilities of investigation to discover and apply new and new best practices, although there are not many venues where the organized exchange of experiences takes place.

#### *Table 1. International RBE practices*

The involvement and curriculum-based development of varied literacies also fruitfully supports the goals of research-based education. From these kinds of literacies, *information literacy* appeared early and became a fundamental one that is not restricted to textual information, but relates to digital content, data, and images; thus it is not a stand-alone concept, but overlaps with other literacies (CILIP 2018, 3).

*Media literacy*, especially in its critical from is similarly fundamental, as it focuses on trustworthy media content, and considers how messages are constructed (Funk et al. 2016).

The newest entry in this group of literacies is *data literacy*. According to one of its definitions, it aims at enabling individuals to access, assess, manage, handle, and use data (Calzada Prado and Marzal 2013, 126). Citizens' critical and active agency is paramount when society's datafication and decision-making, driven by algorithms, has become normalized. One of the enabling factors of data literacy is data citizenship that underlines critical and active agency that takes account of society's datafication and decision-making, driven by algorithms. It is divided into three components: (1) *Data thinking*, i.e. citizens' critical understanding of data collection and data economy; (2) *Data doing*, e.g. everyday engagements with data, including using and deleting it in an ethical way; (3) *Understanding the digital economy*, i.e. how algorithms work and who is funding social media platforms (Carmi et al. 2020, 10). Nevertheless, *visual literacy* (*visuacy*) can greatly help in providing confident and attractive representation of the used data.

Illustrating these new triggers of research-based education, the following table provides an overview of emblematic courses from leading universities. In the future, the number and plurality of these kinds of literacy-focused and data culture-related improvements will expectedly spread in higher education.

*Table 2. International literacy practices*

By relying on inquiry-based and research-intensive learning, supported by varied literacies, research-based education is meant to provide engaging research opportunities that are well incorporated in learning activities and well supervised by teaching staff (Van der Rijst 2017). This quality research-based education promises varied types of transformative learning experience for a wide range of students. It will play a growing role in education and, simultaneously, in the production of new scientific knowledge, while building more future-proof universities. Research-based education is not just a way to refresh education practice with stronger student motivation, but also outlines a new, community-driven culture of doing science.

#### **References**

Cham: Springer. Wolpert-Gawron, Heather. 2016. *What the heck is inquiry-based learning?* Available from https://www.edutopia.org/blog/what-heck-inquirybased-learning-heather-wolpert-gawron

## **Science Communication**

*Konstantin S. Kiprijanov and Marina Joubert*

#### **Definition**

Science communication is a dynamic field of practice and research that deals with the communication of scientific knowledge to audiences that are typically outside academic institutions. Science communication is widely recognized as a broad term that encompasses a wide variety of actors and formats, and includes a spectrum of activities that range from informal to strategic in nature (Bucchi and Trench 2021). As such, science communication does not constitute a clearly defined discipline, but can be conceptualized – in the words of Bucchi and Trench – as "an inherently, even joyously, interdisciplinary field" (2021, 2).

Historically speaking, *science* is derived from the Latin word *scientia* for knowledge, understanding, and learning (Onions 1966, 797). Today, the term refers to a practice of systematic production and organization of specialized knowledge by means of specific methods and strict quality standards; it is simultaneously a system for stabilizing said knowledge (Bauchspies et al. 2006, 5–6; Mittelstraß 2010). This chapter employs the term science in a broad sense that is not limited to the natural sciences such as physics or geology, but "has a much broader meaning and includes all the academic specialties, including the humanities" (Hansson 2021). Communication refers to the "practice of producing and negotiating meanings" (Schirato and Yell 1997, x).

In order to do justice to the dynamics and diversity of this multi-faceted field of practice and research, science communication is understood as a broad concept that includes "all forms of communication focused on scientific knowledge or scientific work, both within and outside institutionalized science, including its production, content, use, and effects" (Schäfer et al. 2015, our translation). In this way, knowledge is not simply transferred from one person or community to the other, but it is rather negotiated, mediated, and transformed in a mutual exchange of ideas, opinions, and values. In this chapter, a distinction is made between science communication *teaching* and science communication *training.* For this purpose, *science communication training* is defined as practical courses that are

typically offered over one or more days to researchers who are interested to advance their science communication skills. In contrast, *science communication teaching* is defined as academic courses offered by universities and other higher education institutions. Many of these courses are presented as dedicated postgraduate diplomas, Master's courses or PhD programs, but some universities offer modules in science communication as part of degree courses at undergraduate and postgraduate levels.

Although science communication constitutes an essential part of the processes of knowledge production (Horst et al. 2017; Secord 2004) and exchange (Jensen and Gerber 2020), and plays an essential role in transdisciplinary processes, the complex relationship between transdisciplinarity and science communication is yet to be studied from a comprehensive and systematic perspective (Wang 2019). Individual studies, however, offer some promising insights and lay the groundwork for further inquiry. For instance, Mercer-Mapstone and Kuchel (2017) conceptualize the entirety of science communication as a transdisciplinary field due to the inclusion of different actors and the traversing of disciplinary and professional boundaries. Others emphasize that science communication provides the communication skills that are essential for shaping transdisciplinary research processes (Kalmár and Stenfert 2020; Misra and Lotrecchiano 2018; Wang et al. 2019). In addition, Burns et al. (2003, 193) suggest that the act of communication itself has a transdisciplinary dimension, as "the need to explain complex issues in lay terms can lead to new perspectives on a topic and a deeper understanding of the field by the professional".

#### **Background**

The multifaceted nature of science communication stems from the complex socioeconomic background that has determined the evolution of the field within distinct national and cultural settings. Scholars of different branches of knowledge have been sharing their knowledge in different contexts and languages for millennia (Gordin 2015, 35–40; Secord 2004). Many traditional approaches to science communication included elements of entertainment – such as music and art – as well as listening and dialogue. The diverse histories, cultural roots, and trajectories of science communication are ref lected in Gascoigne et al. (2020). Despite the existing national idiosyncrasies, it is possible to trace a common historical trajectory (Gascoigne et al. 2020) along a number of major historical landmarks, such as the growth of the print market; the professionalization, specialization, and institutionalization of academic research; the emergence and proliferation of mass media and, more recently, social media (Bucchi 2008; Dawson and Topham 2020; Kiprijanov 2021). For a comprehensive overview of the history of science communication from the 18th to the 20th century, see Knight (2006), as well as Gascoigne et al. (2020) and the contributions in volume 16, number 3 (2017) of the *Journal of Science Communication*.

In the wake of the institutionalization of academic research, professionalization, and internal and external differentiation of academic disciplines at the beginning of the twentieth century (Mittelstraß 2010), researchers came to believe that science was too complicated for the general public to understand. This idea corresponds to the *deficit model* (also called *deficit-dif fusion model*) of science communication, which was the predominant model until the 2000s. This model describes science communication as a linear transmission of specialized knowledge from a small number of experts to an allegedly ignorant mass audience. The transmission occurs from areas of high concentration among experts to areas of low concentration among audiences. Controversies and misunderstandings are attributed to a lack of scientific literacy among the public. Comparable to Shannon and Weaver's (1949) mathematical model, the deficit model distinguishes between active communicators (senders) and passive recipients who lack any agency.

The deficit model served as the ideological foundation and justification of the *Public Understanding of Science* movement that gained momentum in the United Kingdom during the 1980s and 1990s with the aim of promoting public interest in, and awareness of, the natural sciences (Bucchi 2008). While the dissemination of information about new advances in science is a legitimate and useful activity, the critical f law of the deficit model is the logical fallacy and incorrect assumption that providing more information and better explanations will lead to more public support for and increased public trust in science.

Ref lections on the motivations behind efforts to improve the so-called public understanding of science, as well as concerns about the efficacy of these campaigns, prompted the beginning of systematic science communication research. Criticism from social scientists led to revision of the assumptions and goals of the deficit model. Today, a variety of competing or complementary science communication models exist, as described by Trench (2008), and Schmid-Petri and Bürger (2020), and it is clear that these approaches (or models) are interdependent and often overlap in science communication practice (Brossard and Lewenstein 2010).

According to Horst et al. (2017, 883), the existing models can be placed on a continuum that ranges from *deficit* (one-way, elitist, and fact-oriented) to *dialogue* (two-way or interactive, participatory, and ref lective). Dialogue and participation models acknowledge the communication needs and preferences of specific audiences and prioritize meaningful and "mutually supportive relationships between research and society … through high levels and varied forms of interaction between the two" (Burchell et al. 2017, 200). These forms are also used in transdisciplinary processes, such as participatory research and citizen science. These models ref lect current societal demands for more transparency (Weingart et al. 2021) and a "general participatory/collaborative opening of the science system" (Schrögel and Humm 2020, 488).

As science communication became more professionalized and institutionalized, the demand for professionals in the field began to grow, and science communication became a f lourishing industry (Davies and Horst 2016). Universities responded by offering a growing number and range of degree programs, as has been documented by a number of scholars (e.g. Massarani et al. 2016; Trench 2012; Turney 1994). For example, Schiele and Gascoigne (2020) document how university-based courses in science communication started to emerge in the 1980s (with one precursor program in the United States in 1960), spreading to countries around the world since then.

#### **Debate and criticism**

Proponents of science communication teaching programs use a number of motivations to justify the need for this type of offering in higher education. Motivations include professional capacity building, development of evidence-based policy around public participation in science, provision of authentic educational experiences involving academics and communication professionals, as well as the contributions of this type of program to the employability of students (Longnecker 2014; Longnecker and Gondwe 2014; McKinnon and Bryant 2017; Ramani and Pitrelli 2007).

Already in 1994, Turney pointed out that science communication courses on offer in the United Kingdom in the early 1990s varied from those focusing purely on skills to those with a more theoretical (or big-picture) approach. He argued for the inclusion of theory into science communication education in order to deliver more effective communicators who benefit from lasting intellectual resources, as well as to guard against courses that merely teach students to promote science. Since then, scholars and educators have debated the recurring question about to what extent students need to know the theoretical underpinnings of the science communication skills they learn and how much practical experience should be included in science communication teaching (e.g. Baram-Tsabari and Lewenstein 2017; Mercer-Mapstone and Kuchel 2017).

Overall, there is agreement that the content of science communication programs needs to address both theory and practice, striving for a balance and a productive interface between these components (Baram-Tsabari and Lewenstein 2017; Longnecker 2014; Mercer-Mapstone and Kuchel 2017; Mellor 2013). In general, these authors argue that a theoretical foundation is essential for students to be able to understand and apply the knowledge base, and to identify relevant evidence that can inform and enhance their practice. Practical work, on the other hand, is essential to consolidate what they have learnt and to prepare them for

the world of work. Practical expertise can be brought into these courses via guest lectures by industry experts, as well as by work placements and internships. For instance, Bray et al. (2012) emphasize the need for students to develop self-awareness around their own scientific values and science communication objectives, as well as the contexts in which they operate, necessitating a broad understanding of the societal implications of science, rather than a focus on technical media skills.

Academic programs in science communication cannot afford to be static. In order to prepare students to cope with the increasing complexities of science communication and fast-changing media ecosystems, courses must be f lexible and respond to changing circumstances and the evolving needs and expectations of students and future employers (Fähnrich 2020, 3; Ramani 2009, 2). Science communication students must be prepared for the complexities of communication around increasingly contested topics that are rooted in science but have social, moral, or ethical dimensions and are often heavily politicized, such as climate change, biotechnology, stem cell research, and artificial intelligence. In addition, societal challenges such as science skepticism and dwindling trust in democratic institutions call for a critical ref lection on the relationship between science and society, as well as a new and more inclusive approach to knowledge production (Schrögel and Humm 2020). Students must therefore be equipped with competencies that will be required to navigate the controversies, uncertainties, and polarized debates around science and its applications in society.

Teaching in this field must also keep up with fast-evolving science communication ecosystems and landscapes, characterized by a general move away from mainstream media where journalists were the traditional gatekeepers, towards online and social media where everyone can communicate and comment on science (Fähnrich 2020, 1). Digital science communication channels are characterized by fragmented audiences, online hostility and concerns around mis- and disinformation, and social media may disrupt scientific standards and challenge the authority of science. Jointly, these trends demand a continuous reassessment of the theoretical and practical content taught within academic science communication courses.

In the 1990s, higher education and research institutions around the globe embarked on a journey of transformation toward fostering positive societal impact beyond economic goals. This ongoing transformation, ref lected by concepts such as *Third Mission* (Trencher et al. 2014) and *Quadruple Helix* (Carayannis and Campbell 2009), is accompanied by a shift toward a mode of knowledge production that surpasses the boundaries of established academic disciplines (Scholz 2020). Science communication is understood to be an essential and integral part of this process, as dialogue-focused and participation-oriented activities play a key role in knowledge and research exchange through engaging a wide range of stakeholders from outside the academic domain (Jensen and Gerber 2020; Leshner and Scheufele 2017). Scholars also point out that, following the idea of Responsible

Research and Innovation, participatory science communication – understood as joint knowledge production – can make a significant contribution to strengthening innovation processes, and to developing solutions to challenges that affect society as a whole (Loroño-Leturiondo and Davies 2018).

#### **Current forms of implementation in higher education**

Academic programs in science communication around the world share some common approaches and characteristics, but also significant variations in content, goals, learning outcomes, and delivery (Trench 2012; Trench and Bucchi 2021). This plurality originates from different national and institutional contexts, and the unique views of the individuals who champion these programs. However, despite the interdisciplinary nature and diversity of the field, it is argued that there are some core topics that should be covered in a science communication degree program (Longnecker and Gondwe 2014).

A number of handbooks related to science communication constitute evidence that the field is maturing and encompasses a range of core topics that should be considered by teachers in the field. These books provide a valuable starting point for curriculum developers and are useful guides for educators and students (Bucchi and Trench 2021; Jamieson et al. 2017; Leßmöllmann et al. 2020; Van Dam et al. 2020). In addition to the field delineation and guidance provided by these handbooks, several science communication scholars have generated ideas and topics for a core science communication curriculum (e.g. Baram-Tsabari and Lewenstein 2017; Bray et al. 2012; Mercer-Mapstone and Kuchel 2017). Further reports by scholars such as Costa et al. (2019), Fähnrich (2020), Gascoigne et al. (2020), Hong and Wehrmann (2010), Longnecker (2016), Longnecker and Gondwe (2014), and Massarani et al. (2016) have suggested several core topics to be considered when new science communication programs are designed. These include: (1) Social studies of science, including the history, sociology, and philosophy of science and science communication; (2) Media studies and communication science, theory, and strategies; (3) Behavioral studies, including persuasive communication; (4) Education studies and learning theories associated with informal learning; (5) Public participation in science and the co-creation of scientific knowledge, including citizen science; (6) Evaluation of science communication materials and projects; (7) Research methodologies relevant to science communication scholarship; and (8) Real-world experiences for students via industry placements or institutional internships.

Despite consensus on the value of agreeing on core concepts, experienced science communication teachers recognize that most science communication programs will not be able to include all these topics. They therefore advise curriculum designers of new programs to consider local needs and priorities carefully (Longnecker and Gondwe 2014). New degree programs in the field should be clear about their learning outcomes and strengths, and should use their uniqueness as a way to attract relevant students (Hong and Wehrman 2010).

Although science communication plays an essential role in transdisciplinary processes, there is little systematic research into the specific relationship between transdisciplinarity and science communication (Du Plessis 2012; Wang 2019), and only a few studies explore this question from the perspective of science education (Arber 1999; Mercer-Mapstone and Kuchel 2017). There is, however, a number of practical examples that illustrate the effective integration of transdisciplinary approaches into science communication courses. These include programs at the Karlsruhe Institute of Technology (KIT), the Universidad Nacional Autónoma de México (UNAM), and the University of Leeds. The latter offers joint honors degrees consisting of a STEM subject (e.g. biology or physics), instruction in history or philosophy of science, and an integrated research project in science communication (University of Leeds 2021).

Science communication has been an integral part of modern science for over 200 years and contributes significantly to the circulation and targeted exchange of knowledge between academia, politics, society, and business. Today, the presence of academic education in science communication is recognized as a key indicator of the maturing of the field and its associated infrastructure in different national and regional contexts. However, empirical research into the relationship between transdisciplinarity and science communication in the context of higher education is still lacking. Here, prospective studies might benefit from existing scholarship in neighboring areas, most notably in sustainability studies, and Research and Innovation.

#### **References**

*communication*, eds. LeeAnn Kahlor and Patricia Stout, 11–39. New York, NY: Routledge.

International Conference on Public Communication of Science and Technology (PCST), 6–9 December 2010. New Delhi: MK Patairiya.

## **Science Shop**

*Martine Legris and Frank Becker*

#### **Definition**

A science shop is defined as a collaborative space where communities, nonprofit organizations, researchers, and students work together to address socially relevant issues and problems (Frickel and Moore 2006). It emerged in this form in Europe in the 1970s, offering independent and participatory research support to civil society organizations (CSOs) willing to develop a research project in response to a particular concern.

A science shop is not a commercial shop, but an entry point into the university for anyone outside academia who is looking for answers based on a scientific approach to a problem. However, a single, uniform format that could easily be transferred does not exist. Some science shops operate as an integral part of a university, while others run as a social enterprise, an association, or a civics initiative. The members of a science shop – usually researchers, students, or academic staff and representatives of nongovernmental organizations (NGOs) – mediate the research process so that civil society, academics, and students become co-researchers or co-contributors. Two conditions quoted in the literature as criteria for science shop projects are: (1) The civil society organization does not bear the costs of the research; (2) neither the science shop nor the cooperating institution pursue commercial interests (Stewart 1988).

Research participation requires a collaborative approach among hybrid groups consisting of research professionals and civil society actors, such as NGOs, grassroots organizations, and residents. Members of a science shop act as mediators in the research process, enabling civil society, academics, and students to become co-researchers or co-contributors. Various stages of the research process require a form of cultural translation. Science shops support to translate civil society's concerns into research questions and provide participatory engineering. This mediation goes beyond dialogue or facilitation. The members of a science shop bridge gaps and create meaning where differences in vocabulary, experience, or knowledge make collaboration difficult.

Science shops depend on their context of emergence and are diverse in terms of the themes they address, the type of support they provide, their institutional position, and their governance. Nonetheless they share common characteristics. Based on a true co-production of knowledge between researchers and organized civil society actors, science shops produce the knowledge that democracies need to address today's social, health, and environmental challenges.

Civil society organizations reach out to science shops with an issue related to their activities, and the science shop, in return, provides support to partners throughout the research process, which typically occurs in several phases (Blangy et al. 2018). All phases involve both civil society organizations and academics, including students. The organizational process may differ from one science shop to another – depending on its institutional design, as science shops may be independent units or university-based – but it follows a common path: (1) gathering the request, followed by (2) translating it into a scientific issue, which is a critical point and the main added value of the support, (3) identifying an academic team to address the subject, (4) conducting the research work based on the co-production of knowledge, (5) returning the results to the actors and disseminating them widely, and (6) concluding with a ref lexive phase of research evaluation that enables the system's improvement. Today, more than 50 science shops and comparable intermediaries exist in Europe, Tunisia, and Canada (Living Knowledge 2023).

#### **Background**

Following a long tradition of public engagement in research, science shops are part of a movement to redress a divide that emerged at the beginning of the 19th century. This global divide separated the scientific and academic spheres from all other kinds of knowledge, whether experiential, know-how, or user-based knowledge, among others. The construction of a disciplinary structure of science and the belief in technical progress (Habermas 1970) led to a high specialization of knowledge, excluding lay people from the margins of scientific endeavor. However, a countermovement emerged to adapt scientific research to the needs of society rather than the other way around. Several crises and epidemics highlighted the need for a more inclusive and systemic approach to knowledge production (as argued by Morin 1992).

Although a historical overview of science shops does not exist, scholars (Fischer et al. 2004; Millot 2019) agree on decisive turning points. The first wave of science shops started in the Netherlands in the 1970s. The phenomenon then spread throughout Europe due to a positive political and institutional climate. In contrast, the 1990s saw the closure of many European science shops, and in the 2000s even the Netherlands witnessed the demise of several historic science shops. Only in 2010s were several new science shops established. In 2001, the European Union launched its Science and Society Program (European Commission 2001) to strengthen the societal impact of research. This program funded large research projects, which in turn triggered the rise of new science shops across Europe. Initially, a European network was established, today known as the *Living Knowledge Network*, which efficiently supports science shops in fostering public engagement and participation. Subsequently, many changes in the European governance of research have occurred. Some of them have favored the spread of science shops in European countries, such as the promotion of responsible research and innovation, participatory research, and open science (Rodriguez et al. 2013).

At the same time, a vision of technical democracy, or the empowerment of the public to participate democratically in scientific decision-making, emerged among researchers from different disciplines. This was partly due to the dramatic consequences of past scientific decisions, such as nuclear technology, genetically modified organisms, changes in occupations and jobs, and pollution (Beck 1992; Feenberg 1999). More recently, various trends and theories (Voorberg et al. 2015) have emerged (co-production, co-creation, etc.) to link different practices and methodologies, resulting in a semantic blurring. One remaining question concerns the new challenges science shops are facing. Rather than adapting to a new environment, and possibly reinventing themselves, science shops may initiate the cultural translation and the interdisciplinary process, while providing collaboration frames during the research projects. They also provide meta-analysis of the participatory dimension of the research and improve ref lexivity.

#### **Debate and criticism**

When addressing societal challenges through a scientific approach, the crucial question is whether the knowledge generated is relevant to the lifeworld solution of the problem at hand. This is facilitated by a non-reductionist approach to the problem and the contextualization of research. Science shops contribute to this development through their constitutive bottom-up approach. In order to remain relevant in research and society, it is also crucial to ref lect on their internal quality of intermediation and cultural translation capacity. If science shops are understood as a relevant link between civil society and science, the question of funding their cultural translation services between the logics of the science enterprise and civil society requires attentiveness. Interdependencies may arise from the forms of funding that affect both the interaction between society and science and the contribution of science shops to academic education.

Science shops find themselves in a difficult position between the need to find new social decision-making processes and the pressure of social closure move-

ments (Koppetsch 2019, 34). The tried and tested social negotiation processes of the past no longer seem sufficient to deal with the increased complexity of contemporary society (Latour 2018, 106). To what extent can or should the scientific community be experimentally involved in recent developments such as citizens' assemblies (e.g. Ireland) and major debates (e.g. France)? Phenomena such as populism (Inglehart and Norris 2016) can arise from the uncertainties resulting from the apparent mismatch between societal complexity and existing processing capacities, social closure movements, and tendencies towards greater hierarchization of societies. A reinterpretation and instrumentalization of the dialogical working principle of science shops can be the result. Science shops have to consider this essential aspect of the social ecosystem in which they operate. Such a ref lection is equally important for established (as in Europe and North America) and emerging (e.g. in Africa) science shops, as well as for students using science shops as an academic resource: What kind of funding supports a science shop? What decision-making processes govern the interaction between civil society and science? How are civil society representatives involved in the evaluation of outcomes?

In the environment of a university-based science shop, the claim of a university's Third Mission have gained in importance. Transfer, transdisciplinarity, and participation provide a limited ecosystem for academic activities of young academics seeking tenure. At the same time, the social closure movements mentioned above are leading to a change in the capabilities, function, and reputation of science shops. As intermediators, science shops are seen as boundary crossers and disruptive forces at the same time. Neoliberal trends such as "the top-down implementation of competition and market principles under the aegis of New Public Management (NPM) in higher education and science has led not to more but to less professional freedom for those concerned" (Koppetsch 2020, 18, own translation).

The contemporary benefits of science shops are linked to their capacity to deepen and enlarge their main mission. Climate change and major social events as Covid 19 (Latour 2018) request a systemic review of science shops' modus operandi. Six aspects can contribute to enhance collaboration on eye-level: (1) The research question or underlying problem may affect *individuals*. It requires major attention to clarify who are the people that are actively involved in the project. (2) Science shops involve *students* and universities need to develop specific curricula and procedures for them. (3) The *leadership* for the research project can be taken by anyone. To widen the circle of participants or co-researchers, outreach efforts can be made to individuals and groups who may not have been involved initially. (4) An intended *co-research approach* involves collaboration between different actors. This approach aims to facilitate the equal participation of all stakeholders and to ensure that the research is guided by their collective knowledge and expertise. (5) Research projects may involve both *research and implementation*. The balance between these two aspects will depend on the specific aims and objectives of the project. Action and research can be thought of in the same systemic perspective to avoid getting caught up in narrow perspectives that lead to poor experiments. (6) Science shops approach researchers and students to offer them fair cooperation with *nongovernmental organizations*. It is possible to use a transdisciplinary team even if students are supposed to belong to one discipline.

Although solutions to some basic challenges have been identified, embedding them to academic routines and organizational procedures has proved difficult (Schlierf and Mayer 2013). Two key challenges remain: First, research in general and participatory research specifically is often constrained by a lack of time, as co-producing knowledge requires significant time investment. Second, a shortage of human resources, partly due to a lack of institutional recognition and dedicated funding, hinders successful cooperation (Bammer et al. 1992; Legris 2012).

#### **Current forms of implementation in higher education**

For budding academics, science shops provide a hands-on learning environment. In universities, the ability to recruit and train academics and students in participatory research and knowledge co-production is crucial for the implementation of science shops in higher education. To achieve this goal, specific training programs are to be designed and integrated into the curriculum, with community-based learning or service learning being the most common form (Ferrari and Chapman 1999; Hyde and Meyer 2004). In independent science shops, links with higher education institutions are established through personal networks, European projects, hiring of undergraduate assistants, and other means.

Students involved gain new knowledge and skills from the process of conducting research on real-life problems. They become familiar with the concept and practice of social responsibility, enhance their professional standing, for example by publishing the research and participating in conferences. In addition, their dissertations serve a purpose. The results of their research are often used to bring about meaningful change.

Science shops provide students with a support system that they can turn to for help with any problems or questions that arise during their research. Nevertheless, students may find it difficult to meet academic standards. New communication and pedagogical skills are needed to deal with multiple stakeholders. In terms of students' experiences, Rao et al.'s (2004) analysis of students' reports suggest that not all of them benefited or were equally satisfied with the experience. Some said they had problems interacting with the community in the field; others did well in the field but had problems with the research itself.

The link between science shops and transdisciplinarity is two-fold: First, science shops engage in cultural translation by promoting ref lexivity in the collaboration between civil society and the scientific community. Second, they provide students with an opportunity to engage in negotiation processes on various levels, which they may not otherwise experience in their studies.

Science Shops appear as a mostly Western product of the dialog between science and society. Despite the lack of exhaustive survey, most of them are located today in Europe and Canada.

*Figure 1. Geographical distribution of science shops in 2023. Source: own illustration based on data of Living Knowledge (2023), SYNO (2023), and own research.*

A typology of science shops emerges from their organizational and institutional structure. (1) *University-based* science shops are the original form. In the 1970s, for instance, almost all Dutch universities maintained science shops that were fully integrated into the university structure (Dixon 1988). This integration provided them with stability. They were funded by the universities and other higher education actors. Today, this model is followed by the science shops of the University of Lille and TU Berlin, for instance. (2) A second group of science shops are *nongovernmental associations*, e.g. the Bay Zoltan science shop in Hungary. These institutions often charge for their services or apply for funding. (3) A third group of science shops belongs to the *private sector*. In France, for instance, science shops tended to be independent of universities (Dixon 1970), but they still relied heavily on public funding. Some organizations now accept requests from larger CSOs and commercial companies.

Two cases from Europe and one from Canada may illustrate the specific functionality of science shops.

In conclusion, the main outputs of science shops include the democratization of expertise, the co-creation of knowledge between researchers and communities, and the promotion of social justice and sustainability (Frickel and Moore 2006; Wibeck et al. 2022). Through science shops, community members, students, and researchers work together to develop research projects aimed at creating social change and promoting democratic, equal, and participatory practices Overall, science shops need to face many challenges while maintaining their inner characteristics favoring the common public good and peer-to-peer relationships.

#### **References**

## **Scientific Knowledge**

*Hildrun Walter and Kerstin Kremer*

#### **Definition**

Scientific knowledge has gained renewed attention in the so-called knowledge-based society today. Challenges and crises highlight the question of what scientific knowledge is and what science can achieve. Especially in inter- and transdisciplinary contexts, one should be aware of the potential of scientific knowledge, but also of the reductionism inherent in a scientific approach.

Defining what scientific knowledge is, what it means when someone claims to know something based on evidence and what this knowledge implies, is part of scientific and philosophical ref lections. These questions that originated in ancient Greece were discussed by numerous philosophers, such as Aristotle, Bacon, or Popper, thereby developing the rules of what is today accepted and applied as a scientific approach. Therefore, knowledge acquired via adhering to these rules must be accepted as scientific knowledge (Kuhn and Vessuri 2016, 11).

The term *scientific knowledge* has, regarding its etymology, a double name. *Knowledge* is an Old English word describing the fact of being acquainted with a thing or a familiarity gained by experience (Oxford University Press 2022a). The attribution *scientific* relates to the Latin *scient-*, *sciēns*, present participle of *scīre*, which means "to know", so knowledge as opposed to belief (Oxford University Press 2022b).

Scientific knowledge is gained via a specific process which adheres to the conditions of science, here used in the embracing notion including non-empirical sciences such as mathematics, law, philosophy, linguistics, and history. The UNESCO (2018, 5) defines science as the

enterprise whereby humankind, acting individually or in small or large groups, makes an organized attempt, by means of the objective study of observed phenomena and its validation through sharing of findings and data and through peer review, to discover and master the chain of causalities, relations or interaction; brings together in a coordinated form subsystems of knowledge by means of systematic reflection and conceptualization; and thereby furnishes itself with the opportunity of using, to its own advantage, understanding of the processes and phenomena occurring in nature and society.

There is no final definition of scientific knowledge, the term is still frequently discussed within and between different scientific disciplines. It encompasses empirical, theoretical, and hermeneutical approaches towards a systematic knowledge acquisition. However, researchers and students should be aware of the various conceptions of knowledge implied in different scholarly cultures. Within transdisciplinary learning contexts, the different cultures of knowledge provide the potential for a more holistic ref lection, and therefore more comprehensive understanding. Persons who intend to collaborate in a transdisciplinary research project or educational task should ref lect on and communicate their sources of knowledge, its reliability, and limitations. Conscious discussion may enhance mutual understanding for different approaches, documentation, and methodologies in scientific knowledge acquisition and therefore may prevent possible misconceptions (Pohl et al. 2021, 18–19). In addition, this ref lection may help to identify common points of contact and complementary additions to the various disciplinary levels of knowledge, thereby enhancing mutual learning.

### **Background**

The conception of scientific knowledge and how scientists gain knowledge is part of epistemology. Epistemology deals with the origin, nature, and limits of human knowledge (Stroll and Martinich 2022). Philosophers, historians, and science sociologists contribute to the subject. The modern scientific system can be divided into three areas.

First, science as a *system of knowledge*. Scientists use terms to specify the origin, conditions, and reliability of statements. They differ between hypotheses – tentative explanations that need to be tested by further investigation; scientific laws – statements that describe the relationship between certain variables under given conditions; and theories – well-substantiated, overarching explanations of natural phenomena. Further, scientific knowledge is classified using disciplinary typologies, grouping items or concepts based on commonalities they share, like the taxonomy in biological classification. These typologies are developed by scholars forming a thought collective (Fleck 1979, 99), which means that they share a framework of ideas, cultural customs, and experiential knowledge.

Second, science as an *organized process*. In their research, scholars apply different methodological approaches including empiricism, analytical methods, and hermeneutics. Empiricism involves careful observation, applying rigorous skepticism about interpretation of observations. It involves formulating hypotheses via induction, experimental testing of deductions and refinement (or elimination) of the hypotheses based on the experimental findings. Not all steps take place in every procedure to the same degree and in the same order. Researchers use analytical methods to reveal type, structure, and function of an object by breaking it down into its components and describing their relationships on a theoretical basis. Hermeneutics describe the theory and practice of interpretation. It ref lects the nature, scope, and validity of statements, for example, inherent in texts or observations. Thereby, it can help an understanding of how problems are defined and situate them in a societal and historical context.

Third, science as *cultural achievement*. Scientific knowledge is organized in institutions with specific rules and values, and with a societal role and responsibility. For Europe, this culture has its origins in ancient Greece and, through knowledge exchanges, such as e.g. with the Arab world, has developed over the centuries into modern science as we experience it today. Science in the scholarly sense described above is today applied universally.

The history of scientific knowledge is complex, and a multitude of perspectives and notions exist. However, it is possible to highlight key developments that have led to the emergence of the modern science system. The Greco-Roman ancient world represents a distinct cultural area that produced significant scientific advances and is today regarded as the cultural origin of European science traditions. The first period of scientific history in ancient Greece was characterized by developments in research methods, the formation of rules and systematization, the observation of the course of diseases or the study of order in nature (Merlin 2014, 16–21). Natural philosophers from this period, like Socrates, Plato, or Aristotle, engaged in the earliest known forms of what is today recognized as rational scientific knowledge acquisition. Aristotle's inductive-deductive method used a cyclic process of inductions from observations to infer general principles and deductions from those principles to check against further observations to continue the advance of knowledge systems. Based on Aristotle's work, in the Middle Ages the scientific systematics of scholasticism were developed including, for example, the work of Thomas Aquinas and William of Ockham, elaborating the proof of evidence via disputation (Marrone 2006, 32–37). Assertions were developed based on assumptions, which were then tested for arguments for and against this assertion with the help of logical considerations.

However, during the 16th century English humanists began to value practical knowledge more than solely theoretical consideration, thereby rejecting scholastic disputation (Gaukroger 2001, 6–15). The pursuit of practical knowledge was one major aim Bacon followed (Gaukroger 2001, 9–10, 101). With the help of his commitment to observation and experiment, empiricism became a central part in the reform of natural philosophy towards modern science. This era of scien-

tific revolution achieved "facts, principles, laws, hypotheses, and theories [being] subject to objective judgment in the light of empirical evidence" (Wenning 2009, 12). Furthermore, humanists, such as Nicholas of Cusa and Bacon, recognized the unique role of the researcher, which was a remarkable step in raising awareness of the cultural dimension within science and scientific knowledge. Bacon proposed rules of conduct for researchers, claiming the requisite of good sense and behavior in observation and experiment (Bacon 1620; Gaukroger 2001, 12). With his publication *Discourse on the Method*, Descartes is also recognized as pioneer of the development of modern natural science, especially for emphasizing the significance of doubt or skepticism as an essential attitude for scientific reasoning (Descartes 1637, part two).

In the 17th and 18th centuries, the development of more formalized processes of knowledge creation through empiricism or mathematical reconstruction led to an enormous increase in scientific data that had to be collected and ordered. The amount of available information increased the pressure to treat data selectively, depending on scientific criteria. Furthermore, experimental settings allowed scholars to construct their research around specific subjects and phenomena. Scholars communicated concepts and methods that were more specific to these subjects, finally leading to specialized journals and communities. Through this specialization, the disciplines in the modern sense emerged around 1800. They became institutionalized in scholarly associations and universities. This further structured knowledge formation and conception, its distribution in research and teaching, and its application. The enormous growth of science stimulated by the disciplinary development forced the system to further structuring and internal differentiation, and, therefore, to a multiplication of disciplines. Scholars had to focus their attention on a specific field, thereby leading to an increase in specialization. Although the loss of scientific unity was perceived by scholars themselves, it was not until around 1970 that public attention to environmental protection and technological developments fueled the debate on inter- and transdisciplinarity (Weingart 2010). The previous accumulation of knowledge and techniques within delimited disciplines now allows complex problems to be viewed from different perspectives.

#### **Debate and criticism**

The major challenges facing society today are characterized by a multi-layered nature and complex underlying causal chains. Their complexity does not allow for solutions developed within one discipline (Mittelstraß 1987, 154–55), despite the profound stock of disciplinary knowledge available. Researchers need to unify different knowledge perspectives in order to address these challenges in a transformative manner. While the natural sciences can provide insights into laws and relationships, the humanities can offer ref lective perspectives and elucidate the cultural embeddedness of observations. Transdisciplinary research thereby represents a complement to disciplinary research, not a replacement. It builds on multidisciplinary research, so addressing the same problem within different disciplines, and by final sharing of results, it combines findings within a common context. It also builds on interdisciplinary research, which means a close interaction between different disciplines in terms of transferring methods and knowledge at an early stage, as well as close cooperation throughout the research process. Furthermore, transdisciplinary approaches also often involve societal actors to integrate their knowledge and perspective (Lawrence et al. 2022, 44–48). A successful integration of these different types of knowledge and practices in such collaborative processes can lead to mutual learning, a more holistic perception of issues, and synergistic, innovative approaches in searching for solutions to societal problems. This integration can only be achieved when the scientists themselves become aware of the properties of disciplinary knowledge, the processes of its development, and its boundaries. Higher education should therefore help to ref lect the relevance of mono-, multi-, inter-, and transdisciplinarity to complex problems. Teachers and students should become aware that many disciplinary perspectives exist and that they are not static, but are evolving based on progress in their own as well as in other disciplines (Vereijken et al. 2022, 6). The comprehension of basic scientific concepts and a solid understanding of the epistemological characteristics that are part of disciplinary knowledge are essential baselines for transdisciplinary problem-solving. Here, the concept of Nature of Science could serve as an example for educational implementation.

Nature of Science encompasses an understanding of the epistemic, historical, social, and cultural reach of scientific knowledge as well as an understanding of scientific reasoning and methods. It further ref lects the values and norms to justify scientific claims (Heering and Kremer 2018). Since the 1960s, Nature of Science was increasingly taken up by science educators and was then central in the debate from the 1990s (Heering and Kremer 2018, 105; Lederman et al. 2002, 498). Communicating the overarching ideas in science that hold true in several disciplines are today seen as superior outcomes for science education (Lederman et al. 2013, 138–39). One educational aim within Nature of Science is to convey that "scientific knowledge is tentative, empirical, theory-laden, partly the product of human inference, imagination and creativity, and socially and culturally embedded" (Lederman et al. 2002, 499). The authors furthermore underline the importance of teaching the distinction between observation and inference, the lack of a universal method within science, and the functions and relationships between theories and laws in science. Scholars from different disciplines, however, still controversially discuss conceptions of Nature of Science.

Today, educators all over the world accept the comprehensive understanding of Nature of Science as a goal to be achieved in the science classroom and informal educational settings (Allchin 2011, 519; Lederman et al. 2013, 138). Several studies investigated how the explicit ref lection of Nature of Science during education supported its understanding, whereby longitudinal studies showed only short-term gains (summarized in Cullinane and Erduran 2022, 2). Alternatives to the rather general "consensus view" of Nature of Science (Lederman et al. 2013, 138) were discussed. Allchin's (2011) "Whole Science" framework highlights dimensions that shape the reliability of science, so that students are empowered for personal and public decision-making. Erduran and Dragher (2014) presented their "Family Resemblance Approach" that provides perspectives on similarities and unique differences of the discipline-specific Nature of Science, such as for chemistry, physics, and biology.