Introduction

Amid rapid sociotechnical transformations and escalating global challenges such as Generative AI, poverty, workforce disruptions, and human and environmental health, there is a pressing need for educational programs that equip students with critical skills and competencies to navigate and influence complex postdigital realities. Societal issues, evolving in unanticipated scales and kinds, have challenged the way students gain and apply knowledge across disciplines, demanding that educational institutions reflect real-life practices that are increasingly non-standard and cross-boundary. Yet, the prevailing disciplinary and interdisciplinary learning models of higher education have been limited in fostering reflective practice across boundaries.

To this end, the purpose of this paper is to develop a new learning framework and explain, in theory and practice, how the learner might move across traditional disciplinary and professional boundaries through reflective practice—i.e., enhancing the intuitive performance of day-to-day actions by examining one’s experiences and actions to inform subsequent actions (Schön 1983). Reflective practice has traditionally been applied within disciplinary contexts or specialized professional settings in a single field (e.g., nurses, teachers, toolmakers). Surveying the historical shifts and the limitations of discipline-based educational models—disciplinarity and interdisciplinarity—this paper explores how reflective practice might be reimagined to support emergent, fluid, and contextual problem-solving across domains. Following transdisciplinary theories and ethos, yet evolving towards a more practically actionable framework, it proposes Challenge-Based Reflective Learning (CBRL). Through the development of CBRL, this paper advocates for a new kind of expertise necessary to navigate present and future postdigital complexities.

CBRL shifts the purpose of learning from content-oriented (i.e., content as a final product of learning) to context-driven learning (i.e., the process of learning which embraces at its core that context can fundamentally alter the relevance of a problem). We demonstrate that reflective practice is conducive to advancing transdisciplinarity, as its emphasis on context and practice helps students find paths to gain the necessary knowledge and skills within specific challenge spaces. Based on this vision of education, our proposed framework engages students with contextualized, sociotechnical challenges in ways that intentionally and progressively draw in multiple perspectives and domain areas to enhance their knowing-in-practice.

Originating from the University of Southern California (USC) in the United States, the CBRL framework has been designed and implemented within an innovative school that integrates technology, art and design, and business and entrepreneurship: the Iovine Young Academy (IYA or the Academy). While IYA’s CBRL focuses on the intersection of these three areas, producing emerging challenge spaces such as extended reality (XR), product innovation, design strategy, and transformational AI, CBRL is adaptable to integrated programs focused on other interconnected domains—e.g., participatory wellness involving policy, healthcare, and medicine. Thus, IYA’s case study offers a roadmap for operationalizing transdisciplinary learning across domains.

This article proceeds as follows. The subsequent section lays out the background to understanding the emergence of postdigital complexities leading to different types of learning frameworks as well as the key concepts involving the proposed framework. The second section, ‘Review of Literature’, is composed of four subsections, surveying the disciplinary, interdisciplinary, and transdisciplinary models in relation to the reflective practice tradition, as well as the challenge-based reflective approach. The third section conceptualizes the CBRL framework by outlining its four interrelated layers of learning. The fourth section shares the case of at IYA at USC as an illustration of CBRL’s practical implementation by explicating its curriculum. The discussion section then connects CBRL back to the broader reflective practice and transdisciplinary scholarship, highlighting its implication for envisioning what it means to cultivate expertise in a complex postdigital landscape. The paper concludes by discussing remaining questions and suggesting future work on how CBRL might be further developed and adopted.

Background: Postdigital Complexities and Conceptual Definitions

New technologies are rapidly integrated into work processes and workplaces, demanding relevant skills that would better respond to massive global employment shifts, the automation of tasks across all industries, distributed work, and cross-cutting innovation (World Economic Forum 2023). These shifts raise questions about how people might leverage their uniquely human abilities to tackle complex, evolving challenges alongside new intelligent machines. A spectrum of positions exist regarding the potential of generative AI, or its augmented counterpart (Peters et al. 2019b). On the one hand, some raise concerns about how AI-generated technologies may displace workers who are unable to keep pace with emerging innovations (Frey and Osborne 2017). On the other hand, others see that as repetitive tasks become automated, more opportunities will emerge for leveraging human ability to engage in more complex and tacit activities, leveling the gap between high and low skilled workers (Brynjolfsson et al. 2023).

Between this spectrum, postdigital scholars have revealed more nuanced views of the relationship between technology (AI in particular) and human work, and its linkage with education (and teaching and learning) and work landscape (Jandrić et al. 2023; Peters et al. 2019a; Moradi and Levy 2020). These studies point out the broader issue raised in global and national policy reports (OECD 2023; McKinsey Global Institute 2021; World Economic Forum 2023; The Workforce Board 2019): that people are expected to gain unusual and complex combinations of advanced skill sets. The World Bank Group (2019) report states, ‘a marketing professional might well be called upon to write algorithms. A physics graduate may land a job as a quantitative trader in the finance industry’. Since students will enter work in new jobs and functions that currrently do not exist, these reports highlight the importance of nurturing cross-functional skillsets. To do so, they suggest enhacing cross-industry, multi-sector collaboration and partnerships, and incentivizing lifelong learning needed for cross-boundary learning and collaboration (World Economic Forum 2016).

The fragile and unconventional linkage between work and education cannot exclusively be addressed through existing learning models. For instance, preparing students for the unforseen future of work does not happen by simply switching degrees or obtaining an additional degree. Disciplinarity has often failed to capture the multidimensional complexity emerging from the postdigital convergence between science, technology, and society, insufficiently supporting students in developing the adaptability and complex thinking needed (Darbellay 2019; Ashby and Exter 2019).

Efforts to address these issues have led to alternative forms of collaboration between fields, via interdisciplinary and transdisciplinary models (Jandrić and Knox 2022). Conceptual distance exists between inter- and trans-disciplinary models (Jandrić and Knox 2022; Darbellay 2019; Ashby and Exter 2019; Collin 2009; Gao et al. 2020; Klaassen 2018), developed through their ‘complementary and antagonistic relationships’ (Darbellay 2019: 96). Without seeking to establish a taxonomy in this article, we guide readers to further conceptual clarity in the literature (Nicolescu 2010; Jandrić and Knox 2022; Darbellay 2015, 2019; Klaassen 2018).

  • Interdisciplinarity involves ‘studying one research question within an integrated system mode of various disciplines’ (Jandrić and Knox 2022: 10). It moves beyond merely juxtaposing disciplinary viewpoints to collaboratively engage the constituting disciplines in the ‘joint production of knowledge’ (Darbellay 2015: 166). It is still anchored in specific disciplinary traditions, focusing on ‘transferring or borrowing’ methods as well as ‘hybridizing or bridging’ mechanisms between (inter) disciplines (Jandrić and Knox 2022; Darbellay 2015).

  • Trandisciplinarity implies ‘a gathering of various research approaches around a common problem, which transforms “original” research methodologies arriving from each discipline’ (Jandrić and Knox 2022: 10). Nicolescu (2010) suggests that it is achievable at a higher conceptual plane of commensurability where new frameworks are created. Some emphasize dialogue among social, political, and economic actors and ordinary citizens in the research process (see Zurich's approach in McGregor 2015).

Yet, these models of integrated learning—models that aim to combine subject areas of different disciplines into an integrated whole (Gao et al. 2020)—have been limited in equipping learners to address complex and unanticipated issues, because they have been primarily applied as an extension of disciplinary learning. A central challenge is enabling learners to explore the world by ‘transcending’ disciplinary boundaries, while simultaneously navigating the ‘disciplinary organization of academic institutions that for now retains its dominance and its prevalence’ (Darbellay 2019: 101). To create more diverse ways in which students engage with postdigital complexities, there is a need to develop and test a new learning framework to prepare students with different kinds of expertise—beyond disciplinary expertise.

Against this backdrop, the postdigital community has posed a key question: What is the function and purpose of education in a postdigital age where continuous sociotechnical and employment shifts are expected (Peters et al. 2019b)? As Biesta (2020) states, education is not oriented toward a single purpose. Developing new models begin with redefining the purpose of education to consider other values neglected in the existing educational landscape: to enhance students' expert performance (i.e., knowing in practice—indicating action, practice, and doing (Orlikowski 2002; Polanyi 1967)) in handling complex, diverse experiences.

From this purpose, learning begins with real-life challenges that are relevant for the learner and unique to their practical interests across complex domains. In this paper, the word domain is used to contrast with disciplinary knowledge to denote abstracted knowledge (e.g., design strategy, communication, computation) or cross-cutting themes with strategic focus (e.g., cybersecurity) (adopted from Goodyear et al. 2023). The incorporation of knowledge across diverse domains allows for tackling a very particular challenge relevant in a particular point and place in time. In essence, CBRL facilitate the learner’s continuous movement between ‘noisy’ challenges of the world and relevant domain knowledges involved, leveraging the rich interplay between domain-general competencies and domain-specific skills. The result is the translation of reflective practice into a new kind of expertise focused on the process of addressing the ‘meta-convergence’ (between biology, science, information, technology, and society) (Jandrić and Knox 2022; Knox 2019).

Review of Literature

Constraints of Disciplinary Thinking in Fostering Reflective Practice

John Dewey (1933: 118) saw ‘reflective thinking’ as a means to confront an authentic problem, as it involves ‘active, persistent, and careful consideration of any belief or supposed form of knowledge in the light of the grounds that support it’. Since every experience is at least partially new, one goes through a reflective thinking cycle, transforming the experience into an iterative cycle of action and reflection (Kolb 1984). This reflective thinking cycle also depends on a double movement between deduction and induction, moving back and forth between meaning (inclusive and holistic) and facts (observed and specific) (Dewey 1910). It uses generalized knowledge across various experiences (e.g., domain-general competencies) to inform the understanding of specific components of new experiences (e.g., domain-specific skills and knowledge). Reflective thinking is more than processing experiences; it is also generative (Rodgers 2002).

Within the full complexity of rich life experiences (Dewey 1933), individuals move across these experiences and ‘confront the urgent challenges in our unequal, messy, data-driven societies beyond disciplinary boundaries’ (Poltze 2023). The human experience requires the ability to engage the suspended contradictions and the uncertainty of plurality and complexity. For example, the development of aesthetics relies deeply on the synergies of conflicting experiences (Vygotsky 1972). Many complex socio-economic events are not well fitted to deterministic analyses (Wells 2008). Recognizing this complexity inherent in the dynamics of knowledge has been central to the discourse that challenges the notion of disciplinary structures (Nicolescu 2010; Klein 2001, 2004a, b).

A disciplinary approach to learning offers an explicit and replicable way of understanding the world (Menand 2010). Disciplines systematize information, facilitating structured knowledge development, which supports ongoing contributions and gap-filling by others. Disciplinary curricula are organized into fixed learning paths—and these progress from elementary to more complex concepts (Ong 1983). Also, they are delivered through a scalable didactic pedagogy and, in many cases, tested through standardized tests (Cope and Kalantzis 2016). Yet, Dewey challenges the assumption that disciplines are collections of objective epistemic materials (Stoller 2018). Disciplines, instead, are value-laden ecosystems of social practices shaped by histories and thus limited in the approaches.

Disciplinary systems that aim for ‘consistency’ of processes and associated values and ‘certainty’ in solutions and outcomes may impede the ability of the learners to engage conflicting ideas and recognize gaps for innovation (Walsh 2020). When considering fields regarded as constituting stable and objective bodies of subject matter, the disciplinary methodology often becomes the goal rather than a means to an end. Symbolic math is regularly conflated with applied quantitative ability, even though depending on the person and the application, other forms of quantitative expertise (e.g., visual or non-symbolic methods) may be more effective (Grandin 2006; Van Herwegen et al. 2018).

The growing specialization in technical skills continues to evolve quickly. Combined with this, technologies create complex social and organizational structures, posing challenges for disciplinary learning (Johnson 2023). ‘Disciplinary codification’, which was essential for the organization and stabilization of subject-based knowledge, has become increasingly difficult. While technology increasingly dictates changes in work routines and systems, educational stakeholders find increasingly difficult to keep pace with growing subdisciplines organized by subjects and tools (Johnson 2023). New tools and techniques including Generative AI and Large Language Models also alter processes of learning and research, challenging disciplinary methodologies in dramatic ways.

Even though disciplinary knowledge is one way of facilitating human abilities, it has by now become almost coterminous with the idea of education itself. The notion of expertise is predominantly associated with disciplinary preparation. Disciplinary expertise promotes explicit, codified knowledge, formalizing and systemizing work processes and division of labor. The processes and methods for gaining relevant knowledge have remained rigid in higher education (Rich 2009). Consequently, learners are limited in their abilities to expand beyond their established areas of subject-based expertise. It overlooks other forms of knowing critical for tackling challenges that Dewey describes as democratic life and the reflective practices of inquiry crucial in diverse disciplines (Stoller 2018).

The ability to utilize one’s reflective capacity involves making learning meaningful across rich and diverse experiences and actions. Yet, theories of reflective practice have primarily been applied within single disciplines or professions, focusing on achieving professional artistry at work (Tan et al. 2023). Developing reflective practice suitable for the twenty-first century involves rethinking its application in today’s landscapes of work, technology, and education beyond its theoretical origins. The theory can be updated by investigating how people create novel configurations of heterogenous ideas and relationships, including the blending of the digital world with human experiences (Ball and Savin-Baden 2022).

Reflective Practice in Interdisciplinary Education: Persistent Challenges

There have been increasing efforts since the 1960s in exploring different degrees of interaction and integration of diverse disciplines (Klein 2010). Researchers have examined various collaborative approaches that create new ways to tackle complex societal challenges. They have also highlighted the role of interdisciplinary and transdisciplinary education in enhancing problem-solving across diverse fields, moving beyond the limits of traditional academic boundaries. Empirical studies have examined the design and assessment of such cross-disciplinary models (Dierdorp et al. 2014; Lou et al. 2011, 2017; Riskowski et al. 2009).

Interdisciplinarity emphasizes the synthesis of knowledge, methods, and processes from multiple disciplines to address problems that are too complex to deal with by a single discipline or profession (Knight et al. 2013). Interdisciplinary programs begin with well-established knowledge from specific disciplines and use it as a foundation to develop new, integrated fields. Integration occurs by identifying new combinatorial disciplines, such as bioengineering, chemical engineering, and even quantum cosmology (Nicolescu 2010; Ramachandran 2010). Discovering new disciplines through this process, the number of interdisciplinary majors grew by 250% between 1975 and 2000 (Knight et al. 2013).

Yet, interdisciplinarity often operates as multidisciplinary assemblages of discipline-based knowledge (Klein 2010). From a student’s standpoint, they are typically expected to first choose a disciplinary home while simultaneously building and gathering knowledge in a neighboring discipline. The integration of subject matters is left primarily up to the learner who often does not know how different disciplinary processes and knowledge might overlap (Howlett et al. 2016). Relying solely on the content-driven integration of knowledge can hinder students in effectively applying their expertise to novel contexts outside of known boundaries (National Academy of Engineering and National Research Council 2014). Successful interdisciplinarity is thus often limited to local interdisciplinarity—i.e., connectivity of neighboring disciplines (e.g., behavioral medicine, nanotechnology, bioinformatics) (Ashby and Exter 2019).

Many interdisciplinary programs are built on disciplinary roots that operate via a core question: How does a discipline fit to solve a problem? Common to the disciplinary approach, interdisciplinarity is driven by a content-oriented approach that dominates higher education. Subject-based content is both a product and a primary outcome of learning. Examples include mastering skill sets to design a chair or training to become a disciplinary specialist. Solely focusing on content also fixes methodologies, rendering learning process to be about ‘disciplining’ learners. The expectation is that the learner will produce an outcome imposed by a rigid curriculum or the methodologies of the involved disciplines, external to their personal learning experience. Jandrić and Knox (2022) point out this limitation, where specific en vogue methodologies (e.g., data science) dominate the learning process and collaboration.

Human learning and development are shaped by one’s daily experiences, actions, consciousness, relationships, feelings, and intentions (Johnson 2023). People learn by making sense of and transforming their experiences into knowledge—hence, learning by doing (Kolb 1984). As reflective practice engages with these experiences involving life situations, practice depends on one’s understanding of the context in which the practice occurs. Thus, reflective practice emphasizes learning as a matter of understanding, embodying, and navigating context, not as a progressive and linear accumulation of disciplinary knowledge. Reflective thinking processes involve noticing problems of interest, engaging in meaningful inquiry that incorporates subjective judgement and intuition, and experimenting with solutions across new application areas.

For cross-domain interactions to better consider the increasingly unstable and non-standard linkage between education and work, alternative framework might explore a path that moves beyond merely focusing on a set of subject-based knowledge that a graduate is expected to master to graduate (Thompson and Cook 2019). The complexity of a problem space should inform diverse paths towards cross-domain inquiry. This is done by enhancing students’ contextualized knowing while enabling them to handle diverse experiences that draw on various domains.

Transdisciplinarity as a Path Towards Cultivating Reflective Practice

The levels of cross-domain interactions are contingent upon factors such as problem selection, interaction levels, and alignment or dissociation among disciplines (Klaassen 2018). Depending on such factors, a program may explore a new approach that moves beyond disciplinary framing (Nicolescu 2002; Klein 2004a, b). Known as transdisciplinarity, these models can ‘metaphorically encompass the several parts of the material field that are handled separately by the individual specialized disciplines’ with the goal of understanding the present world (Nicolescu 2002 in Gao et al. 2020; Nicolescu 2010). Transdisciplinarity emphasizes the problem space, aiming to foster deep, authentic learning experiences of learners in understanding the real-world problems (McGregor 2017).

During the 1980s, educators diverged into two general camps, one emphasizing discipline or field-based learning that favors standardized assessments and the other promoting interdisciplinary learning (Rich 2009). The transdisciplinary movement offered a partial resolution to address this schism because it identified a path to examine cross-boundary interactions by highlighting higher-order thinking and skills (e.g., creativity, computational thinking, and problem-solving competencies). Transdisciplinarity also offered a ‘better route to methodological plurality than interdisciplinarity’ that tends toward a single set of assumptions and methods (Jandrić and Knox 2022: 11).

Differences exist in the two approaches within transdisciplinarity scholarship: the Zurich approach and the Nicolescuian approach. In dealing with complex real-world challenges, the Zurich approach emphasizes partnerships between diverse stakeholders and end users, including academics and non-academics (Klein 2001, 2003). Authentic knowledge interaction occurs when people with different ideas, frames of mind, and habits commit to the collective creation and expansion of new knowledge (Rich 2009). Yet, this approach has been critiqued for limiting transdisciplinarity within existing social constraints (Nicolescu 2010), which may revert interactions to discipline-based models. Solutions stem from science, aiming to improve scientific approaches to address societal complexity (McGregor 2015). The Zurich model focuses on joint problem solving where the goal is on the production of knowledge as opposed to the process of discovery, interpretation, and understanding (Nicolescu 2010).

Nicolescu’s (2010) approach leans towards process, placing the person at the center of the interactions within the environment. It offers a path to transcending the content-driven education and advancing towards learning as a discernment process, wherein individuals engage in their experiential practice to cultivate their unique disposition—developing their way of thinking, problem-solving, and relating to the world. Transdisciplinarity promotes an understanding of evolving realities by offering a more realistic and participatory learning process. From this standpoint, transdisciplinarity is beyond integrative (Evans 2019), as it considers both strengths and weakness of each field to identify a higher conceptual plane where different theories and methodologies can at least partially commensurate (Nicolescu 2008; Jandrić and Knox 2022).

Transdisciplinarity, however, remains conceptual without substantial practical development. Especially, it lacks clear connections to bridge the gap between fostering transdisciplinary ways of thinking and implementing practical mechanisms for integrating diverse forms of knowledge that are organized within disciplinary structures. Darbellay (2019) contends that failing to recognize the existing disciplinary organization can lead to an unproductive, ‘declare war’ scenario where academic tribes refuse any constructive dialogue that questions the exclusivity of disciplinary principles. Concerted efforts are needed to advance transdisciplinary models to a new level of practice, tested against real-world contexts.

Following the transdisciplinary ethos and recognizing its limitations, we present a novel perspective on how learners can develop the reflective practice essential for transdisciplinary thinking. Such a framework responds to Green’s (2022) challenge to surpass what Nicolescu (2010) called as ‘the war of definitions’ that exists within the transdisciplinarity scholarship. Our work, informed by our experiences in implementing CBRL within our institution, aims to advance towards the development of ‘an actualized praxis of transdisciplinarity’ (Green 2022: 689).

Fostering Reflective Practice Across Diverse Domains

Jantsch (1972) postulated that the integration of disparate knowledge domains and reconciling their contradictory elements require identifying a high-dimensional problem space. When one makes something (e.g., a wooden tool, a house, or a computer), the person learns about how to make that specific artifact. Yet, they also develop generalized design strategy abilities which can apply to the making other kinds of artifacts (Simon 1969; Auernhammer and Roth 2021). Similarly, every time the learner engages in a specific embodied task (e.g., playing sports, performing music, or conducting a scientific experiment), the learner builds insights—not only about the performance of the specific action, but also domain-general understanding of performing similar actions (Dourish 2004).

Both Dewey and Polanyi (1967) explain that embodied learning through personalized experiences and the development of domain-specific knowledge occur in parallel. Tsoukas (2003: 5), echoing Polanyi, explains that what makes ‘a scientist to use the formulae of celestial mechanics to predict the next eclipse of the moon, and a physician to read an X-ray picture of a chest’ is ‘skillful action’ achieved through the body. The learner applies skills which are not fully and consciously captured in terms of the particulars, but which can be skillfully performed (e.g., riding a bike, swimming). Thus, the reflective learner develops a domain-general understanding, informed by a series of related or even heterogeneous experiences involving performance and skills.

When the learner reflectively engages in diverse kinds of performances, intentionally in relation to each other, the skillful learner learns to interconnect diverse knowledge, linking the specific skills with broader human experiences. This serves as the backbone in what we define as Challenge-Based Reflective Learning (CBRL). The CBRL framework is built on the notion of tacit knowledge we gain from our daily life, while explicitly recognizing the rich interconnection between embodied reflective learning experience (the personal), the abstract knowledge gained through such engagements (the general), and the domain-specific knowledge that the learner gains from specific activities (specific).

The human ability to develop domain-specific knowledge in tandem with generalized abstractions has been documented through research in neurophysiology of learning (Desai et al. 2018). This is linked to our brain’s ability to learn in different ways at once and to apply and transfer knowledge flexibly (Badre et al. 2010; Eraut 2004). Learning scientists have proposed a layered learning approach. The top layer can relate to the embodiment of knowledge in real-world actions. This connects with the next layer, broad and general abstractions, which connects with detailed knowledge specific to a subject area, activity, or action (Carroll 1993; Tenenbaum et al. 2011). A key aspect of the CBRL framework is prioritizing the development of learners’ overall reflective abilities across diverse domains by focusing on the interplay of these learning layers. The learner’s movements across these layers foster the development of the learner’s unique disposition conducive to lifelong reflective learning.

For transdisciplinary approaches manifest tangible outcomes conducive to authentic cross-domain interactions beyond subject-based knowledge, programs can utilize novel practices aimed at cultivating learners’ reflection-in-action: ‘thinking about what we are doing when we are doing it with a view to making any changes needed during the event’ (Schön in Corrall 2017: 27). This concept differs from reflection-on-action (Schön 1983, 1987), retrospective reflection that deals with thinking on or about what one has done while evaluating the effectiveness of one's action (Corrall 2017).

Reflection has traditionally been understood in the context of a single, one-off experience detached from action rather than an overarching process of inquiry (Lundgren et al. 2017). For instance, many inter- or trans-disciplinary programs add separate reflective journal exercises into existing course activities as a way to enhance reflexivity (Bell et al. 2011; Corrall 2011). These approaches do not fully address the dichotomy between action and reflection (Freire 2000). They fail to capture how learners leverage their ability to ‘self-distanciate’ themselves from customary ways of acting to gain critical insight into their improved practice (Tsoukas 2009).

This limitation also echoes the restricted application of the theories of reflective practice within existing discipline-specific educational ecosystems. Fostering reflection-in-action enables learners and practitioners to reflectively monitor their assumptions, purposes, and the knowledges and interests entangled within existing boundaries. Enabling reflection-in-action, intentionally across domains, can lay a practical foundation for actualizing transdisciplinarity, allowing learners to iteratively experiment with different perspectives, action, skillsets, and solutions during skilled activities.

Challenge-Based Reflective Learning (CBRL): The Conceptual Framework

CBRL elucidates how reflection-in-action can be developed while understanding the mechanisms for integrating domain-relevant knowledge, skills, and competencies beyond learners’ familiar expertise. Informed by the work of Rikakis et al. (2020), the CBRL framework constitutes four interrelated multilayers of learning: Dispositions (i.e., overall life skills), Domain-general competencies, Intersectional expertise (i.e., cross-cutting problem spaces) and Domain-specific skills and knowledge (see Fig. 1).

Fig. 1
figure 1

The Challenge-Based Reflective Learning (CBRL) Framework, CC BY 4.0 

Full size image

Figure 1 displays an interconnected relationship between the four learning components involving the development of a disposition of productive inquiry (at the top of the learning layer image), domain-general competencies (at the second highest level), intersectional expertise (at the mid-level), and learner’s development of domain-specific skills and knowledge (at the lowest level). Arrows cycle between the layers indicating a level of fluidity between each layer. Next to the image are four boxes of text that further describe each learning layer.

Key Components of CBRL: The Four Learning Layer

Dispositions

CBRL underscores the central educational goal of fostering what Brown and Thomas (2008) call a disposition—‛a stance toward the world that inclines the person toward effective practice’. Dispositions are not simply attitudes, values, and worldviews. Dispositions, situated within the overarching dimension of the framework, are about propensity, or ‘what people are likely to do in particular situations’ (Brown and Thomas 2008: Para 2). Cultivating students’ unique dispositions of productive inquiry means that the learner builds their unique tendencies that support their meaningful inquiry. In CBRL, students achieve this by engaging with real-world questions that hold personal significance, reflecting what Biesta calls (2020) subjectification—taking the freedom to enhance or restrict capacities as individuals.

At the same time, the cultivation of disposition never occurs separately from the learner’s social experiences, or what Biesta calls socialization. CBRL emphasizes that students tackle challenges in collaboration with diverse stakeholders and other students who have different dispositions and strengths. This expansive socialization of complex problems cultivates dispositions and enables students to gain the needed knowledge and skills, thus achieving Biesta’s (2020) qualification of education—the provision of knowledge and skills.

The process of taking informed actions to address complex challenges situated across various domain areas is not predetermined. Learning that is angled toward reflective practice combines insights from both domain-general and domain-specific dimensions, with the goal of integration for purposeful action. This is best nurtured by providing students opportunities to collectively practice integrations within a learning environment designed for exploring challenge spaces that directly interest them.

Domain-General Competencies

CBRL emphasizes domain-general competencies that act as a bridge between reflective experiences and diverse knowledge areas. These competencies, like design strategy and abstract computation [i.e., extracting the quantitative relations of the key parameters of an experience (Simon 1969; LaViers and Maguire 2023)], facilitate knowledge transfer across experiences. This transfer is crucial for associating disparate elements of complex challenges and is developed in tandem with domain-specific skills (Carroll 1993; Desai et al. 2018; Rikakis et al. 2020).

Yet, knowledge transfer does not stem from codified disciplinary knowledge. Because knowing is inseparable from its constituting practice (Orlikowski 2002), the competence of skillful practice arises through ongoing involvement in specific tasks and social practices (Lave 1988; Suchman 1987). Biesta (2020) similarly observes that socialization provides learners access to practices and traditions that help them develop their identities. For learners to gain competencies across varied areas, they must actively participate in these social practices, aiming to grasp and bridge the mindset, norms, language, and habits of competent practitioners (e.g., software engineers, UX designers)—all involved in understanding the context of a challenge.

Such processes necessarily involve accepting plurality and disagreements in different domains (Nicolescu 2008), fostering socialization around the challenge being addressed. Curricula and pedagogy that suppoort cross-domain competencies enable learners to apply 'useful practices' (Orlikowski 2002) within a challenge space, facilitating temporary unification of contradictory ideas (Nicolescu in McGregor 2015). This approach aligns with CBRL’s objective to enhance expert performance across complex situations by intentionally exposing them to diverse perspectives, contexts, and languages involved in a broader challenge space. Beginning with the individual and social experience, as the impetus for reflective learning, the learner develops a new form of expertise that differs from traditional notions of disciplinary thinking.

Intersectional Applications Expertise

Postdigital challenges emerging from industry and societal needs occur at the intersection of technology, human experience, as well as specific applications, products, and tools that are tailored to domain areas and related fields (e.g., biotechnology, computational chemistry, AI and statistics in the arts) (Johnson 2023). Postdigital innovations across these intersections also require the understanding of evolving business models. Consequently, intersectional application areas are more fluid, emergent, and shaped by the changing societal, sociotechnical, and workforce trends and discourse (hence, real-world, challenge based). As learners develop and apply their domain-general competencies through real-world challenges, they can gain expertise at the intersection, gaining the reflective practice needed to address complex and multifaceted complexities.

Intersectional application areas are developed concurrently with domain-general and domain-specific knowledge and competencies. When the student learns to deconstruct a challenge across meaningfully chosen inquiry areas (e.g., design, computing, and business), the student can connect knowledge from one application area (e.g., e-commerce) with other domain areas (e.g., product innovation and extended reality). Mastery occurs when making integrative and applied responses to real-world challenges through a series of collaborative practice.

CBRL can be enhanced through a challenge-based learning cycle that begins with (1) discerning dimensions and perspectives of a challenge, (2) prompting relevant approaches and the knowledge needed, (3) prototyping to test ideas in action, and (4) iterating or pivoting based on experiences. This pedagogical process also involves the notion of tinkering (Bardone et al. 2024), where learners proactively respond to adaptive problems. By accounting for the inherent unpredictability of unique situations, they enhance their learning by leveraging the positive significance of chance events in-action.

Through iterative engagements in these challenge areas, students gain competencies to address them in similar intersections [e.g., business (from e-commerce), design (from product innovation), and technology (from extended reality)]. The learner’s mobility across these broader areas of domain enables the learner to cultivate what we call expertise at the intersection. CBRL posits that this intersectional expertise enables learners to move beyond conventional disciplinary expertise, allowing them to apply a broader set of domain knowledge and competencies across various and unknown challenge spaces.

Domain-Specific Skills and Knowledge

Domain-specific knowledge functions neither as the main goal of CBRL nor as a fixed pathway through which learners develop their competencies. With CBRL’s challenge-driven approach, the learner deconstructs and redefines challenges, ascertains needed information and resources, and pursues pertinent skills needed for the specific challenge being explored. CBRL emphasizes collaborative culture of learning where one can access necessary knowledge and resources through collaborative or self-directed efforts (Thomas and Brown 2011). The CBRL framework focuses on redefining challenges for innovative perspectives and solutions.

This differs from the goals of combining diverse knowledge for interdisciplinary outcomes. Unlike conventional approaches—where learners start by acquiring discrete skill sets and knowledge within a discipline, gradually expanding to interdisciplinary knowledge—CBRL begins with learners’ reflective engagement in real-world problems and their simultaneous engagement in skillful practices and social participation across multiple domain-general areas. During the practice of identifying, socializing, and addressing real-world challenges, students learn to identify the domain-specific knowledge needed and find ways to access or gain that knowledge. Consequently, CBRL reorders the conventional sequence of acquiring domain-specific knowledge and skills.

In sum, the Challenge-Based Reflective Learning framework aims to nurture reflective learners to move across the four learning layers to synergistically pursue real-life challenges beyond disciplinary boundaries. The next section illustrates how CBRL can be executed by sharing a case study where this framework has been developed.

A Case at the University of Southern California, Iovine and Young Academy

Case Context

In 2013, the co-developers of Beats, Jimmy Iovine and Andre ‘Dr. Dre’ Young, announced a 70-million-dollar gift to the University of Southern California (USC) for the creation of an innovative 4-year academic program, the Iovine and Young Academy (IYA). In 2014, IYA admitted 25 first-year undergraduate students as a part of its first cohort. In 2023, 53 students started the program, and by 2027, the first-year cohort is expected to reach 70 students, for a program total of 280 undergraduates by 2030. The school expanded in 2017 to include graduate students and in 2020 to include minors, totaling 200 enrolled graduate students and 250 minors. Upon graduating, students at IYA pursue a diverse range of positions in the workforce, particularly in technology and creative industries. Many have launched startups and student-driven ventures, garnering more than $120 million venture and development funding (IYA n.d.a, n.d.e).

Applying the CBRL Framework at IYA

Applying the CBRL framework, IYA’s overarching educational goal is to cultivate the learners’ unique dispositions to engage in diverse and productive inquiries across diverse challenge areas. IYA focuses on applications at the intersection of human-centric design (arts and design), technology development (computing and technology), and business transformation (entrepreneurship and business). Students are encouraged to incorporate their diverse interests in addressing societal challenges, through partnerships with relevant stakeholders ranging from small startups to large corporations, local and community-based organizations, academic and industry mentors, researchers, and peers. Thus, IYA admits students with diverse and complementary interests, especially those with creative traits that differ from students traditionally sought by other disciplinary programs (e.g., engineering or business majors). This aim uniquely shapes the IYA application process and recruiting practices (IYA n.d.b).

As illustrated in Fig. 2, the IYA curriculum is mapped in accordance with the four interrelated layers of CBRL indicated in Fig. 1: Dispositions, domain-general competencies, intersectional expertise, and domain-specific skills and knowledge. These four types of courses align with different phases of IYA’s challenge-based pedagogical model, designed to facilitate a cyclical process for innovation (See IYA n.d.c). Overall, the four arrows moving horizontally across a four-column grid represent the journey of an undergraduate IYA student navigating the CBRL curriculum.

Fig. 2
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The CBRL Curriculum at the Iovine and Young Academy, CC BY 4.0 

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Dispositional Core Courses

The dispositional core courses allow for students to engage in the challenge-based learning experiences and learn to understand, address, or redefine various societal issues. Most challenge areas explore innovations at the intersection of Technology, Design, and Business, but many also expand beyond these areas. The dispositional courses at IYA are:

  • Innovators Forum (1st year): Students gain an innovator’s mindset by ‘pitching’ ideas across diverse challenges provided by real stakeholders.

  • Design Strategy (2nd year): Students learn to think critically across intersecting areas—from business problems, everyday human needs, and resource constraints—through design strategy methodologies (IYA n.d.d).

  • Industry Practicum (3rd year): Students practice innovation from the perspective of engineers, designers, and entrepreneurs while solving field-specific problems.

  • Garage Experience (GX) (Final year, yearlong): Students develop innovative projects that lead to viable enterprises, operational prototypes, or a practical initiative for advanced research. Expert faculty and field specialists guide this capstone involving labs, demos, workshops, and critiques (IYA n.d.e).

  • Innovation Quest (Open to all students, yearlong): Students learn to grow entrepreneurial mindset to develop, accelerate, and scale their ventures. (IYA n.d.f).

Domain-General Core Courses

The domain-general core courses connect essential skills, language, norms, and perspectives in technology, arts and design, and business to the following domain general competencies: design strategy, interactive computation, innovation. These competencies are critical to intersectional applications across design, technology, and business. The domain-general courses at IYA are:

  • Dev I and Dev II: While learning the backend and frontend of interactive computing applications, students also learn to rapid prototype and iterate through user testing. These courses aim to develop competencies in computation and design strategy.

  • Rapid Visualization: While learning various design techniques and tools, students learn to think visually and translate their ideas into concrete visual forms. The course focuses on the abstract ability of visual thinking for developing design strategy.

  • Disruptive Innovation: While learning finance, accounting, and management fundamentals, students gain the entrepreneurial mindset needed to develop student-driven ventures. The course focuses on strategy and innovation management.

These courses help establish a shared language for all IYA students and expectations for cross-domain collaboration. They serve as an intermediary, helping to translate intersectional applications expertise and domain-specific knowledge into overarching reflective and life skills.

Intersectional Application Areas Courses

The intersectional application areas courses help students create functional prototypes in relevant industries that require a combined application of technology, design, and business skills. For example, the Transformative AI course teaches students how to design for inclusive sociotechnical transformations and meet the needs of specific groups and communities. The course takes a challenge that society faces and build solutions using AI, rather than starting with building tools and looking for a way to apply it. Students choose their courses from seven intersectional areas, such as Augmented Intelligence, Extended Reality, Health Innovation, and Product Innovation. These areas within CBRL may shift over time, depending on the focused domain-general competencies and relevant industry and societal demands.

Domain-Specific Areas Courses

Lastly, the domain-specific areas courses represent free electives to pursue domain-specific skills relevant to various challenges that students pursue throughout different courses, activities, and the program at IYA. Students can take courses across diverse departments on campus, such as Medicine, Law, Engineering, and Cinematic Arts. They also collaborate with others to engage in special projects at these schools or IYA. Since CBRL reorders the conventional sequence of acquiring domain-specific knowledge, students work with faculty to determine the appropriate domains and levels, access relevant courses, and find needed experts for collaboration.

Observed Outcomes of CBRL at IYA

Based on data from the past six years, the CBRL framework implemented at IYA has resulted in significant promise in integrating reflective and transdisciplinary learning, with applied learning and career outcomes desirable in today’s workforce needs. Since 2018,

  • 86% of the Academy graduates are employed within three months after graduation, joining companies in various sectors, especially in tech and creative industries (e.g., Apple, Blizzard, EY, Harlem Capital, Google, Volvo, Meta) (n.d.e).

  • Many Academy graduates are hired in strategic positions where they engage in sociotechnical problem solving and designing (e.g., digital strategy senior consultant, augmented reality (AR) engineer, XR designer).

  • The five-year graduation rates are 95%, with approximately 8% of graduates launching startups with external funding secured (n.d.e).

Discussion

The increasing societal transformations have advocated for nurturing reflective human capabilities involving creative and divergent thinking (Evans 2019). Such a discernable movement has been demonstrated in this paper by outlining the historical shift from traditional discipline-based educational models towards emergent, fluid, and contextual problem-solving (Klein 2015). Yet, existing mono-, inter-, and trans-disciplinary models have fallen short in cultivating reflective practice needed to navigate what Jandrić and Knox (2022) call ‘techno-scientific convergences’. Following the transdisciplinary ethos while addressing its limitations associated with the lack of actualized praxis in transdisciplinarity (Green 2022), the proposed framework demonstrates how learners can leverage their reflective abilities across domains to generate new meaning out of complexity, addressing unknown and evolving scenarios of the future.

Reflective practice theories show how new meaning emerges at the intersection of personal and embodied experiences, and environmental influences that shape these experiences. Since these theories were developed within the confines of traditional disciplinary education and specialized professional contexts, they have not fully addressed how to foster reflective thinking in postdigital settings. Reflective practice, when understood in relation to domain-general and domain-specific competencies and knowledge grounded in everyday action, offers a new path to seeing and addressing postdigital complexities beyond a discipline-bound methodology. It offers a new method for understanding ‘messiness and unpredictability’ in and for postdigital times (Jopling 2023: 155).

CBRL establishes the practical base for transdiscplinarity through reflective engagement in action. By deconstructing and redefining problems across various domains, students delve into complex problems and inquires, creating new connections between areas of thought, technology, people, and broader sociotechnical systems (Fawns et al. 2023). CBRL at IYA enriches the interplay between personal experience, sociocultural structures of knowledge, and intersectional expertise centered around emerging technologies.

CBRL contributes to the postdigital transdisciplinary scholarship by reimagining how one may engage domain knowledge across boundaries in a dynamic, challenge-based inquiry process. Transdisciplinarity recognizes what Gibbons et al. (1994) call Mode 2 knowledge (as opposed to Mode 1, disciplinarity): contextualized and heterogeneous knowledge. Yet, transdisciplinarity necessarily needs to consider ‘the epistemological framing of disciplines themselves, framing that points to the strengths and weaknesses each field can bring to addressing a given issue’ (Evans 2019: 70). This is achieved by contextualizing the challenge space and utilizing domain-general competencies that can act as what Nicolescu (2010) described as the ‘the included middle’: a bridge between reflective dispositions (process) and diverse forms of domain-specific knowledges (specific skillsets), enabling learners to apply prior experiences to new situations.

By seeing problems at the intersection of multiple domains (in IYA’s case, technology, art and design, and business), students can navigate and utilize multiple realities and contradictory ideas inherent in the real world by temporarily uniting them (Nicolescu 2005 in McGregor 2015) within a challenge. CBRL’s reflective learning model prompts learners to critically assess assumptions and redefine problem areas, promoting a shift from static content-driven models towards a plurality of new thought styles (Darbellay 2015).

CBRL explores various transdisciplinary research and pedagogical methods, as called for by Peters et al. (2019a). It does not aim to teach people how to solve certain types of problems, because of its core educational focus on dispositions. Thus, it eschews a product-based (knowledge as commodity) model of education, embracing vulnerability and uncertainty needed in postdigital education—being open to uncertainty in addressing a problem and ‘developing a reflective approach to teaching’ (Jopling 2023).

CBRL’s methodology is indicative of a shift towards a postdigital economy, where teaching, learning, and professional development are intertwined within the fabric of academia, industry, and society at large. While seeking to help students build their dispositional capacities to develop their personalized and adaptive learning trajectories spanning sectors and domains, it also seeks to reconfigure and transform the social systems related to the organization of academic institutions and its knowledges. This involves maintaining a position at the intersection, embracing the overlap between interdependence of different combinations and perspectives. It moves towards a resilient, lifelong learning ethos of transdisciplinarity emphasizing collaboration and iteration across boundaries.

Recognizing that expertise can be developed across diverse domains, CBRL helps reevaluate what it means to gain expertise beyond the confines of disciplinary and professional norms. Expertise has predominantly been associated with being a specialist in a particular field, generating distinct professions (e.g., physicians, lawyers, and engineers) (Hardoš 2018; Heimstädt et al. 2023). However, this notion does not recognize other kinds of expertise that may complement or expand beyond disciplinary or interdisciplinary framings. Discipline-bounded education does not produce all forms of expertise; therefore, reflective and transdisciplinary competencies need to be enacted to prepare students for an unforeseeable future. CBRL thus offers alternative avenues to disciplinary and interdisciplinary models, cultivating expertise that can support other forms of innovation at the intersection, helping individuals and groups better respond to the ever-changing and cross-cutting uncertainties of postdigital times.

An expert, in this sense, is a reflective practitioner who draws on a repertoire of context-specific problem cases across diverse areas of knowledge (Rolfe 1997) while building what Tauritz call ‘uncertainty competences’ (Jopling 2023: 164). The expert moves intuitively across diverse and unknown situations, embracing vulnerability and applying a body of personal, tacit knowledge along with a repertoire of past experiences to inform future practice. The reflective practitioner translates knowledge into practice in whatever situation they find themselves across different areas (Rolfe 1997), moving beyond the boundaries of knowledge in ways that are unanticipated.

Conclusion

This paper has explored the limitations of viewing disciplinary, interdisciplinary, and transdisciplinary models as complete educational paradigms for the twenty-first century postdigital world. Grounded in the reflective practice tradition, we introduced Challenge-Based Reflective Learning (CBRL) with the aim of reimagining the purpose of education: to enhance reflective practice necessary for learning across intersected and uncertain domain areas. We have demonstrated that such an aim can be practically operationalized when a learning framework acknowledges the interrelationships between one’s expert performance and the cultivation of domain-specific and domain-general skills and competencies, along with the development of expertise at the intersection realized within real-life challenges. We contend that education in postdigital times should focus more on guiding students to gain and apply knowledge as resources for future and unknown contexts, reshaping it to meet new demands and situations (Brown and Thomas 2008). This approach also values personal judgement, embodied action, and the embracing of uncertainty and plurality, which are essential for navigating the complexities of postdigital times (Jandrić et al. 2023).

Limitations and Future Work

Caveats concerning the CBRL framework warrant attention. First, to enact a transformative framework like CBRL, more agencies need to be given to students, teachers, and researchers to envision new educational, technological, and vocational futures (Peters et al. 2019a). Pedagogical innovation and philosophy are closely tied with institutional design, leading to issues of agency, power, and control. While these issues were not discussed in this paper, we recognize that promoting pedagogical innovation and advocating for broader educational reform require a critical examination of underlying organizational structures, practices, and norms. Reflecting on our decade of experience in applying the CBRL framework at our institution, a helpful study could highlight opportunities and challenges of navigating the complexities of institutional change. Bossio et al. (2014)’s reflective self-study discusses complex and politicized interactions involving interdisciplinary education. Such studies can reveal cultural and organizational complexities. Other approaches such as critical and historical discourse analyses examine deeper logics of institutional structures, questioning the goals of educational reforms (Schneider 2019; Hayes 2019).

Secondly, the framework was developed and evaluated within the context of a well-resourced, research-intensive university in North America. This environment may differ from that of other institutions, leading to varied applications and challenges of the framework in different settings. Our ongoing empirical investigation focuses on assessing CBRL’s adaptability to diverse student populations, particularly in underserved communities within our local urban settings of the greater Los Angeles area. We evaluate its applicability in high school and after-school programs. Working with high school teachers and administrators preparing to launch new schools that adopt CBRL, we are observing significantly different challenges faced by their students—such as food and security.

These inquiries prompt us to consider what support is needed when CBRL disrupts the traditional learning sequence. Future research should explore how transdisciplinary reflective practice engages students of diverse backgrounds and needs. Postdigital critical pedagogy emphasizes the role of education in fostering equity, dialogical approach to learning, and horizontal communication networks (Jandrić et al. 2019). This could prompt further inquiries on how the CBRL framework might be applied, modified, and expanded.

Finally, while reflective practice theories focus on professional development, and thus, benefits work performance, the CBRL framework should not be seen solely as a means to enhance employability and career prospects. Schneider (2019) warns against the trend of preparing students solely for future marketability. Nevertheless, given the convergence of work, employment, technology, and education, further discussion is needed on the broader implications of CBRL in postdigital work landscape. There has been rich dialogue among postdigital scholars about the interplay between pedagogy, technology, and work (See Part II and III in Peters et al. 2019a).

In conclusion, a new learning framework that promotes innovative cross-domain interaction enhances our understanding of what it means to cultivate reflective practice and expertise in a dynamic postdigital world.