Going beyond the AHA! moment: insight discovery for transdisciplinary research and learning

Addressing complex, multifaceted problems like sustainable development and climate change requires more than traditional disciplinary approaches. These "wicked problems" are characterized by their context-dependent definitions and open-ended solutions. The authors posit that "insight discovery," the ability to identify and challenge one's own assumptions by integrating new knowledge and experiences, is a key competence for effectively engaging with such complexity. This contrasts with "reproductive solutions" that simply transfer existing knowledge to new contexts. The need for a transdisciplinary approach is acknowledged, but practical implementation, particularly methods for integrating diverse perspectives and restructuring assumptions, remain underdeveloped. The paper proposes that fostering insight discovery is a critical step towards achieving this. The focus shifts from accumulating information to improving its interpretation and utilization. The paper explores existing literature on insights, then presents a framework for the insight discovery process, drawing on empirical evidence from a transdisciplinary winter school, and finally discusses its implications for research, learning, and societal transformation.

The concept of "insight" has been explored since the 1920s by Gestalt psychologists, focusing on problem-solving through information restructuring. Early work focused on well-defined problems with pre-existing solutions. However, in the context of complex, real-world problems, the concept of insight needs to be extended. Problem framing, which involves eliciting, searching, and selecting relevant perspectives, has been recognized as an important element of transdisciplinary research. Joint problem framing, in particular, emphasizes integrating diverse viewpoints to achieve a shared understanding. The authors build upon this concept, further developing the understanding of insights within a transdisciplinary context. Previous literature has identified key characteristics of insights: subjectivity, suddenness, certainty, and emotional impact. This paper aims to fill gaps in this existing literature by examining the broader process through which insights are discovered, rather than just the "AHA!" moment itself.

The concept of "insight discovery" was initially developed within a Bachelor's level course at ETH Zurich. This study builds upon experiences from the Transdisciplinarity Lab (TdLab) Winter School, a 10-year program for Master's students, PhD candidates, and postdoctoral researchers. The study focuses on the final year of the program, where 17 participants from diverse backgrounds worked with local community members on "community amalgamation." The 8-day program involved data collection through conversations with stakeholders, field visits, and the creation of "rich pictures." In the later stages, participants identified key insights, formulated problem statements, and designed a community interaction event. Data collection involved participants keeping daily online journals, prompted by the question: "What was your AHA! Moment of today? If there was none, what was something new that you learned?" Sequential analysis of these journals was undertaken by all co-authors through open coding, identifying relevant quotes and deriving categories to develop an insight discovery process model. The self-reporting approach, while acknowledging limitations like perceptual differences and potential social desirability bias, was chosen to explore the inherently subjective nature of insights. The authors mitigated these limitations through multiple perspectives of analysis from the diverse writing team, employing "social processes of collective interrogation" to arrive at non-idiosyncratic conclusions.

Analysis of the insight diaries revealed a five-stage Insight Discovery Process (IDP): 1. **Original mental model:** The individual's existing understanding and assumptions. 2. **Insight trigger:** New information or experiences that challenge the existing mental model, creating cognitive dissonance. 3. **Liminal space:** A period of reflection, reframing, and signal processing where the individual grapples with the new information. This phase includes: * **Reflection:** Questioning and evaluating one's own assumptions. * **Reframing:** Adjusting assumptions and perspectives based on new knowledge. * **Signal processing:** Making sense of new information and seeking validation. 4. **Insight formulation:** A moment of clarity and understanding, resulting in a shift in the individual's mental model. 5. **Adapted mental model:** The individual's updated understanding incorporating the new insight. The IDP is not necessarily linear; multiple phases can occur concurrently or iteratively. Not all participants reported all phases, highlighting the subjective nature of the process. The success of the process is also dependent on both individual willingness to learn and external enabling conditions such as the physical environment, shared collective identity, norms and goals, and specific learning activities and practices. A safe learning environment that encourages vulnerability and risk-taking was identified as particularly crucial for navigating the liminal space. Examples from participant journal entries illustrate the non-linearity and dynamic nature of the IDP.

The IDP framework offers three main implications: 1. **Addressing societal dilemmas:** The IDP's ability to integrate diverse perspectives is vital for tackling "wicked problems" where solutions are context-dependent and involve multiple stakeholders. This is demonstrated in its application to the energy transition, where bridging diverse interests is crucial for successful decarbonization. 2. **Inter- and transdisciplinary knowledge integration:** The IDP's requirements (curiosity, open-mindedness, critical thinking, and persistence) align with those of transdisciplinary research. Furthermore, the process of insight formation inherently requires integrating knowledge from diverse sources, going beyond a single disciplinary silo. 3. **Transformative learning:** The IDP aligns with Mezirow's transformative learning theory, emphasizing the shift in "frame of reference" (mental model) through critical reflection. The liminal space within the IDP mirrors the need for critical reflection in transformative learning, emphasizing the communicative mode of learning and engagement. The IDP has been successfully integrated into a transdisciplinary curriculum, demonstrating its practical application and impact on student learning.

This paper advances our understanding of insight discovery as a crucial competence for transdisciplinary research, learning, and problem-solving. The proposed IDP model, derived from empirical data from a transdisciplinary winter school, emphasizes the iterative and dynamic nature of insight formation, highlighting the interplay between individual cognitive and affective abilities and the enabling conditions of the learning environment. The implications for integrating the IDP into higher education curricula, fostering transdisciplinary research collaborations, and promoting transformative learning are significant. Future research could focus on further refining the IDP model, exploring its applicability across diverse contexts, and investigating the long-term impacts of fostering insight discovery on research outcomes and societal change.

The study relies on self-reported data from a specific educational program, limiting the generalizability of the findings. Potential biases related to social desirability and perceptual differences are acknowledged. The non-linear and subjective nature of insight discovery poses challenges for quantitative measurement and analysis. Future research incorporating diverse methodologies and broader participant samples would strengthen the generalizability of the findings.