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

The paper addresses the competencies needed to tackle complex, wicked problems such as sustainable development and climate change, whose framing and solutions depend on stakeholders’ perspectives. It argues that a key enabler is “insight discovery,” defined as the ability and willingness to identify and overturn one’s own assumptions by assimilating new experiences and knowledge. Rather than relying on reproductive, technical solutions, the authors emphasize new ways of knowledge production that integrate diverse disciplinary and extra-academic perspectives. They propose focusing on an insight discovery process (IDP) that improves how individuals interpret existing information, fostering joint problem framing in transdisciplinary research. The paper outlines literature gaps on insight, presents the IDP framework developed through a transdisciplinary winter school with Masters, PhD, and postdoctoral participants in Switzerland, and discusses implications for research, learning, and societal transformation.

The paper reviews the concept of “insight” as accurate and deep understanding, often labeled as the AHA!/Eureka moment. Originating with Gestalt psychology, early research showed that restructuring available information can lead to sudden new understandings, typically studied in well-defined problems. Extending to complex, group-based problem solving, the authors connect insights to joint problem framing in transdisciplinary research, where integrating diverse perspectives requires individuals to adapt their mental models. In transdisciplinary education (integrated systems and design thinking), insights are distinguished from facts by their explanatory power (how/why, not just what), often revealing counterintuitive contrasts and restructuring prior assumptions. The literature supports key characteristics of insights: (1) subjectivity (not all individuals receiving the same information achieve insight), (2) suddenness (light-bulb experience), (3) certainty (confidence without checking), and (4) emotions (positive affect and tension release). The review identifies a gap in applying insight beyond laboratory settings to complex, collaborative contexts and motivates the development of a process-oriented framework for insight in transdisciplinary learning.

Context: The concept of insight discovery was developed in a Bachelor’s course at ETH Zurich (“Tackling Environmental Problem Solving”) and further explored in the TdLab Winter School (8 days), which engages participants with a real-world community issue. This paper is based on experiences and data from the final year of the Winter School. Participants and setting: 17 Masters students, PhD candidates, and postdoctoral researchers from 13 countries and 10 universities, speaking more than 10 languages, collaborated with residents of Wislikofen, Switzerland, on the topic of community amalgamation. Participants lived and worked together at a monastery-turned seminar hotel (Propstei Wislikofen), which served as the hub for engagement with local stakeholders. Procedure: The task was to design a community interaction event to support amalgamation. First 4 days: participants explored the local context via conversations, site visits, and rich pictures (image-rich system maps from soft systems methodology). They validated their understanding with stakeholders. Last 4 days: groups identified key insights, defined problem statements (insight, affected stakeholder, and stakeholder needs), and designed the event using a design thinking ideation process. In parallel, they were introduced to transdisciplinary concepts and tools, joint problem framing, soft systems thinking, and design thinking to practice moving beyond disciplinary silos. Data collection: Participants completed an online daily insight journal over 8 days (at least 6 entries each), guided by the prompt: “What was your AHA! Moment of today? If there was none, what was something new that you learned?” Entries were anonymized and visible to participants. Participants were informed entries could be used for research; those quoted provided permission. Data analysis: All co-authors independently conducted open coding of the sequential diaries to identify quotes relevant to insights and derive categories (Strauss and Corbin, 1998). Through iterative differentiation and relating categories, the team developed an initial model of the insight discovery process and selected illustrative quotes capturing phases and the overall process. Ethical considerations and biases: The study relied on subjective self-reports outside laboratory settings (as recommended by prior research). Limitations include perceptual differences in defining ‘insight’ and potential social desirability bias, mitigated by voluntary, anonymous entries and emphasis on safe participation. Collective analysis by a diverse author team aimed to reduce idiosyncratic interpretations. The research was unplanned within an educational program; ethical principles (Declaration of Helsinki) were followed, data were anonymized and secured, and informed consent for quoted material was obtained.

• The Insight Discovery Process (IDP) model: Derived from qualitative analysis of participant journals, the IDP comprises two states and three phases: • State 1: Original mental model (pre-existing personal representation shaped by experiences, attitudes, and knowledge) • Phase 1: Insight trigger (new information challenging the current model, inducing cognitive dissonance; aligns with Klein’s Triple Path: contradictions, connections, creative desperation) • Phase 2: Liminal space (movement beyond comfort zone into uncertainty; requires willingness to learn and includes three intertwined sub-processes):
  • Reflection (questioning and making implicit assumptions explicit)
  • Problem reframing and iteration (nonlinear adjustments to assumptions; multiple loops)
  • Signal processing (sensemaking through external ‘signals’, feedback, and testing ideas with others) • Phase 3: Insight formulation (moment of clarity and shareable understanding; akin to threshold concepts that transform perception) • State 2: Adapted mental model (new, integrated understanding used going forward)
• Non-linearity: The sub-processes within the liminal space occur nonlinearly; multiple can co-occur and repeat. Not all participants described all sub-processes, and not all reached a formed insight or adapted mental model.
• Enabling conditions: Internal and external factors facilitate the IDP. • Internal: Willingness to learn (openness and readiness to acquire new knowledge; influenced by attitudes, personality, and context). • External: Physical environment (retreat-style, communal setting fostering bonds and reflection), collective identity/norms/goals (listening over telling, reflection, questioning assumptions, embracing uncertainty), and specific activities and tools (journaling, rich pictures, systems thinking, joint problem framing, design thinking; use of td-net toolbox). Together these create a safe space that supports movement through discomfort toward insight.
• Illustrative examples: Journal entries showed participants experiencing triggers (e.g., ‘fishbowl’ session), entering liminal spaces of confusion, iteratively reframing roles (from passive student to active researcher), processing varying engagement levels, and formulating insights (e.g., seeing process as a flow of energy among people).
• Contextual data points: 17 participants; 13 countries; 10 universities; multi-lingual collaboration; 8-day program with at least 6 journal entries per participant.

The authors propose three main implications of the IDP for inter- and transdisciplinary research and learning:

1. Confronting societal dilemmas: For wicked sustainability and climate challenges, the IDP offers a process to integrate divergent perspectives and foster social innovation by cultivating willingness to learn and safe spaces among stakeholders. In areas like the energy transition, the IDP can help bridge global objectives with local needs by developing shared, collective mental models, informing initiatives such as the ENCLUDE project.
2. Knowledge integration for inter- and transdisciplinarity: The mindset underpinning insight discovery—curiosity, openness, suspension of one’s viewpoint, tolerance for discomfort, critical and creative inquiry—aligns with capabilities required for ITDR. Insight formulation inherently involves integrating knowledge across disciplines and beyond academia, supporting emergence of holistic understanding and equipping students with future-oriented skills (e.g., complex problem solving, ideation).
3. Transformative learning: The IDP operationalizes transformative learning theory (Mezirow) by explicating how frames of reference (mental models) are transformed through critical reflection within a liminal space. It emphasizes communicative learning (Habermas), where meaning, values, and emotions are integral to understanding, and shows how threshold-like insights catalyze lasting perspective shifts. The IDP is embedded in an award-winning undergraduate curriculum reaching over 1000 students, indicating its practical applicability for transformative education.

Insight discovery is presented as a key competence for inter- and transdisciplinary research, transformative learning, and addressing wicked societal problems. The authors propose a non-linear, dynamic Insight Discovery Process comprising triggers, a liminal space (reflection, reframing, signal processing), and insight formation, culminating in an adapted mental model. Based on qualitative journals from a transdisciplinary winter school, they show that insight discovery is shaped by both cognitive and affective processes and is contingent on external conditions (physical setting, collective identity and norms, activities and tools) that create safe spaces for learning. By articulating the IDP and its enabling conditions, the paper supports researchers and instructors in designing projects and courses that systematically foster insight discovery and integration of diverse perspectives.

• Reliance on self-reported journals introduces subjectivity, potential perceptual differences in the meaning of ‘insight,’ and social desirability bias; mitigations included anonymity, voluntariness, and fostering a safe environment.
• Qualitative, context-specific study with a small cohort (n=17) in a single 8-day program may limit generalizability.
• Nonlinearity and variability in participants’ experiences mean not all sub-processes are observed for all individuals, and not all participants reach a formed insight or adapted mental model.
• Unplanned research embedded in an educational program did not follow standard prospective ethical approval pathways (though ethical principles and informed consent for quoted material were applied); participants were part of a pre-existing group rather than recruited for research.
• No control group or longitudinal follow-up to assess persistence or transfer of adapted mental models beyond the program; datasets are not publicly available due to privacy constraints.