Making sense of interdisciplinarity in challenge-based learning:A two-step co-creation approach towards educational redesign

Challenge-based learning gains popularity in engineering education for allowing students to transcend academic and disciplinary boundaries and to fully engage in real-world problems, but it is largely underexplored how to improve specific designs of such educational practices to promote interdisciplinary learning experiences and competencies. This paper describes two studies that together in two steps make up an evidence-based redesign of a challenged-based course featuring group-work projects in an undergraduate program combining engineering with liberal arts and sciences. A first study based on observation and interviews collects different and varying learning experiences throughout students' learning activities. The results showed that interdisciplinary experiences are constructed in complex dynamics between students' disciplinary identity formation and the interdisciplinary and collaborative course configuration. Such dynamics may result in positive learning experiences (engagement and interdisciplinary enrichment) as well as negative ones (disengagement and frustration). Especially regarding the discrepancy between common experiences across the three phases of tackling the challenge (mapping, mitigating, integrating), representatives of parties important for the course were invited to a roundtable session in a second study to discuss and reflect on the first study's findings and what they can mean for the course design. Understandings achieved in the session are used as input for upcoming course redesign towards a more desirably organized challenge-based learning. The two-step approach towards redesign is an example of involving researchers and students in evidence-based educational redesign, exemplifying the value of naturalistic research and educational co-creation in understanding and optimizing students' learning experience to achieve fruitful challenge-based learning.</p

Rethinking social robustness: participatory modeling and values in sustainability science

Participatory modeling in sustainability science allows scientists to take stakeholders’ interests, knowledge, and values into account when designing a model-based solution to a sustainability problem, by incorporating stakeholders in the model-building process. This improves the chance of generating socially robust knowledge and consensus on solutions. Part of what helps in this regard is that scientists, through involving stakeholders, limit their own values from influencing the outcome, thus achieving some level of value-neutrality. We argue that while it might achieve this to some extent, it comes at a cost to the reliability of the outcomes, which is ethically problematic.Peer reviewe

Rethinking Ethnography for Philosophy of Science

We lay groundwork for applying ethnographic methods in philosophy of science. We frame our analysis in terms of two tasks, 1) to identify the benefits of an ethnographic approach in philosophy of science, and 2) to structure an ethnographic approach for philosophical investigation best adapted to provide information relevant to philosophical interests and epistemic values. To this end, we advocate for a purpose-guided form of cognitive ethnography which mediates between the explanatory and normative interests of philosophy of science, while maintaining openness and independence when framing such an investigation in order to achieve robust unbiased results

Mesoscopic modeling as a cognitive strategy for handling complex biological systems

In this paper we aim to give an analysis and cognitive rationalization of a common practice or strategy of modeling in systems biology known as a middle-out modeling strategy. The strategy in the cases we look at is facilitated through the construction of what can be called mesoscopic models. Many models built in computational systems biology are mesoscopic (midsize) in scale. Such models lack the sufficient fidelity to serve as robust predictors of the behaviors of complex biological systems, one of the signature goals of the field. This puts some pressure on the field to provide reasons for why and how these practices are warranted despite not meeting the stated goals of the field. Using the results of ethnographic study of problem-solving practices in systems biology, we aim to examine the middle-out strategy and mesoscopic modeling in detail and to show that these practices are rational responses to complex problem solving tasks on cognitive grounds in particular. However making this claim requires us to update the standard notion of bounded rationality to take account of how human cognition is coupled to computation in these contexts. Our account fleshes out the idea that has been raised by some philosophers on the “hybrid” nature of computational modeling and simulation. What we call “coupling” both extends modelers’ capacities to handle complex systems, but also produces various cognitive and computational constraints which need to be taken into account in any computational problem solving strategy seeking to maintain insight and control over the models produced

Tomorrow's challenges for today's students: challenge-based learning and interdisciplinarity

TU/e innovation Space offers an environment for students to work in interdisciplinary teams on societal problems. These problems ask for development of a shared language for interdisciplinary collaboration and to facilitate learning processes. Little is known about design characteristics for these problems, and what is needed to support interdisciplinarity in student teams. The educational concept Challenge-based learning (CBL) uses authentic societal problems ('challenges') to urge student learning. The main research question for this case study is: What design characteristics of innovation Space challenges support interdisciplinary student collaboration? Data collection consisted of analysis of learning materials, interviews with teachers and students, student surveys about motivation and collaborative learning in four courses and two honour’s tracks. The results show how teachers ask for competence development in supporting students, especially in assessing and integrating discipline knowledge. Students reported high motivation combined with anxiety for open and complex challenges. Over time this anxiety decreases, as students develop knowledge to solve the challenge. Students also reported a need for a clear mapping of learning goals to activities and assessment. For students it appeared often unclear how and on what criteria they are assessed. Yet, students also reported support in developing ownership, self-directed learning, and collaborative learning. This study confirms existing literature that emphasises difficulties in students developing rigorous discipline knowledge in CBL and interdisciplinary assessment. This study increases our understanding of challenge design and how interdisciplinarity can be situated in this design. It offers starting points for research on motivation and collaborative learning in CBL