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In today’s complex world, we know as educators that learning is most meaningful when established through experience – learning by doing rather than by simply listening or observing. Our learners need to be supported in nurturing their creativity, developing as critical thinkers and flexible problem solvers, to apply skills and understanding in new domains and different situations creating solutions to problems encountered. Education and life should not be isolated from each other. By providing opportunities for learners to engage and learn through authentic, real-life, relevant experiences, we are scaffolding their application of skills to learning including adapting and changing their ideas and forming habits of lifelong learners. This chapter provides educators with a guide for embedding cross-curricular exploratory learning experiences as an integral part of planning, teaching and assessment responsive to all learners; and inclusive of the theoretical foundations and instructional strategies that inform their approaches. Authentic studies will be utilised, and practical tools outlined, to demonstrate how to bring these concepts to life within a constructivist framework.
This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity.
Methods:
We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology.
Results:
The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops.
Conclusion:
Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.
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