Target Group-specific Curricula (NFDI4Earth Deliverable D1.3.2)

The NFDI4Earth EduTrain team addresses the widening gap between current and required skills for Earth System Science (ESS) researchers, focusing on Research Data Management (RDM) training and Spatial Data Analytics. Ensuring ongoing relevance, the team continuously evaluates tailor-made modules designed to equip ESS researchers with competencies for roles such as research data manager, data steward, and Earth system data scientist.

This exploratory report underscores the importance of optimal learning experiences and introduces planned curriculum development. Emphasis is placed on key principles, including a shift to recognising learning outcomes and competencies, and the crucial role of motivation. Learning Objectives play a central role in curriculum design, providing clarity on intended behaviours, conditions, and assessments; while the discussion on Learning Domains highlights the multifaceted nature of educational goals. We also highlight the importance of active learning and delve into Adult Learning Theories, particularly Malcolm Knowles' assumptions, providing valuable insights for our educational framework.

We define a curriculum as a set of goals activated through a development process, with a focus on assessment, goal definition, and continuous evaluation. Strategies for curriculum development including leveraging Bloom's taxonomy, adopting a fixed grammar for learning objectives, and mapping teaching formats to qualification goals for flexibility, are introduced. Three state-of-the-art strategies are selected: the Four-Component Instruction Design, a lesson life-cycle approach inspired by The Carpentries, and scenario-based learning – collectively providing a comprehensive framework for the NFDI4Earth EduTrain curriculum development.

In addition, the process of crafting a tailored study plan for our target group is delineated, emphasising an iterative and non-linear curriculum development approach. Divided into two distinct phases—Plan and Implementation—the creation of learning paths and course offerings targets Earth system science researchers, with an initial focus on doctoral-level content. A thorough needs assessment, including input from the EduTrain team and Academy Fellows, informs the scope of the curriculum, addressing core competencies such as FAIR data principles and data analysis. Drawing inspiration from established frameworks like the EDISON Data Science Framework and utilising existing course material within the consortia, we present a template and guide for the structure of the spatiotemporal analysis curriculum. The phased workflow, encompassing planning and implementation, sets the groundwork for future milestones.

In conclusion, the NFDI4Earth curated curriculum aims to provide teaching modules covering relevant concepts in the spatial data lifecycle, with a special focus on spatial data analytics content adaptable to our target group or learners' needs. Continuous evaluation and optimisation with each feedback and revision cycle ensure the developed curricula's ongoing relevance and effectiveness.