As cases of COVID-19 surge across the world, research has begun to emerge which considers the implications of school lockdowns on student learning, engagement, and achievement. Yet as face-to-face teaching and learning recommences, it is not only students who will need help adjusting to "the new normal". While 2020 has seen a dramatic increase in the workload of teachers, many of whom have negotiated a continuity of learning in adverse circumstances, we must remember that long before COVID-19 disrupted schools, teachers were already at risk of burnout. The novel coronavirus has further exacerbated the stresses facing teachers, and as countries continue to navigate periods of remote education, recognising and supporting teacher wellbeing should be a key priority. In recognition of the contributions of teachers and the influence they yield over student learning, this article considers the importance of creating conditions for supporting teacher wellbeing before, during, and after the current pandemic.
There is debate within the health promoting school (HPS) movement on whether schools should monitor health behaviour outcomes as part of an evaluation or rely more on process type measures, such as changes to school policies and the physical and social environment which yield information about (in)effective implementation. The debate is often framed around ideological considerations of the role of schools and there is little empirical work on how these indicators of effective implementation can influence change at a policy and practice level in real world settings. Information has potentially powerful effects in motivating a change process, but this will vary according to the type of information and the type of organizational culture into which it is presented. The current predominant model relies on process data, policy and environmental audit monitoring and benchmarking approaches, and there is little evidence of whether this engages school communities. Theoretical assertions on the importance of monitoring data to motivate change need to be empirically tested and, in doing so, we can learn which types of data influence adoption of HPS in which types of school and policy contexts.
Understanding the interactions between natural processes and human activities poses major challenges as it requires the integration of models and data across disparate disciplines. It typically takes many months and even years to create valid endto-end simulations as different models need to be configured in consistent ways and generate data that is usable by other models. MINT is a novel framework for model integration that captures extensive knowledge about models and data and aims to automatically compose them together. MINT guides a user to pose a well-formed modeling question, select and configure appropriate models, find and prepare appropriate datasets, compose data and models into end-to-end workflows, run the simulations, and visualize the results. MINT currently includes hydrology, agriculture, and socioeconomic models.
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