Remote or Removed: Predicting Successful Engagement with Online Learning during COVID-19

Using data from a spring 2020 survey of nearly 10,000 parents of elementary school parents in one large southeastern public school district, the authors investigate predictors of elementary school student engagement during the initial period of pandemic remote learning. The authors hypothesize that household material and technological resources, school programming and instructional strategies, and family social capital contribute to student engagement in remote learning. The analyses indicate that even after controlling for rich measures of family socioeconomic resources, students with access to high-speed Internet and Internet-enabled devices have higher levels of engagement. Exposure to more diverse socioemotional and academic learning opportunities further predicts higher levels of engagement. In addition, students whose families remained socially connected to other students’ families were more likely to engage online

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Lean and Green – Synergies, Differences, Limitations, and the Need for Six Sigma

Part 1: Knowledge-Based SustainabilityInternational audienceHistorically, profitability and efficiency objectives have been the prevailing interest for organisations. However, the move towards green operations has forced companies to seek alternatives to combine these with green objectives and initiatives. Green lean is the result of this combination. The purpose of this paper is to critically discuss the green lean approach and the potential benefits of integrating Six Sigma to enhance its effectiveness. The paper is based on a literature review that discusses the synergies and differences of lean and green, and its main limitations. Departing from the limitations identified, the paper then proposes Six Sigma, and specially its problem solving methodology DMAIC, as an approach that may help in overcoming the limitations of green lean. Thus, the paper conceptually proposes Green Lean Six Sigma. It intends to offer academics, researchers and practitioners interested in lean and green with some initial conceptual ideas regarding their possible integration with Six Sigma