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A STEM-based faculty in an Australian university leveraged online educational technology to help address student and academic concerns associated with team-based assessment. When engagement and contribution of all team members cannot be assured, team-based assessment can become an unfair and inaccurate measure of student competency. This case study explores the design and capacity of an online self and intra-team peer-assessment of teamwork strategy to measure student engagement and enable peers to hold each other accountable during team-based assessments. Analysis of student interactions across 39 subjects that implemented the strategy in 2020, revealed that an average of 94.4% of students completed the self and intra-team peer-assessment task when designed as part of a summative team-based assessment. The analysis also revealed that an average of 10.3% of students were held accountable by their peers, receiving feedback indicating their teamwork skills and behaviours were below the required minimum standard. Furthermore, the strategy was successfully implemented in cohorts ranging from seven to over 700 students, demonstrating scalability. Thus, this online self and intra-team peer-assessment strategy provided teaching teams with evidence of student engagement in a team-based assessment while also enabling students to hold each other accountable for contributing to the team task. Lastly, as the online strategy pairs with any discipline-specific team-based assessment, it provided the faculty with a method that could be used consistently across its schools to support management and engagement in team-based assessments.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL.