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The need to be able to choose, perform and interpret the results from appropriate statistical tests is ubiquitous in many STEM disciplines and beyond. In this case study, we illustrate a learning and assessment approach that has been used successfully for first year Business School students taking a module on Business Decision Making for Marketing and Events. The objective of the module is to give students a grounding in statistics, including learning to use the SPSS package, and to apply the techniques learnt to a large real-world data set. Due to the large number of students and their diverse abilities the learning and teaching strategy is centred on using formative key skill e-assessments to encourage students to self-learn. On accessing each e-assessment, students are presented with a randomly generated data set, which they are required to import into SPSS to then appropriately analyse and report on. Marking and feedback occurs automatically on submission and repeated use ensures that a student thoroughly learns a key skill and covers various analysis outcome scenarios, for instance significant or not significant test outcomes. Each key skill e-assessment has multiple embedded links to comprehensive Help pages that provide SPSS 'how-to' information or output interpretation. Access to these means that staff in the PC sessions can concentrate on giving higher-level support as opposed to merely helping with the mechanics of producing SPSS output. The e-assessments were created using Dewis, which is a fully algorithmic open-source e-assessment system. Dewis' ability to communicate with the R programming language facilitates the creation of authentic e-assessments, generating bespoke student data and providing answers that match SPSS screen output. The assessment of students' statistical competency is by in-class e-exams, which are summative and sat under exam conditions. The fact that the formative and summative e-assessments are marked immediately by Dewis represents a huge saving in marking time compared to human marking and allows students to have instant feedback on their work. Repeated use of the formative e-assessments allows students to independently practice and check their understanding. In this case study, we find that those students that did practice achieved significantly higher marks in the e-exams. We are now in our third year of delivery and the module has developed further due to stronger connections between the business and statistics strands of the module.

We demonstrate how the DEWIS e-Assessment system may use embedded R code to facilitate the assessment of students' ability to perform involved statistical analyses. The R code has been written to emulate SPSS output and thus the statistical results for each bespoke data set can be generated efficiently and accurately using standard R routines. This enables students' answers, generated from their application of SPSS, to be marked and appropriate feedback supplied back to them automatically. Staging is used between different parts of the e-Assessment to replicate the natural stages of a complete statistical analysis. This allows students the freedom to work away from the e-Assessment; they may view the relevant stage an unlimited number of times prior to submitting their answers for that stage. The technical challenges of setting up the e-Assessment in this way are discussed as well as the rationale for adopting this pioneering approach.

This paper explores a recent move towards project-based learning for a first-year undergraduate statistics module at the University of the West of England, Bristol. The course is aimed at students specialising in Mathematics and Statistics. A classroom-based end of module project week was developed with the focus on project-based learning, supported by Dewis-R data generation and e-Assessments. Simulation of a practice-based environment with a dedicated working area and daily deadlines is incorporated to enhance the activity. Students are faced with a highly relevant statistical analysis task, that is large and has not had the prior data screening or cleansing that they may be accustomed to in basic didactic teaching. Indications are that the project-based learning approach, assessed during a project week with supplementary e-Assessments and a final report, is well received and leads to improved student outcomes. [ABSTRACT FROM AUTHOR]

Tropical rainforests are increasingly disturbed by human activities. While restoration projects often succeed in replacing tree cover, they rarely manage to restore soil function. Consequently, there is an urgent need to understand the changes that occur during soil restoration. Model ecosystems such as the Eden Project present an ideal opportunity to investigate these changes. The Eden Project was built 15 years ago, and its plants grown from seedlings, or sown directly into a soil made up of standardized mixtures of recycled organic material. Today, the Eden Project's rainforest biome consists of a diverse community of plants, invertebrates, and microorganisms. Different areas within the biome are managed differently, allowing us to separate the relative contributions of decomposers under differing physical conditions. Litterbag experiments revealed significant differences in decomposition rates in bags of different mesh sizes. Phospholipid fatty acid analysis revealed that microbial biomass and community structure varied under different management regimes. Soil enzyme assays revealed that glucosidase activity increased in soils with more organic matter, whereas phenol oxidase activity increased in more alkaline soils. Our study takes a step toward understanding the interactions between invertebrates and microbes, and the way in which soils function during restoration. [ABSTRACT FROM AUTHOR]

We report on the creation of statistics e-assessments using the Dewis system with embedded R code. Dewis is a fully algorithmic open-source e-assessment system designed and developed at the University of the West of England, Bristol (UWE). Dewis' ability to communicate with the R programming language greatly facilitates the task of generating bespoke data and its subsequent analysis. This approach has allowed us to successfully test students' ability to perform involved statistical analyses on individual data sets and led to the creation of a suite of open access online e-learning modules on the UK national statstutor website. Development of a Dewis-R interface allows the creation of sophisticated e-assessments solely by writing an R script file. The goal is to create a community of Dewis-R practitioners who will be able to author and share relevant, authentic and engaging statistics e-assessments that enrich the learning experience of students. [ABSTRACT FROM AUTHOR]

Nitric oxide (NO) and hydrogen peroxide (H2O2) are key signalling molecules produced in response to various stimuli and involved in a diverse range of plant signal transduction processes. Nitric oxide and H2O2 have been identified as essential components of the complex signalling network inducing stomatal closure in response to the phytohormone abscisic acid (ABA). A close inter-relationship exists between ABA and the spatial and temporal production and action of both NO and H2O2 in guard cells. This study shows that, in Arabidopsis thaliana guard cells, ABA-mediated NO generation is in fact dependent on ABA-induced H2O2 production. Stomatal closure induced by H2O2 is inhibited by the removal of NO with NO scavenger, and both ABA and H2O2 stimulate guard cell NO synthesis. Conversely, NO-induced stomatal closure does not require H2O2 synthesis nor does NO treatment induce H2O2 production in guard cells. Tungstate inhibition of the NO-generating enzyme nitrate reductase (NR) attenuates NO production in response to nitrite in vitro and in response to H2O2 and ABA in vivo. Genetic data demonstrate that NR is the major source of NO in guard cells in response to ABA-mediated H2O2 synthesis. In the NR double mutant nia1, nia2 both ABA and H2O2 fail to induce NO production or stomatal closure, but in the nitric oxide synthase deficient Atnos1 mutant, responses to H2O2 are not impaired. Importantly, we show that in the NADPH oxidase deficient double mutant atrbohD/F, NO synthesis and stomatal closure to ABA are severely reduced, indicating that endogenous H2O2 production induced by ABA is required for NO synthesis. In summary, our physiological and genetic data demonstrate a strong inter-relationship between ABA, endogenous H2O2 and NO-induced stomatal closure. [ABSTRACT FROM AUTHOR]