A case study in the e-assessment of statistics for non-specialists

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 represen