Providing opportunities to demonstrate mastery rather than memory: testing programming skills in a programming environment

First year programming units are commonly assessed by paper-based programming examinations. This component forms a large proportion of the assessment of the unit, and students report that they find both the preparation process and the environment highly stressful. Studying for a closed book, paper-based examination encourages surface learning, rather than understanding. This method of assessment tests a student’s ability to perform at only the lower levels of the Cognitive Domain of Bloom’s Taxonomy of Learning and does not effectively test performance at the higher levels of Synthesis and Evaluation. Often what is really being tested is a student’s ability to memorise information and to perform under examination conditions. The question of whether or not a student has achieved the learning outcomes of a programming unit may be better answered by assessing a student’s ability to design, code and test a solution to a real programming problem in a real programming environment. This paper describes a situation in which students undertaking a first year programming unit are assessed using a programming examination, in a programming environment and focuses on the logistics management and security issues raised by this kind of examination. Preliminary results are analysed, and feedback from the students is documented

Computing with CodeRunner at Coventry University:Automated summative assessment of Python and C++ code.

CodeRunner is a free open-source Moodle plugin for automatically marking student code. We describe our experience using CodeRunner for summative assessment in our first year undergraduate programming curriculum at Coventry University. We use it to assess both Python3 and C++14 code (CodeRunner supports other languages also). We give examples of our questions and report on how key metrics have changed following its use at Coventry.Comment: 4 pages. Accepted for presentation at CEP2

Architecture of Environmental Risk Modelling: for a faster and more robust response to natural disasters

Demands on the disaster response capacity of the European Union are likely to increase, as the impacts of disasters continue to grow both in size and frequency. This has resulted in intensive research on issues concerning spatially-explicit information and modelling and their multiple sources of uncertainty. Geospatial support is one of the forms of assistance frequently required by emergency response centres along with hazard forecast and event management assessment. Robust modelling of natural hazards requires dynamic simulations under an array of multiple inputs from different sources. Uncertainty is associated with meteorological forecast and calibration of the model parameters. Software uncertainty also derives from the data transformation models (D-TM) needed for predicting hazard behaviour and its consequences. On the other hand, social contributions have recently been recognized as valuable in raw-data collection and mapping efforts traditionally dominated by professional organizations. Here an architecture overview is proposed for adaptive and robust modelling of natural hazards, following the Semantic Array Programming paradigm to also include the distributed array of social contributors called Citizen Sensor in a semantically-enhanced strategy for D-TM modelling. The modelling architecture proposes a multicriteria approach for assessing the array of potential impacts with qualitative rapid assessment methods based on a Partial Open Loop Feedback Control (POLFC) schema and complementing more traditional and accurate a-posteriori assessment. We discuss the computational aspect of environmental risk modelling using array-based parallel paradigms on High Performance Computing (HPC) platforms, in order for the implications of urgency to be introduced into the systems (Urgent-HPC).Comment: 12 pages, 1 figure, 1 text box, presented at the 3rd Conference of Computational Interdisciplinary Sciences (CCIS 2014), Asuncion, Paragua