EWMA p charts for detecting changes in mean or scale of normal variates

Methods of Statistical Process Control (SPC) are used for detecting deviations from regular processing. SPC is applied in manufacturing implementations where statistical tools are used to monitor the performance of production processes in order to identify and correct considerable changes in the process performance. Today, SPC methods are incorporated by organizations around the world as a suitable tool to improve product quality by reducing process variation. The current method of SPC is the application of control charts which are used to monitor process parameters (e. g., mean μ, standard deviation σ or percent defective p) over time. Well-established control chart schemes are, amongst others, exponentially weighted moving average charts (EWMA), cumulative sum charts (CUSUM) or, of course, the classical Shewhart charts. In this article, an EWMA control chart for variables calculating the percent defective p = f (μ, σ) will be presented where both process parameters are under risk to change. The scheme will be compared to several other control chart applications (EWMA X, EWMA X-S2, and an alternative EWMA p chart). Numerical methods and Monte Carlo simulations are used for computing the average run length (ARL) as the measure of performance

Make MOOCs count for higher education: Approaches to awarding ECTS Credits for learning in open online courses

MOOCs provided by Higher Education Institutions (HEIs) have the potential to open up education to a wider audience. By implementing appropriate quality assurance measures, they could also provide a first creditable step into the formal higher education system. Exploring the potential of credentialization and recognition of MOOCs was a major pillar of the INTEGRAL²-project (“Integration and Participation of Refugees in the Context of Digital Teaching and Learning Scenarios”) of Lübeck University of Applied Sciences, RWTH Aachen University and Kiron Open Higher Education. The partners explored possible combinations of the openness of MOOC-based learning with quality assurance and examination approaches that abide to standards of the European Higher Education Area. Regarding quality assurance measures, Kiron has repurposed and adapted tools developed through the Bologna Process in order to explore new pathways to the recognition of prior learning. A core element are MOOC booklets (MOOklets) that connect and display all quality information needed for recognition in a comparable, standardized way. As the university partners identified the existing exams within MOOCs to be the most critical part in order to award legitimate credit points, the partners followed two different approaches: Module-based competence assessment (on- and offline) and MOOC-based examinations (offline). Lübeck University of Applied Sciences tested a procedure to verify learning outcomes by written and oral examinations whilst RWTH Aachen University targeted a more traditional examination approach with written and e-exams that can be taken simultaneously at different offline locations. In the follow-up project INTEGRAL+, the partners will focus on establishing a German examination network for e-assessment of MOOC-based learning. Both efforts in the field of a firm examinations and the endorsement of recognition processes of all existing and future university partners within the Kiron network can lead to simplified admission process and can be key enablers of a successful integration via education