Spatial microsimulation models have been in use for around 40 years for various applications. Responding to users' needs and project purpose, many have emerged using different methods and algorithms. Despite this, the literature suggests a gap in applications combining operability, flexibility, availability or generally an implementation of an online web mapping application in the area of spatial microsimulation. In this paper we introduce the development of a new open-source web-based spatial microsimulation framework, called simSALUD, as a solution approach for static simulation modelling where no programming skills are required. The emphasis lies on the design and implementation of the wizard and web-based spatial microsimulation application, including integrated validation and mapping elements. The current version supports two deterministic spatial microsimulation algorithms (combinatorial optimisation and iterative proportional fitting). The application is designed for experts as well as for non-experts to simulate
Abstract-The success of (online) courses depends, among other factors, on the underlying didactical models which have always been evaluated with qualitative and quantitative research methods. Several new evaluation techniques have been developed and established in the last years. One of them is 'learning curves', which aim at measuring error rates of users when they interact with adaptive educational systems, thereby enabling the underlying models to be evaluated and improved. In this paper, we report how we have applied this new method to two case studies to show that learning curves are useful to evaluate didactical models and their implementation in educational platforms. Results show that the error rates follow a power law distribution with each additional attempt if the didactical model of an instructional unit is valid. Furthermore, the initial error rate, the slope of the curve and the goodness of fit of the curve are valid indicators for the difficulty level of a course and the quality of its didactical model. As a conclusion, the idea of applying learning curves for evaluating didactical model on the basis of usage data is considered to be valuable for supporting teachers and learning content providers in improving their online courses.
The topic of adaptation-pertinent systems was treated intensively by researchers before the era of computers, also in the field of teaching and learning. Further, E-Learning is a relatively young term, but since the beginning of computer sciences in the middle of the past century, many systems and theoretical solution approaches were developed to enable digital education. This paper aims at reviewing some interesting issues regarding this context in order to gain an insight into forgotten or ignored opportunities and challenges as well as underline the relevance and impact of old issues for present requirements.
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