Harmonizing Software Standards with a Semantic Model

The application of standards in the software development process supports interoperability between systems. Maintenance of standards must be guaranteed on the organisational and technical level. The use of semantic technologies can contribute to the standard maintenance process by providing a harmonizing bridge between standards of different knowledge domains and languages and by providing a single point of administration for standard domain concepts. This paper describes a case study of the creation of a semantic layer between software standards for water management systems in The Netherland

Semantic Web Tools and Decision-Making

Semantic Web technologies are intertwined with decision-making processes. In this paper the general objectives of the semantic web tools are reviewed and characterized, as well as the categories of decision support tools, in order to establish an intersection of utility and use. We also elaborate on actual and foreseen possibilities for a deeper integration, considering the actual implementation, opportunities and constraints in the decision-making context.info:eu-repo/semantics/publishedVersio

Generating actionable predictive models of academic performance

© 2016 Copyright held by the owner/author(s). The pervasive collection of data has opened the possibility for educational institutions to use analytics methods to improve the quality of the student experience. However, the adoption of these methods faces multiple challenges particularly at the course level where instructors and students would derive the most benefit from the use of analytics and predictive models. The challenge lies in the knowledge gap between how the data is captured, processed and used to derive models of student behavior, and the subsequent interpretation and the decision to deploy pedagogical actions and interventions by instructors. Simply put, the provision of learning analytics alone has not necessarily led to changing teaching practices. In order to support pedagogical change and aid interpretation, this paper proposes a model that can enable instructors to readily identify subpopulations of students to provide specific support actions. The approach was applied to a first year course with a large number of students. The resulting model classifies students according to their predicted exam scores, based on indicators directly derived from the learning design

Transformation language integration based on profiles and higher order transformations

For about two decades, researchers have been constructing tools for applying graph transformations on large model transformation case studies. Instead of incrementally extending a common core, these competitive tool builders have repeatedly reconstructed mechanisms that were already supported by other tools. Not only has this been counter-productive, it has also prevented the definition of new language constructs independently of a specific transformation tool. Moreover, it has complicated the comparison of transformation languages. This paper describes a light-weight solution to this integration problem. The approach is based on executable transformation modeling using a small UML profile and on higher order transformations. It enables the integration of graph transformation tools such as Fujaba, VMTS and GReAT. The paper illustrates the approach by discussing the contribution of a Copy operator to any of these tools. Other language constructs can be realized similarly, without locking into specific tools

Emergent achievement segregation in freshmenlearning community networks

A common assumption about Freshmen Learning Communities (FLCs) is that academic relationships contribute to students’ success. This study investigates how students inlearning communities connect with fellow students for friendship and academic support. Longitudinal social network data across the first year, collected from 95 Dutch students in eight FLCs, measure both social and academic relational choices within and beyond the FLCs. Using stochastic actor-based models, the study tests two competing hypotheses. The alignment hypothesis states that students connect with their similar-achieving friends for both academic and social support, leading to an alignment of both types of networks over time. In contrast, the duality hypothesis states dissimilarity between academic support networks and friendship networks: students should connect with better-achieving fellow students for academic support and to more similar peers for friendship. The data support the alignment hypothesis but not the duality hypothesis; in addition, they show evidence of achievement segregation in FLCs: the higher the students’ achievement level, the more they connect with other students for both academic support and friendship, relating in particular to peers with a similarly high achievement level. The results suggest that lower-achieving students are excluded from the support provided by higher achieving students and instead ask similar lower achievers for support. They thus cannot benefit optimally from the academic integration FLC offer. The article concludes with recommendations of how to support students in an FLC so that they can reach optimal achievement potential