Towards a semantic modeling of learners for social networks

The Friend of a Friend (FOAF) ontology is a vocabulary for mapping social networks. In this paper we propose an extension to FOAF in order to allow it to model learners and their social networks. We analyse FOAF alongside different learner modeling standards and specifications, and based on this analysis we introduce a taxonomy of the different features found in those models. We then compare the learner models and FOAF against the taxonomy to see how their characteristics have been shaped by their purpose. Based on this we propose extensions to FOAF in order to produce a learner model that is capable of forming the basis of a semantic social network.<br/

The role of social networks in students’ learning experiences

The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined

New variable stars in the direction of the bright cloud B in Sagittarius

621 new variable stars have been detected in a field of 5.5 degrees *5.5 degrees in the direction of the galactic centre on plates obtained with the Schmidt telescopes of the Mount Palomar Observatory (1968) and of the European Southern Observatory (1976 to 1980). The parameters alpha , delta , 1, b, R(Max), R(Min) and delta m for these variable stars have been determined from astrometric measurements at ESO-CERN and photometric measurements at CDCA. It is found from the delta m/N histogram that 379 variable stars have an amplitude of variation between 0.5 and 2.0 magnitudes. The number of variable stars is found to decrease rapidly towards large amplitudes. As a result of these observations the surface density of known variable stars in this field has increased from 2 to 21 per square degree

A multiple constraints framework for collaborative learning flow orchestration

Paper presented at ICWL 2016, 15th International Conference, Rome, Italy, October 26–29, 2016.Collaborative Learning Flow Patterns (e.g., Jigsaw) offer sound pedagogical strategies to foster fruitful social interactions among learners. The pedagogy behind the patterns involves a set of intrinsic constraints that need to/nbe considered when orchestrating the learning flow. These constraints relate to the organization of the flow (e.g., Jigsaw pattern - a global problem is divided into sub-problems and a constraint is that there need to be at least one expert group working on each sub-problem) and group formation policies (e.g., groups solving the global problem need to have at least one member coming from a different previous expert group). Besides, characteristics of specific learning situations such as learners’ profile and technological tools used provide additional parameters that can be considered as context-related extrinsic constraints relevant to the orchestration (e.g., heterogeneous groups depending on experience or interests). This paper proposes a constraint framework that considers different constraints for orchestration services enabling adaptive computation of orchestration aspects. Substantiation of the framework with a case study demonstrated the feasibility, usefulness and the expressiveness of the framework.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness/n(TIN2014-53199-C3-3-R; MDM-2015-0502)

Group formation for collaboration in exploratory learning using group technology techniques

Exploratory Learning Environments (ELEs) allow learners to approach a problem in different ways; they are particularly suitable for ill-defined problems where knowledge is less structured and open-ended exploration is allowed. Moreover, multiple solutions which are equally valid are possible and a common and efficient way to convey this is by promoting and supporting students’ collaboration. Successful collaboration, however, depends on forming groups in which the activity is relevant for all members of the group. In this paper we present a computational model for group formation for open-ended exploration in ELEs by modelling the various strategies that learners adopt to solve the same task. This is underpinned by Group Technology techniques that use as criteria the learners’ strategies and the similarity among them to form groups that match pedagogy considerations. The proposed mechanism is tested in an exploratory learning environment for mathematical generalisation