Supporting Learning Analytics for Informal Workplace Learning with a Social Semantic Infrastructure
This paper presents the potential of a social semantic infrastructure that implements an Actor Artifact Network (AAN) with the final goal of supporting learning analytics at the workplace. Two applications were built on top of such infrastructure and make
- PDF / 445,063 Bytes
- 4 Pages / 439.37 x 666.142 pts Page_size
- 23 Downloads / 202 Views
2
Tallinn University, Narva Road 29, 10120 Tallinn, Estonia {adolfo,vtomberg,kpata,tley}@tlu.ee Graz University of Technology, Inffeldgasse 13, 8010 Graz, Austria {sdennerlein,dtheiler,elex}@know-center.at
Abstract. This paper presents the potential of a social semantic infrastructure that implements an Actor Artifact Network (AAN) with the final goal of supporting learning analytics at the workplace. Two applications were built on top of such infrastructure and make use of the emerging relations of such a AAN. A preliminary evaluation shows that an AAN can be created out of the usage of both applications, thus opening the possibility to implement learning analytics at the workplace. Keywords: Informal learning · Workplace learning · Social-semantic technologies · Artifact-Actor Network · Data integration
1
Introduction
Informal learning at the workplace is a multi-episodic activity that is often connected to current demands and tasks at the workplace. This fact makes the knowledge to be easily applicable but hinders individual learning experiences to be further taken up in systematic organizational learning practices [1]. Supporting such unplannable learning experiences with technology has proven to be a major challenge that is far from being solved. The Learning Layers project is devoted to tackle with these learning processes. Several applications have been developed in this project, as well as an infrastructure that enables their technical integration [2]. This infrastructure relies on a semantically-enriched Artifact-Actor Network (AAN) [3] to describe the relationships among actors and artifacts in different learning contexts. This AAN can be useful to support learning activities or to monitor the learning processes [2]. But how to take advantage of this AAN to monitor and to feed back on these learning processes is still a problem that could be approached using learning analytics techniques [4]. This paper reports a first step exploring how an AAN can be exploited for learning analytics using a social-semantic infrastructure. c Springer International Publishing Switzerland 2015 G. Conole et al. (Eds.): EC-TEL 2015, LNCS 9307, pp. 634–637, 2015. DOI: 10.1007/978-3-319-24258-3 76
Supporting Learning Analytics for Informal Workplace Learning
2
635
A Social Semantic Infrastructure to Support Workplace Learning
The Social Semantic Server (SSS) is an infrastructure specially developed to integrate workplace-learning applications. From a data perspective, its key idea is to log the interactions between actors and artifacts-including some meta-data that describes the context where this interaction takes place- and then offer an abstraction of this data as a semantically-enriched AAN. Thus, the relationships between the SSS entities are explicit. In addition, as the relationships of this AAN have a semantic meaning, they can be based on different characteristics of the entities that may depend on their associated context. For example, some artifacts may be related because they are frequently accessed from the
Data Loading...
