Adolfo Ruiz-Calleja

GLUE!: An architecture for the integration of external tools in Virtual Learning Environments

The integration of external tools in Virtual Learning Environments (VLEs) aims at enriching the learning activities that educational practitioners may design and enact. This paper presents GLUE!, an architecture that enables the lightweight integration of multiple existing external tools in multiple existing VLEs. GLUE! fosters this integration by imposing few restrictions on VLE and tool providers, as well as by requiring an attainable effort from developers, unlike other integration works. Besides, GLUE! facilitates the instantiation and enactment of collaborative activities within VLEs, leveraging the VLEs distinctive features for the management of users and groups. GLUE! has been evaluated using three authentic collaborative learning situations, instantiated and enacted by real practitioners at university level. The results of this evaluation show that GLUE! reduces the burden of educators when instantiating collaborative activities that require the integration of external tools, while facilitates students the realization of these activities in collaboration. Interestingly, the development effort required by the integration software is similar to that in other lightweight generic approaches that offer a lower degree of functionality.

A Linked Data approach for the discovery of educational ICT tools in the Web of Data

The use of Information and Communication Technologies (ICT) tools to support learning activities is nowadays generalized. Several educational registries provide information about ICT tools in order to help educators in their discovery and selection. These registries are typically isolated and require much effort to keep tool information up to date. To address this issue, this paper explores whether educational tool registries can be federated to other datasets currently available on the Web of Data. In order to answer this question, and following the Linked Data approach, this paper proposes to collect data from third-party sources, align it to a vocabulary understandable by educators and finally publish it to be consumed by educational applications. This way, an incipient educational dataset can be automatically created and easily maintained, since non-educative information is obtained from updated third-party sources. A case study with practitioners has been carried out to evaluate whether the information about ICT tools provided by this dataset is understandable and useful for educators. Evaluation results show that available information on the Web of Data can be used to obtain suitable tools for real educational settings, thus overcoming the sustainability problems of existing ICT tool registries.

Integration of External Tools in Virtual Learning Environments: Main Design Issues and Alternatives

The integration of existing educational computer-based tools is a current research trend aimed at increasing the range of learning situations that can be supported by most widely adopted Virtual Learning Environments (VLEs). Nevertheless, due to the technological and functional heterogeneity of both tools and VLEs, there is an integration cost that must be assumed and that varies depending on several design issues. This paper identifies the issues to be tackled when designing a VLE or a tool and the effects that the different alternatives may have in the integration cost. Besides, the paper discusses the advantages and drawbacks of previous research proposals when dealing with such issues. The final goal is to understand the impact of design decisions in the chances for acceptance of the adopted integration approaches.

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 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.

Automatic Retrieval of Educational ICT Tool Descriptions from the Web of Data

Linked Data is a methodology to publish data on the Web that facilitates the federation of data sources. Following this methodology, a huge quantity of data is being published on the Web of Data, but very little is currently consumed by educational applications. This paper proposes to overcome this situation by relating educational vocabularies to the ones already used on the Web of Data. This way, educational applications can take advantage of the data published on the Web even if such data was not published for educational purposes. As a case study, the vocabulary used by an educational tool search system, called Ontoolsearch, is related to ICT tool descriptions published by DBpedia and Factforge. Evaluation results show that 2905 tool descriptions can be retrieved from the Web of Data to be consumed by Ontoolsearch. In addition, most of these descriptions have a similar quality to the ones manually published by an educational tool expert.

Reuse of Data Flow Designs in Complex and Adaptive CSCL Scripts: A Case Study

Existing Educational Modeling Languages (EML), and especially the IMS LD specification, does not appropriately address data flow among Computer Supported Collaborative Learning (CSCL) activities. Several solutions proposed in the literature, have tackled the important dimensions of data flow automation or the consistency of design, but they have not adequately covered the perspective of reusing scripts. Current data and tools binding specifications do not establish the dependencies between this setting and the structural design of the collaborative data flow situations. This preclude a complete design particularization and raise the issue of reusing data flow designs, which is especially important in the case of complex and adaptive real-world collaborative learning scenarios. This paper presents a case study in which the LeadFlow4LD approach, an IMS LD interoperable solution, is analyzed with respect to the reusability of data flow designs. Besides, the case study is performed using a real-world complex CSCL script in order to illustrate the adaptive characteristics that could be taken into account. Findings show limitations of the current approaches concerning reuse and structural design particularization of the data flow. Additionally an alternative solution based on abstract workflow templates that is briefly outlined in this paper.

Learning Analytics for Professional and Workplace Learning: A Literature Review

Despite the ubiquity of learning in the everyday life of most workplaces, the learning analytics community only has paid attention to such settings very recently. One probable reason for this oversight is the fact that learning in the workplace is often informal, hard to grasp and not univocally defined. This paper summarizes the state of the art of Workplace Learning Analytics (WPLA), extracted from a systematic literature review of five academic databases as well as other known sources in the WPLA community. Our analysis of existing proposals discusses particularly on the role of different conceptions of learning and their influence on the LA proposals’ design and technology choices. We end the paper by discussing opportunities for future work in this emergent field.

Integration of external tools in VLEs with the GLUE! architecture: a case study

This paper presents a case study of the usage of GLUE!, a loosely-coupled architecture that enables the integration of external tools in VLEs. The case study is a collaborative learning situation carried out through a VLE, but involving several external tools. GLUE! is used to instantiate and enact this situation in two authentic experiments. Evaluation results show that GLUE! alleviated educators in the instantiation process, and facilitated the effective collaboration among students. These results are relevant as this is a real situation with a complex structure and groups that change over time.

Reusability of data flow designs in complex CSCL scripts: evaluation results from a case study

Several approaches have addressed the consistency and automatic enactment dimensions of CSCL scripts with data flow, but they have not appropriately tackled the problem of reusing such learning designs. For instance, workflow-based solutions such as LeadFlow4LD only capture particular case behaviors, instead of describing generic data flow situations. This limitation hinders the reusability of these designs because the workflow needs to be adapted for specific technical, teaching and social contexts. This adaptation is complex and time consuming, especially with a large number of students. In order to show the relevance of this problem, this paper analyzes the LeadFlow4LD approach through a real-world complex CSCL script. The study characterizes the reuse effort of CSCL scripts with and without data flow definition, in different social context settings. The findings illustrate how the data flow representation may affect the particularization of complex CSCL scripts, and pave the path for alternative, higher abstraction level representations of data flows, to reduce the reuse effort.

From face-to-face to distance LMS-mediated collaborative learning situations with GLUE!

GLUE! is an integration architecture that allows teachers to easily set up an LMS environment with several external tools to carry out complex collaborative learning situations in distance settings. Though its effectiveness in alleviating the burden on teachers of deploying and enacting such situations has been studied elsewhere, there are no studies in the literature analyzing the impact, in terms of learning achievement, of turning traditional face‐to‐face collaborative learning situations into distance LMS‐mediated ones with the support of integration approaches such as the GLUE! architecture. This paper compares the learning achievement in a distance LMS‐mediated collaborative learning situation supported by GLUE! and in the equivalent face‐to‐face in a non‐technological setting. The conclusions of this comparison, along with the fact that GLUE! significantly reduces the set up effort, suggest that GLUE! is a good choice for turning traditional face‐to‐face collaborative learning situations into distance LMS‐mediated ones without significant negative effects in the learning achievement.