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[publication] Leveraging Learning Analytics in a Personal Learning Environment using Linked Data

Our publication about „Leveraging Learning Analytics in a Personal Learning Environment using Linked Data“ for the Bulletin of the Technical Committee on Learning Technology is now online available.
Abstract:

We report on the reflection of learning activities and revealing hidden information based on tracking user behaviors with Linked Data. With in this work we introduce a case study on usage of semantic context modelling and creation of Linked Data from logs in educational systems like a Personal Learning Environment (PLE) with focus on reflection and prediction of trends in such systems. The case study demonstrates the application of semantic modelling of the activity context, from data collected for over two years from our own developed widget based PLE at Graz University of Technology. We model learning activities using adequate domain ontologies, and query them using semantic technologies as input for visualization which serves as reflection and prediction medium as well for potential technical and functional improvements like widget recommendations. As it will be shown, this approach offers easy interfacing and extensibility on technological level and fast insight on trends in e-learning systems like PLE.

Reference: Softic, S., De Vocht, L., Taraghi, B., Ebner, M., Mannes, E. Van Der Walle, R. (2014) Leveraging Learning Analytics in a Personal Learning Environment using Linked Data, Bulletin of the Technical Committee on Learning Technology, Volume 16, Issue 4, pp. 10-13

[Link to full text]

[publication] Why Learning Analytics for Primary Education Matters!

Our publication about „Why Learning Analytics for Primary Education Matters!“ in the Bulletin of the Technical Committee on Learning Technology is now online availabe.
Abstract:

The ubiquitous availability of applications enables us to offer students opportunities to test and train competences in almost every situation. At Graz University of Technolgy two apps for testing competences in multiplication are developed. They estimate the competence level of every user and adapt to their individual development in this domain. They collect a lot of data during a longer period, which could be used on further research. In the foreground they give feedback in a compact and clearly arranged way to the single student and the teachers of classes. But furthermore the analysis of the data during a longer term showed us, that the process of testing and giving feedback has also an positive effect on learning. We emphasize that this quality in supporting the students could not be achieved by human teachers. Information Technology and Learning Analytics gives them a wider radius to perceive specific behavior and establishes their capacity for storing and processing all the relevant data

Here you can find the whole publication as Open Acess [Link]
Reference: Ebner, M., Schön, M. (2013) Why Learning Analytics in Primary Education Matters!,Bulletin of the Technical Committee on Learning Technology, Karagiannidis, C. & Graf, S (Ed.), Volume 15, Issue 2, April 2013, p. 14-17