learning analyics – e-Learning Blog

Our publication about „Why Will Technology Enhanced Language Learning be Essential for Pupils?“ got published in the Bulletin of the Technical Committee on Learning Technology.
Abstract:

The availability of personal digital devices in schools and at home are offering new ways of engaging students in the area of language learning. In this publication, we present a new approach on writing and blogging for children aged 8 to 12 years, which is especially helpful for those who struggle with the acquisition of German orthography. On a web-based platform the pupils can write essays and blog them later on. Combined with learning analytics methods we offer individualized feedback during the process of writing and a training database with appropriate exercises to support the students‘ autonomous learning.

[Article @ Journal’s Homepage]

[Article @ ResearchGate]

Reference: Ebner, M., Ebner, M., Edtstadler, K. (2019) Why Will Technology Enhanced Language Learning be Essential for Pupils?. Bulletin of the Technical Committee on Learning Technology. 2019/1. pp. 14-17

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

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