@article {2015,
	title = {Analysing content and patterns of interaction for improving the learning design of networked learning environments},
	journal = {British Journal of Educational Technology},
	year = {2015},
	month = {03/2015},
	abstract = {<p>Learning Analytics constitutes a key tool for supporting Learning Design and teacher-led inquiry into student learning. In this paper, we demonstrate how a Social Learning Analytics toolkit can combine social network analysis and content analysis for supporting a global and formal teacher inquiry. This toolkit not only supports teachers in improving the organisation of the learning process but also generates important input to improve the students{\textquoteright} reflection on their own learning. Our examples show how combinations of different levels of analysis can provide deep insight in the learning process. We report a case study that exemplifies the main features of our approach and the kind of outcomes that can be obtained. Commenting and rating processes on videos are analysed based on user traces from a social learning platform. Finally, we point out implications on the learning design for networked learning environments in general.</p>
},
	issn = {1467-8535},
	doi = {10.1111/bjet.12264},
	url = {http://dx.doi.org/10.1111/bjet.12264},
	author = {Haya, Pablo A. and Daems, Oliver and Malzahn, Nils and Castellanos, Jorge and H. Ulrich Hoppe}
}
@conference {2014,
	title = {Artifact Analysis around Video Creation in Collaborative STEM Learning Scenarios},
	booktitle = {2014 IEEE 14th International Conference on Advanced Learning Technologies},
	year = {2014},
	address = {Athens, Greece},
	keywords = {Conceptual change, Network text analysis, STEM learning, Video-based learning},
	doi = {10.1109/ICALT.2014.116},
	url = {http://dx.doi.org/10.1007/s40692-014-0013-y},
	author = {Melanie Erkens and Oliver Daems and Hoppe, H.Ulrich}
}
