Digitale Lehre an und rund um der Technischen Universität Graz
Robert Gröbl did his masterthesis about „Development of an English vocabulary trainer for German speaking pupils and other beginners of English with focus on learning analytics„. Here you can find his slides of his final presentation:
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Our publication about „Development of an Information System to Enhance Students Reading Literacy“ is published within the new issue of the International Journal of Emerging Technologies in Learning.
Abstract:
The research study at hand aims to answer the question, whether an innovative information system can be implemented that will help to enhance reading literacy of elementary pupils.
Based on predefined reading tests this web-based system evaluates the reading literacy of pupils. It consists of two primary parts; the system that creates and evaluates such reading tests and the test platform itself.
In order to assess the system a field test was conducted. Therefore it was tested in two school classes. In the course of this study reading tests were carried out and retrieved data and results were evaluated.
Despite some minor usability problems, the system performed very well. The test system delivered good estimations of the reading capabilities of single pupils and classes. Of special interest is the system’s analysis of the created reading tests since the system is capable of evaluating reading test according to their difficulty.
Reference: Picher, P., Ebner, M. (2015) Development of an Information System to Enhance Students Reading Literacy, International Journal of Emerging Technologies in Learning (iJET), pp. 15-21, 10 (3), https://dx.doi.org/10.3991/ijet.v10i3.4457
Our publication at this year ED-Media 2015 conference „Learning Analytics: Principles and Constraints“ is now online available.
Abstract:
Within the evolution of technology in education, Learning Analytics has reserved its position as a robust technological field that promises to empower instructors and learners in different educational fields. The 2014 horizon report (Johnson et al., 2014), expects it to be adopted by educational institutions in the near future. However, the processes and phases as well as constraints are still not deeply debated. In this research study, the authors talk about the essence, objectives and methodologies of Learning Analytics and propose a first prototype life cycle that describes its entire process. Furthermore, the authors raise substantial questions related to challenges such as security, policy and ethics issues that limit the beneficial appliances of Learning Analytics processes.
Reference: Khalil, M. & Ebner, M. (2015). Learning Analytics: Principles and Constraints. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2015. pp. 1326-1336. Chesapeake, VA: AACE
Finally we feel very honored that we get an „Outstanding Paper Award“ for this research work:
Im Rahmen seiner Masterarbeit hat sich Matthias um den Einsatz unserer Mathematikapplikationen im Unterricht bemüht. Das Ergebnis mit dem Titel „Learning Analytics-Eine Feldstudie zum Einsatz von Learning-Analytics-Applikationen in der Mathematik“ hat er mit diesen Folien erfolgreich präsentiert:
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Paul hat in seiner Masterarbeit den Lesetrainer entwickelt und diesen dann auch erfolgreich bei der Präsentation seiner Arbeit verteidigt. Hier reiche ich noch die Folien nach:
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Our contribution to this year LAK conference is about the „De-Identification“. Mohammad gave a presentation within the Workshop „Ethics and Privacy in Learning Analytics“. Here can your find his slides:
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Unsere Abteilungen beschäftigt sich nun schon seit einigen Jahren ganz stark mit Learning Analytics in der Primarstufe – angefangen hat es mit dem Einmaleinstrainer, heute haben wir auch einen mehrstelligen Multiplikationstrainer, Plus- und Minustrainer bzw. steht der Divisionstrainer kurz vor dem Start.
Alles findet man unter https://schule.learninglab.tugraz.at und kann frei von allen Schulen genutzt werden. Wir haben dies im Rahmen eines Workshops an der Fachdidaktik Informatik Tagung vorgestellt und dabei dieses Handout verteilt:
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Our publication about „Towards a Learning-Aware Application Guided by Hierarchical Classification of Learner Profiles“ is published as part of the Special Issue on Learning Analytics.
Abstract:
Learner profiling is a methodology that draws a parallel from user profiling. Implicit feedback is often used in recommender systems to create and adapt user profiles. In this work the implicit feedback is based on the learner’s answering behaviour in the Android application UnlockYourBrain, which poses different basic mathematical questions to the learners. We introduce an analytical approach to model the learners‘ profile according to the learner’s answering behaviour. Furthermore, similar learner’s profiles are grouped together to construct a learning behaviour cluster. The choice of hierarchical clustering as a means of classification of learners‘ profiles derives from the observations of learners behaviour. This in turn reflects the similarities and subtle differences of learner behaviour, which are further analysed in more detail. Building awareness about the learner’s behaviour is the first and necessary step for future learning-aware applications.
Reference: Taraghi, B., Saranti, A., Ebner, M., Müller, V., Großmann, A. (2015) Towards a Learning-Aware Application Guided by Hierarchical Classification of Learner Profiles, Journal of Universal Computer Science, vol. 21, no. 1 (2015), 93-109
Our Special Issue about Learning Analytics is published within the Journal of Universal Computer Science. We like to thank all authors and reviewers for their valuable work. All readers we wish an enjoyable reading experience.
Already back in 2006 Retalis et al. proposed their first thoughts on Learning Analytics (LA) and considered interaction analysis as a promising way to better understand the learner’s behavior. A couple of years later, further activities were organized; especially Siemens and Long predicted that the most important factor shaping the future of higher education would be big data and analytics. Just few months later, the Horizon Report also described Learning Analytics as a big trend for the forthcoming years. Since then a number of conferences (for example LAK 11, LAK 12, …) have been organized and different projects have been started as well as the topic has been rising on Google trends. The number of research publications has also increased arbitrarily in different directions; for instance to define the upcoming research field, to gather practical experiences or simply to confine LA from other topics (especially from Educational Data Mining (EDM)) …
Table of Content:
Reference: Ebner, M., Kinshuk, Wohlhart, D., Taraghi, B., Kumar, V. (2015) Editorial: Learning Analytics J.UCS Special Issue, Journal of Universal Computer Science, vol. 21, no. 1 (2015), 1-6
Together with Behnam Taraghi, Anna Saranti and Sandra Schön we discussed and broad together what makes learning analytics smart – from our perspectives and experiences with some years of work (and several publications). Here your will find the whole publication or simply summarized as figure:
Abstract:
Learning Analytics (LA) is an emerging field; the analysis of a large amount of data helps us to gain deeper insights into the learning process. This contribution points out that pure analysis of data is not enough. Building on our own experiences from the field, seven features of smart learning analytics are described. From our point of view these features are aspects that should be considered while deploying LA.
Reference: Martin Ebner, Behnam Taraghi, Anna Saranti, Sandra Schön (2015). Seven features of smart learning analytics – lessons learned from four years of research with learning analytics. In: eLearning Papers, Issue 40, January 2015, pp. 51.55, URL: https://www.openeducationeuropa.eu/en/article/Assessment-certification-and-quality-assurance-in-open-learning_From-field_40_3?paper=164347