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[publication] Learning Analytics and MOOCs #imoox #hci20 #research

Ebru did a first publication of her PhD-work titled „Learning Analytics and MOOCs“ for this year HCII conference.

Abstract:
There are new discoveries in the field of educational technologies in the 21st century, which we can also call the age of technology. Learning Analytics (LA) has given itself an important research field in the area of Technology Enhanced Learning. It offers analysis, benchmarking, review and development techniques for example in online learning platforms such as those who host Massive Open Online Course (MOOC). MOOCs are online courses addressing a large learning community. Among these participants, large data is obtained from the group with age, gender, psychology, community and educational level differences. These data are gold mines for Learning Analytics. This paper examines the methods, benefits and challenges of applying Learning Analytics in MOOCs based on a literature review. The methods that can be applied with the literature review and the application of the methods are explained. Challenges and benefits and the place of learning analytics in MOOCs are explained. The useful methods of Learning Analytics in MOOCs are described in this study. With the literature review, it indicates: Data mining, statistics and mathematics, Text Mining, Semantics-Linguistics Analysis, visualization, Social network analysis and Gamification areas are implementing Learning Analytics in MOOCs allied with benefits and challenges.

Abstract of the publication

[full article @ publisher’s webpage]
[draft @ researchgate]

Reference: İnan E., Ebner M. (2020) Learning Analytics and MOOCs. In: Zaphiris P., Ioannou A. (eds) Learning and Collaboration Technologies. Designing, Developing and Deploying Learn- ing Experiences. HCII 2020. Lecture Notes in Computer Science, vol 12205. Springer, Cham. pp. 241-254

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[publication] Learning Analytics in der Schule – Anforderungen an Lehrerinnen und Lehrer #tugraz #LearningAnalytics

Unser Beitrag zu „Learning Analytics in der Schule – Anforderungen an Lehrerinnen und Lehrer“ wurden nun in einem tollen Buch über „Bildung und Digitalisierung“ publiziert.

Zusammenfassung:
Dieser Beitrag ermöglicht eine kurze Einführung in das Themenfeld Learning Analytics mit einem besonderen Blick auf den Schulunterricht. Heute erscheint es noch weit entfernt, bis derartige Anwendungen im deutschsprachigen Raum flächendeckend Fuß fassen können. Durch die voranschreitende Technologie werden jedoch solche Anwendungen und die Auseinandersetzung mit der Frage, inwieweit künstliche Intelligenz Aspekte der eigentlichen Lehre ergänzen und erset-zen kann, zunehmend zum Diskussionsgegenstand. Die vorliegende Publikation zielt darauf ab, Learning Analytics selbst und die damit verbundenen Herausforderungen zu definieren. Anschlie-ßend werden einige allgemeine Beispiele genannt, ehe auf zwei webbasierte Informationssysteme im Detail eingegangen wird-dem Einmaleins-Trainer und dem Programm zum Aufbau von Schreibkompetenz IDeRblog. Auf Basis der dort gewonnen Erkenntnisse und Erfahrungen werden drei wesentliche Anforderungen für Lehrerinnen und Lehrer abgleitet: statistische und digitale Kom-petenz sowie grundsätzliches Wissen im Bereich Datenschutz. Der Beitrag schließt mit der Frage, inwieweit diese zukünftig in die Lehrerbildung integriert werden können und müssen.

[Link Vorabzug @ ResearchGate]

Referenz: Ebner, M., Leitner, P., Ebner, M. (2020) Learning Analytics in der Schule – Anforderungen an Lehrerinnen und Lehrer. In: Bildung und Digitalisierung- Auf der Suche nach Kompetenzen und Performanzen. Trültzsch-Wijnen, C., Brandhofer, G. (Hrsg.). S. 255-272. Nomos. ISBN 978-3-8487-6538-6

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[publication] Implementation of Interactive Learning Objects for German Language Acquisition in Primary School based on Learning Analytics Measurements #edil2020 #tugraz #alexa #TEL

At this year EDMedia conference (online) we did a publication about „Implementation of Interactive Learning Objects for German Language Acquisition in Primary School based on Learning Analytics Measurements“.

Abstract:
Obviously, reading and writing are important qualities nowadays, likely more so than ever before. Whether that be in school, work or everyday life, it is a skill set that is omnipresent. This is also evident by the countless contributions that are created and published on various online platforms such as Facebook, Twitter, YouTube or WhatsApp. In order to avoid being misunderstood, it is crucial to have the ability to express one’s written thoughts in a structured and error-free manner. To help children in the early age with their spelling skills, the IDeRBlog platform provides a possibility to reach their goals and support their German spelling learning process. On this platform children can create own blog entries which are then corrected by teachers and an intelligent dictionary before they can finally publish it. Mistakes made by the kids are evaluated and on basis of these mistakes, exercises can be recommended so that the kids can improve their spelling. This paper will present these exercises (also called learning objects), which should help children to practice writing, reading and also listening carefully. It focuses not only on the evaluation setup and process but also results will be explained in the end.

[Draft @ ResearchGate]

Reference: Burazer, M., Ebner, M. & Ebner, M. (2020). Implementation of Interactive Learning Objects for German Language Acquisition in Primary School based on Learning Analytics Measurements. In Proceedings of EdMedia + Innovate Learning (pp. 672-679). Online, The Netherlands: Association for the Advancement of Computing in Education (AACE).

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[publication] Web Analytics as Extension for a Learning Analytics Dashboard of a Massive Open Online Platform #imoox #learninganalytics #tugraz #reseach

Our research about „Web Analytics as Extension for a Learning Analytics Dashboard of a Massive Open Online Platform“ got published.

Abstract:
Massive open online courses (MOOCs) provide anyone with Internet access the chance to study at university level for free. In such learning environments and due to their ubiquitous nature, learners produce vast amounts of data representing their learning process. Learning Analytics (LA) can help identifying, quantifying, and understanding these data traces. Within the implemented web-based tool, called LA Cockpit, basic metrics to capture the learners’ activity for the Austrian MOOC platform iMooX were defined. Data is aggregated in an approach of behavioral and web analysis as well as paired with state-of-the-art visualization techniques to build a LA dashboard. It should act as suitable tool to bridge the distant nature of learning in MOOCs. Together with the extendible design of the LA Cockpit, it shall act as a future proof framework to be reused and improved over time. Aimed toward administrators and educators, the dashboard contains interactive widgets letting the user explore their datasets themselves rather than presenting categories. This supports the data literacy and improves the understanding of the underlying key figures, thereby helping them generate actionable insights from the data. The web analytical feature of the LA Cockpit captures mouse activity in individual course-wide heatmaps to identify regions of learner’s interest and help separating structure and content. Activity over time is aggregated in a calendar view, making timely reoccurring patterns otherwise not deductible, now visible. Through the additional feedback from the LA Cockpit on the learners’ behavior within the courses, it will become easier to improve the teaching and learning process by tailoring the provided content to the needs of the online learning community.

abstract of article

[article @ book’s homepage]
[draft @ ResearchGate]

Reference: Leitner P., Maier K., Ebner M. (2020) Web Analytics as Extension for a Learning Analytics Dashboard of a Massive Open Online Platform. In: Ifenthaler D., Gibson D. (eds) Adoption of Data Analytics in Higher Education Learning and Teaching. Advances in Analytics for Learning and Teaching. Springer, Cham. https://doi.org/10.1007/978-3-030-47392-1_19

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[publication] Property-Based Testing for Parameter Learning of Probabilistic Graphical Models #machinelearning #learninganalytics

Thanks to my colleagues – we did a publication for this year CDMAKE-conference about „Property-Based Testing for Parameter Learning of Probabilistic Graphical Models„.

Abstract:
Code quality is a requirement for successful and sustainable software development. The emergence of Artificial Intelligence and data driven Machine Learning in current applications makes customized solutions for both data as well as code quality a requirement. The diversity and the stochastic nature of Machine Learning algorithms require different test methods, each of which is suitable for a particular method. Conventional unit tests in test-automation environments provide the common, well-studied approach to tackle code quality issues, but Machine Learning applications pose new challenges and have different requirements, mostly as far the numerical computations are concerned. In this research work, a concrete use of property-based testing for quality assurance in the parameter learning algorithm of a probabilistic graphical model is described. The necessity and effectiveness of this method in comparison to unit tests is analyzed with concrete code examples for enhanced retraceability and interpretability, thus highly relevant for what is called explainable AI.

abstract of the article

[publication @ book homepage]
[draft @ ResearchGate]

Reference: Saranti A., Taraghi B., Ebner M., Holzinger A. (2020) Property-Based Testing for Parameter Learning of Probabilistic Graphical Models. In: Holzinger A., Kieseberg P., Tjoa A., Weippl E. (eds) Machine Learning and Knowledge Extraction. CD-MAKE 2020. Lecture Notes in Computer Science, vol 12279. Springer, Cham. https://doi.org/10.1007/978-3-030-57321-8_28

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[publication] Learning Analytics and Spelling Acquisition in German – The Path to Individualization in Learning #hcii20 #iderblog

We did a contribution titled „Learning Analytics and Spelling Acquisition in German – The Path to Individualization in Learning“ for this year HCII conference.

Abstract:
This paper shows how Learning Analytic Methods are combined with German orthography in the IDeRBlog-project (www.iderblog.eu). After a short introduction to the core of the platform – the intelligent dictionary – we focus on the presentation and evaluation of a new training format. The aim of this format is, that pupils can train misspelled words individually in a motivating and didactic meaningful setting. As a usability test was run with twenty one third graders, we are able to present the results of this evaluation.

Abstract of the publication

[full article @ publisher’s webpage]
[draft @ researchgate]

Reference: Ebner M., Edtstadler K., Ebner M. (2020) Learning Analytics and Spelling Acquisition in German – The Path to Individualization in Learning. In: Zaphiris P., Ioannou A. (eds) Learning and Collaboration Technologies. Designing, Developing and Deploying Learning Experiences. HCII 2020. Lecture Notes in Computer Science, vol 12205. Springer, Cham. pp. 317-325.

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[publication] Individualized Differentiated Spelling with Blogs – Implementing and Individualizing (IDeRBlog ii) #iderblog #hcii2020 #tugraz

We did a contribution titled „Individualized Differentiated Spelling with Blogs – Implementing and Individualizing (IDeRBlog ii)“ for this year HCII conference.

Abstract:
The paper depicts the Erasmus+ project “Individual DifferEntiated correct writing with Blogs – Individualizing and Implementing (IDeRBlog ii)”. IDeRBlog ii is a follow-up project evolving the result of IDeRBlog, a blogging platform for pupils aged eight and above. The project is an international cooperation between 3 countries in Europe. This paper presents an overview of possibilities in context of individualization of the exercises. Further, it covers the benefits of using the platform, e.g. learning about media competences, how to communicate online and the possibility to get individualized exercises for supported during their writing process by the feedback of the intelligent dictionary.

Abstract of the publication

[full article @ publisher’s webpage]
[draft @ researchgate]

Reference: Leidinger N., Gros, M., Ebner, M., Ebner, M., Edtstadler, K. Herunter, E., Heide J., Pfeifer, S., Huppertz, A. & Kistemann V. (2020) Individualized Differentiated Spelling with Blogs – Implementing and Individualizing (IDeRBlog ii). In: Zaphiris P., Ioannou A. (eds) Learning and Collaboration Technologies. Designing, Developing and Deploying Learning Experiences. HCII 2020. Lecture Notes in Computer Science, vol 12205. Springer, Cham. pp. 368-279