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[presentation] Learning Analytics and Spelling Acquisition in German – the Path to Indivdualization in Learning #iderblog #hcii20

Markus presented yesterday his research about „Learning Analytics and Spelling Acquisition in German“ at this year HCII 2020 conference.

[presentation] Learning Analytics and MOOCs #mooc #hcii20 #imoox

Ebru is presenting today her research about „Learning Analytics and MOOCs“ at this year HCII 2020 conference.

[publication] Development of a Dashboard for Learning Analytics in Higher Education #STELA #LearningAnalytics

Our first publication at this year HCII 2017 conference was about „Development of a Dashboard for Learning Analytics in Higher Education“.
Abstract:

In this paper, we discuss the design, development, and implementation of a Learning Analytics (LA) dashboard in the area of Higher Education (HE). The dashboard meets the demands of the different stakeholders, maximizes the mainstreaming potential and transferability to other contexts, and is developed in the path of Open Source. The research concentrates on developing an appropriate concept to fulfil its objectives and finding a suitable technology stack. Therefore, we determine the capabilities and functionalities of the dashboard for the different stakeholders. This is of significant importance as it identifies which data can be collected, which feedback can be given, and which functionalities are provided. A key approach in the development of the dashboard is the modularity. This leads us to a design with three modules: the data collection, the search and information processing, and the data presentation. Based on these modules, we present the steps of finding a fitting Open Source technology stack for our concept and discuss pros and cons trough out the process.

[Publication @ Springer]

[Draft @ ResearchGate]

Reference: Leitner P., Ebner M. (2017) Development of a Dashboard for Learning Analytics in Higher Education. In: Zaphiris P., Ioannou A. (eds) Learning and Collabo- ration Technologies. Technology in Education. LCT 2017. Lecture Notes in Computer Science, vol 10296. pp. 293-301 Springer, Cham

[publication] Learning Analytics and Spelling Acquisition in German – Proof of Concept #TEL #Iderblog

Our second publication at this year HCII 2017 conference was about „Learning Analytics and Spelling Acquisition in German – Proof of Concept“ and describes our IDeRBlog-project.
Abstract:

German orthography is known to be quite difficult to master, especially for primary-school pupils in writing texts [cf. 1]. In order to support children with the acquisition of German orthography, we are developing a web-based platform for German-speaking users based on learning analytics techniques. Our goal is to motivate pupils age 8 to 12 to improve their spelling abilities by writing texts and by the possibility to publish them. Concerning spelling in combination with learning analytics the system provides – in case of an orthographic mistake – a specific feedback that encourages pupils to think about the spelling and to correct it. Based on occurred mistakes the teachers and the students are provided with a qualitative analysis of the mistakes. This analysis shows the problematic orthographic areas and gives suggestions for online and offline exercises as well as online courses that are explaining the orthographic phenomena. The aim of this article is to describe the architecture of the web-based system and a proof of concept by evaluating 60 essays. Furthermore, relevant background information is given in order to gain a better understanding in the complex interdisciplinary development.

[Publication @ Springer]

[Draft @ ResearchGate]

Reference: Ebner M., Edtstadler K., Ebner M. (2017) Learning Analytics and Spelling Acquisition in German – Proof of Concept. In: Zaphiris P., Ioannou A. (eds) Learning and Collaboration Technologies. Technology in Education. LCT 2017. Lecture Notes in Computer Science, vol 10296. pp. 257-268. Springer, Cham

[publication] Learning Analytics and Spelling Acquisition in German-A First Prototype #IdERblog

At this year HCII conference we present a short overview about the IderBlog-project, titled „Learning Analytics and Spelling Acquisition in German-A First Prototype

Abstract:

Data-driven learning in combination with emerging academic areas such as Learning Analytics (LA) has the potential to tailor students’ education to their needs [1]. The aim of this article is to present a web-based training platform for primary school pupils who struggle with the acquisition of German orthography. Our objective is the improvement in their writing and spelling competences. The focus of this article is on the development of the platform and the details concerning the requirements and the design of the User Interface (UI). In combination with Learning Analytics, the platform is expected to provide deeper insight into the process of spelling acquisition. Furthermore, aspects of Learning Analytics will help to develop the platform, to improve the exercises and to provide better materials in the long run.

[Draft version @ ResearchGate]

Reference: Ebner, M., Ebner, M., Edtstadler, K. (2016) Learning Analytics and Spelling Acquisition in German-A First Prototype. International Conference on Learning and Collaboration Technologies. pp. 405-416. Springer International Publishing

[presentation] Learning Analytics and Spelling Acquisition in German – A First Prototype #iderblog

Markus presented our research work titled „Learning Analytics and Spelling Acquisition in German – A First Prototype“ at the 18th International Conference on Human-Computer Interaction (HCII) in Toronto. Here are his slides:

[publication] Finding and Exploring Commonalities Between Researchers Using the ResXplorer

Our publication about „Finding and Exploring Commonalities Between Researchers Using the ResXplorer“ at this year HCII conference in Crete, Greece is now online available.
Abstract:

Researcher community produces a vast of content on the Web. We assume that every researcher interest oneself in events, persons and findings of other related community members who share the same interest. Although research related archives give access to their content most of them lack on analytic services and adequate visualizations for this data. This work resides on our previous achievements we made on semantically and Linked Data driven search and user inter- faces for Research 2.0. We show how researchers can find and visually explore commonalities between each other within their interest domain, by introducing for this matter the user interface of “ResXplorer”, and underlying search infrastructure operating over Linked Data Knowledge Base of research resources. We discuss and test most important com- ponents of “ResXplorer” relevant for detecting commonalities between researchers, closing up with conclusions and outlook for future work.

Reference: Softic, S., De Vocht, L., Mannens, E., Van de Walle, R., Ebner, M. (2014). Finding and Exploring Commonalities Between Researchers Using the ResXplorer. Learning and Collaboration Technologies. Technology-Rich Environments for Learning and Collaboration. Panayiotis, Z., Ioannou, A. (Ed.) Lecture Notes in Computer Science, Volume 8524. Springer, pp. 486-494

[publication] Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication

Our second publication at this year HCII conference in Crete, Greece is about „Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication„.
Abstract:

In this work we focus on a specific application named “1×1 trainer” that has been designed to assist children in primary school to learn one digit multiplications. We investigate the database of learners’ answers to the asked questions by applying Markov chain and classification algorithms. The analysis identifies different clusters of one digit multiplication problems in respect to their difficulty for the learners. Next we present and discuss the outcomes of our analysis considering Markov chain of different orders for each question. The results of the analysis influence the learning path for every pupil and offer a personalized recommendation proposal that optimizes the way questions are asked to each pupil individually.

Reference: Taraghi, B., Saranti, A., Ebner, M., Schön, M. (2014) Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication. Learning and Collaboration Technologies. Designing and Developing Novel Learning Experiences. Panayiotis, Z., Ioannou, A. (Ed.), Springer Lecture Notes, pp. 322-322

[publication] Attention Profiling Algorithm for Video-based Lectures

Our first publication at this year HCII conference in Crete, Greece about „Attention Profiling Algorithm for Video-based Lectures“ is now online available as prelimiary version. The slides are already published here.
Abstract:

Due to the fact that students‘ attention is the most crucial resource in a high-quality course it is from high importance to control and analyze it. This could be done by using the interaction and the communication because they are known as valuable influencing factors of the attention. In this publication we introduce a web-based information system which implements an attention-profiling algorithm for learningvideos
as well as live-broadcastings of lectures. For that different methods of interaction are offered and analyzed. The evaluation points out that the attention profiling algorithm delivers realistic values.

Reference: Wachtler, J., Ebner, M., Taraghi, B. (2014). Attention Profiling Algorithm for Video-based Lectures. Learning and Collaboration Technologies. Designing and Developing Novel Learning Experiences. Panayiotis, Z., Ioannou, A. (Ed.), Springer Lecture Notes, pp. 358-367

[presentation] Finding and Exploring Commonalities between Researchers Using the ResXplorer

Our presentation at this year HCII Conference in Crete, Greece about „Finding and Exploring Commonalities between Researchers Using the ResXplorer“ is now online available – enjoy the slides 🙂