[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

[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.

[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

[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

[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