Digitale Lehre an und rund um der Technischen Universität Graz
Markus Friedl hat im Rahmen seiner Masterarbeit mobile Applikationen entwickelt, die es Kindern ermöglicht spezielle Übungen zur Erlernung der deutschen Sprache zu machen. Hier die Folien seiner Präsentation:
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Ich habe zusammen mit vielen Kolleginnen und Kollegen im Rahmen einer Arbeitsgruppe des Forums Neue Medien in der Lehre Austria (FNMA) ein Whitepaper zu “Learning Analaytics: Einsatz an österreichischen Hochschulen” erstellt und darf diese heute im Rahmen einer Veranstaltung präsentieren. Hier die Folien dazu:
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Im Rahmen des CAS eLearning Zertifikatkurses darf ich heuer eine neues Modul rund um “Emerging Technologies and Trends” abhalten. Die dafür notwendigen Unterlagen sind hier nochmals übersichtlich dargestellt.
VORMITTAG: EMERGING TECHNOLOGIES – from social to mobile and seamless learning
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NACHMITTAG: EMERGING TRENDS – Learning Analytics, Maker Education & Lernen mit Videos
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Als weiterführende Literatur wird das Lehrbuch für Lernen und Lehren mit Technologien empfohlen mit den entsprechenden Kapiteln, sowie das Kapitel “Mobile Seamless Learning – Die nahtlose Integration mobiler Geräte beim Lernen und im Unterricht“.
Zur Info für Nicht-Teilnehmer/innen: Es handelt sich um einen ganztägigen Workshop.
We contributed to this year “Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference (CD-MAKE 2019)” with a publication titled “Insights into Learning Competence Through Probabilistic Graphical Models“.
Abstract:
One-digit multiplication problems is one of the major fields in learning mathematics at the level of primary school that has been studied over and over. However, the majority of related work is focusing on descriptive statistics on data from multiple surveys. The goal of our research is to gain insights into multiplication misconceptions by applying machine learning techniques. To reach this goal, we trained a probabilistic graphical model of the students’ misconceptions from data of an application for learning multiplication. The use of this model facilitates the exploration of insights into human learning competence and the personalization of tutoring according to individual learner’s knowledge states. The detection of all relevant causal factors of the erroneous students answers as well as their corresponding relative weight is a valuable insight for teachers. Furthermore, the similarity between different multiplication problems – according to the students behavior – is quantified and used for their grouping into clusters. Overall, the proposed model facilitates real-time learning insights that lead to more informed decisions.
[Proceedings online @ Springer]
Reference: Saranti, A., Taraghi, B., Ebner, M., Holzinger, A. (2019) Insights into Learning Competence Through Probabilistic Graphical Models. In: Machine Learning and Knowledge Extraction. Third IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2019, Canterbury, UK, August 26–29, 2019, Proceedings. pp. 250-271
Im Rahmen des ÖFEB-Kongress darf ich heute über Learning Analytics reden – die Folien findet man hier:
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We did an article about “Scheduling Interactions in Learning Videos: A State Machine Based Algorithm” for the first issue of the “International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI)“.
Abstract:
Based on the currently developing trend of so called Massive Open Online Courses it is obvious that learning videos are more in use nowadays. This is some kind of comeback because due to the maxim “TV is easy, book is hard” [1][2] videos were used rarely for teaching. A further reason for this rare usage is that it is widely known that a key factor for human learning is a mechanism called selective attention [3][4]. This suggests that managing this attention is from high importance. Such a management could be achieved by providing different forms of interaction and communication in all directions. It has been shown that interaction and communication is crucial for the learning process [6]. Because of these remarks this research study introduces an algorithm which schedules interactions in learning videos and live broadcastings. The algorithm is implemented by a web application and it is based on the concept of a state machine. Finally, the evaluation of the algorithm points out that it is generally working after the improvement of some drawbacks regarding the distribution of interactions in the video.
[article @ journal’s homepage]
Reference: Wachtler, J., Ebner, M. (2019) Scheduling Interactions in Learning Videos: A State Machine Based Algorithm. IN: International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI). 2019(1). pp. 58-76
We did an article about “Potentials of Chatbots for Spell Check among Youngsters” for the first issue of the “International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI)“.
Abstract:
Chatbots are already being used successfully in many areas. This publication deals with the development and programming of a chatbot prototype to support learning processes. This Chatbot prototype is designed to help pupils in order to correct their spelling mistakes by providing correction proposals to them. Especially orthographic spelling mistake should be recognized by the chatbot and should be replaced by correction suggestions stored in test data.
[article @ journal’s homepage]
Reference: Arifi, J., Ebner, M., Ebner, M. (2019) Potentials of Chatbots for Spell Check among Youngsters. IN: International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI). 2019(1). pp. 77-88
I did an article with a hand of colleagues about “Efforts in Europe for Data-Driven Improvement of Education – A Review of Learning Analytics Research in Six Countries” for the first issue of the “International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI)“.
Abstract:
Information and communication technologies are increasingly mediating learning and teaching practices as well as how educational institutions are handling their administrative work. As such, students and teachers are leaving large amounts of digital footprints and traces in various educational apps and learning management platforms, and educational administrators register various processes and outcomes in digital administrative systems. It is against such a background we in recent years have seen the emergence of the fast-growing and multi-disciplinary field of learning analytics. In this paper, we examine the research efforts that have been conducted in the field of learning analytics in Austria, Denmark, Finland, Norway, Germany, Spain, and Sweden. More specifically, we report on developed national policies, infrastructures and competence centers, as well as major research projects and developed research strands within the selected countries. The main conclusions of this paper are that the work of researchers around Europe has not led to national adoption or European level strategies for learning analytics. Furthermore, most countries have not established national policies for learners’ data or guidelines that govern the ethical usage of data in research or education. We also conclude, that learning analytics research on pre-university level to high extent have been overlooked. In the same vein, learning analytics has not received enough focus form national and European national bodies. Such funding is necessary for taking steps towards data-driven development of education.
[article @ journal’s homepage]
Reference: Nouri, J., Ebner, M., Ifenthaler, D., Saqr, M., Malmberg, J., Khalil, M., Bruun, J., Viberg, O., González, M., Papamitsiou, Z., Berthelsen, U. (2019) Efforts in Europe for Data-Driven Improvement of Education – A Review of Learning Analytics Research in Six Countries. IN: International Journal of Learning Analytics and Artificial Intelligence for Education (iJAI). 2019(1). pp. 8-27
Our article about an important extension for iMooX titled “Learning Analytics Cockpit for MOOC Platforms” got publishes now. Enjoy reading 🙂
Abstract:
Within the sector of education, Learning Analytics (LA) has become an interdisciplinary field aiming to support learners and teachers in their learning process. Most standard tools available for Learning Analytics in Massive Open Online Courses (MOOCs) do not cater to the individual’s conception of where Learning Analytics should provide them with insights and important key figures. We propose a prototype of a highly configurable and customizable Learning Analytics Cockpit for MOOC-platforms. The ultimate goal of the cockpit is to support administrators, researchers, and especially teachers in evaluating the engagement of course participants within a MOOC. Furthermore, comparing learner’s individual activity to course wide average scores should enhance the self-assessment of students, motivate their participation, and boost completion rates. Therefore, several metrics were defined which represent and aggregate learner’s activity. From this predefined list, stakeholders can customize the cockpit by choosing from multiple visualization widgets. Although, the current prototype focuses only on a minimal group of stakeholders, namely administrators and researchers. Therefore, it is designed in a modular, highly configurable and customizable way to ensure future extensibility. It can be strongly carried out that customization is integral to deepen the understanding of Learning Analytic tools and represented metrics, to enhance the student’s learning progress.
Reference: Maier, K., Leitner, P., & Ebner, M. (2019). “Learning Analytics Cockpit for MOOC Platforms”. In Emerging Trends in Learning Analytics. Leiden, Niederlande: Brill | Sense. doi: https://doi.org/10.1163/9789004399273_014
Our publication about “Why Will Technology Enhanced Language Learning be Essential for Pupils?” got published in the Bulletin of the Technical Committee on Learning Technology.
Abstract:
The availability of personal digital devices in schools and at home are offering new ways of engaging students in the area of language learning. In this publication, we present a new approach on writing and blogging for children aged 8 to 12 years, which is especially helpful for those who struggle with the acquisition of German orthography. On a web-based platform the pupils can write essays and blog them later on. Combined with learning analytics methods we offer individualized feedback during the process of writing and a training database with appropriate exercises to support the students’ autonomous learning.
[Article @ Journal’s Homepage]
Reference: Ebner, M., Ebner, M., Edtstadler, K. (2019) Why Will Technology Enhanced Language Learning be Essential for Pupils?. Bulletin of the Technical Committee on Learning Technology. 2019/1. pp. 14-17