2020, Keck, Ingo R., Vidal, Maria-Esther, Heller, Lambert, Mikroyannidis, Alexander, Chang, Maiga, White, Stephen

In this article, we look at the challenges that arise in the use and management of education credentials, and from the switch from analogue, paper-based education credentials to digital education credentials. We propose a general methodology to capture qualitative descriptions and measurable quantitative results that allow to estimate the effectiveness of a digital credential management system in solving these challenges. This methodology is applied to the EU H2020 project QualiChain use case, where five pilots have been selected to study a broad field of digital credential workflows and credential management. Copyright (c) IARIA, 2020

2020, Fahrenkrog, Gabriele, Muuß-Merholz, Jöran, Fabri, Blanche

[No abstract available]

2021, Dessì, Danilo, Käser, Tanja, Marras, Mirko, Popescu, Elvira, Sack, Harald, Dessì, Danilo, Käser, Tanja, Marras, Mirko, Popescu, Elvira, Sack, Harald

The design and delivering of platforms for online education is fostering increasingly intense research. Scaling up education online brings new emerging needs related with hardly manageable classes, overwhelming content alternatives, and academic dishonesty while interacting remotely, as examples. However, with the impressive progress of the data mining and machine learning fields, combined with the large amounts of learning-related data and high-performance computing, it has been possible to gain a deeper understanding of the nature of learning and teaching online. Methods at the analytical and algorithmic levels are constantly being developed and hybrid approaches are receiving an increasing attention. Recent methods are analyzing not only the online traces left by students a posteriori, but also the extent to which this data can be turned into actionable insights and models, to support the above needs in a computationally efficient, adaptive and timely way. In this paper, we present relevant open challenges lying at the intersection between the machine learning and educational communities, that need to be addressed to further develop the field of intelligent systems for online education. Several areas of research in this field are identified, such as data availability and sharing, time-wise and multi-modal data modelling, generalizability, fairness, explainability, interpretability, privacy, and ethics behind models delivered for supporting education. Practical challenges and recommendations for possible research directions are provided for each of them, paving the way for future advances in this field.

2018, Krüger, Nicole, Burblies, Christine, Pianos, Tamara

Recent didactic approaches often focus on the active participation of learners, as Learner Centered Teaching, Flipped Classroom and Gamification. The question is how these techniques can be used in short-terms information literacy courses or within larger groups and whether this makes sense regarding the learning success. This article examines reasons for using activating methods in information literacy trainings and presents various free online tools and group exercises, that can be used to activate learners in training. The tools presented are suitable for training in public and academic libraries.