In dieser Fortsetzungsfolge zum Thema Learning Analytics erläutern Marius Wehner und Lynn Schmodde von der Wirtschaftswissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf das Verbundprojekt Fair Enough. Zur Fairness von Learning Analytics-Systemen legen sie empirische Evaluationsergebnisse verschiedener Stakeholder-Gruppen dar und geben einen Ausblick auf zukünftige Entwicklungen. Interviewer in Folge 12 des DINItus Podcasts ist Erik Reidt vom ZIM/Multimediazentrum der HHU Düsseldorf.
Allen Brown, Ben Croft, Mary Ellen Dello Stritto, Rebecca Heiser, Shannon McCarty, Darragh McNally, Rob Nyland, Josh Quick, Rebecca Thomas and Marla Wilks
EDUCAUSEreview | Wednesday, February 9, 2022
Seit nahezu einer Dekade werden Learning Analytics im Hochschulkontext als Ansatz zum Verständnis sowie zur Optimierung von Lehr-Lern-Prozessen und Lernumgebungen verwendet. Der Beitrag skizziert zentrale Entwicklungslinien von Learning Analytics und geht auf deren Potenziale sowie damit verbundene Fragen zum Datenschutz ein. Basierend auf einer systematischen Übersichtsarbeit und Stakeholderinterviews werden Handlungsempfehlungen für die Implementation von Learning Analytics an Hochschulen vorgestellt. Der Ausblick diskutiert aktuelle Forschungsdesiderata.
In Latin America (LATAM), socioeconomic inequality and lack of resources shape the context of educational institutions in particular ways. Programme quality and dropout rates preoccupy educationalists and governments.
Researchers from Monash University have developed a new model for learning analytics to help developers create better educational technology, following a systematic literature review of learning analytics dashboards.
Whether they’re driven by commercial interests or not, most developers and companies care about positive impact. Of course, impact helps in selling products, but it’s also a key motivation in why people develop and refine technologies: they care about supporting learning.
Learning Analytics (LA) is a new promising field that is attracting the attention of education providers, including teachers, learning designers and academic directors. Researchers and practitioners are interested in learning analytics as it can provide insights from student data, for example, students’ learning processes, automatically identifying learners in need and visualising learners’ behaviour.
It never bodes well to dive into the unknown without preparation. To define, design and enable learning analytics, it’s essential to have a clear strategy in place. Prep yourself with these evaluation questions before you dive into learning analytics.
Learning analytics (LA) is a technology for enabling better decision-making by teachers, students, and other educational stakeholders by providing them with timely and actionable information about learning-in-process on an ongoing basis.
At the 2019 Enterprise Summit, higher education IT, business and finance, and institutional research professionals gathered to explore the future and the promise of analytics. This third in a series of three blog posts discusses the importance of governance, collaboration, and communication to an analytics future.
The emerging configuration of educational institutions, technologies, scientific practices, ethics policies and companies can be usefully framed as the emergence of a new “knowledge infrastructure” (Paul Edwards).
Today, Web Analytics (WA) is commonly used to obtain key information about users and their behavior on websites. Besides, with the rise of online learning, Learning Analytics (LA) emerged as a separate research field for collecting and analyzing learners' interactions on online learning platforms.
This project brought together learning analytics experts from across Australia to explore key ethical issues relating to the development and use of learning analytics in higher education.
College and university libraries can provide important contributions to institutional efforts to use learning analytics to improve student learning and success.
Professor Mark Brown is Director of the National Institute for Digital Learning (NIDL) based at Dublin City University (DCU) interviewed by LACE project's Maren Scheffel at EC-TEL conference in Toledo, Spain, September 2015
To ensure every stakeholder involved in the design and development of autonomous and intelligent systems is educated, trained, and empowered to prioritize ethical considerations so that these technologies are advanced for the benefit of humanity.
The field learning analytics is established with the promise for the education sector to embrace the use of data for decision making. There are many examples of successful use of learning analytics to enhance student experience, increase learning outcomes, and optimize learning environments.
In order not to fail, it is necessary to have a clear vision of what you want to achieve with learning analytics, a vision that closely aligns with institutional priorities.
This presentation targets privacy aspects organisations need to understand and to consider for implementing xAPI and related learning analytics in complex and …
public draft articulating eight principles that all higher education institutions should consider when implementing technology for the collection and use of learning data