Learning Analytics

Dieser Beitrag beschreibt die Ziele, Methoden und Interessengruppen von Learning Analytics. Darüberhinaus werden die unterschiedlichen Struktu- ren der Daten von Big Data und Learning Analytics betrachtet. Dargestellt werden ferner die Planung des Einsatzes von Learning Analytics und die Phasen der technischen Implementierung.

Development of a Dashboard for Learning Analytics in Higher Education

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.

Learning Analytics in Hochschulen

Unter dem Schlagwort “Big Data” hat sich in den letzten Jahren ein neues Forschungsfeld etabliert. Es handelt sich dabei um Datenmengen, die wegen ihrer Größe, hohen Komplexität, schnellen Vergänglichkeit oder schwachen Strukturierung mit klassischen Methoden der Datenverarbeitung nicht ausgewertet werden können. Das Ziel von Learning Analytics besteht darin solche Datenmengen im Kontext von Lehren und Lernen zu sammeln, zu analysieren und zu interpretieren um neue Erkenntnisse zu gewinnen. Ein wesentlicher Punkt dabei ist die Rückführung des gewonnen Wissens an die Lehrenden und Lernenden, um das Lehr- und Lernverhalten individueller und optimierter zu gestalten und die Entwicklung von Kompetenzen in dem Bereich zu fördern. In diesem Kapitel werden die Möglichkeiten von Learning Analytics genauer erläutert, um dann den Schwerpunkt Learning Analytics in Hochschulen näher zu beleuchten.

Learning Analytics in Higher Education – A Literature Review

This chapter looks into examining research studies of the last five years and presents the state of the art of Learning Analytics (LA) in the Higher Education (HE) arena. Therefore, we used mixed-method analysis and searched through three popular libraries, including the Learning Analytics and Knowledge (LAK) conference, the SpringerLink, and the Web of Science (WOS) databases. We deeply examined a total of 101 papers during our study. Thereby, we are able to present an overview of the different techniques used by the studies and their associated projects. To gain insights into the trend direction of the different projects, we clustered the publications into their stakeholders.

Successful transition from secondary to higher education using learning analytics

The economic and financial crisis is having an important socio-economic effect in Europe and is threatening Europe’s economic growth model and employment and the sustainability of Europe’s welfare model. To counter the crisis, Europe should further evolve to a knowledge- driven and technology-based economy. This evolution however causes a rise in the demand for personnel with post-secondary education diploma, since many jobs in such a knowledge en technology-drive economy require at least a postsecondary education (Carnevale & Desrochers 2003). However, during the transition from secondary to higher education a lot of high-potential students drop out (Banger 2008).