TY - JOUR
KW - Learning Analytics
KW - Virtual Vocational Training
KW - Blended Learning
AU - Ralf Klamma
AU - de Peter Lange
AU - Alexander Tobias Neumann
AU - Petru Nicolaescu
AB - Virtual training centers are hosted solutions for the implementation of training courses in the form of e.g. Webinars. Many existing centers neglect the informal and social dimension of vocational training as well as the legitimate business interests of training providers and companies sending their employees. In this paper, we present the virtual training center platform V3C that blends formal, certified virtual training courses with self-regulated and social learning in synchronous and asynchronous learning phases. We have developed an integrated learning analytics approach to collect, store, analyze and visualize data for different purposes like certification, interventions and gradual improvement of the platform. The results given here demonstrate the ability of the platform to deliver data for key performance indicators like learning outcomes and drop-out rates as well as the interplay between synchronous and asynchronous learning phases on a very large scale. Since the platform implementation is open source, results can be easily transferred and exploited in many contexts.
IS - Special Issue on Big Data and Open Education
M1 - 2
N2 - Virtual training centers are hosted solutions for the implementation of training courses in the form of e.g. Webinars. Many existing centers neglect the informal and social dimension of vocational training as well as the legitimate business interests of training providers and companies sending their employees. In this paper, we present the virtual training center platform V3C that blends formal, certified virtual training courses with self-regulated and social learning in synchronous and asynchronous learning phases. We have developed an integrated learning analytics approach to collect, store, analyze and visualize data for different purposes like certification, interventions and gradual improvement of the platform. The results given here demonstrate the ability of the platform to deliver data for key performance indicators like learning outcomes and drop-out rates as well as the interplay between synchronous and asynchronous learning phases on a very large scale. Since the platform implementation is open source, results can be easily transferred and exploited in many contexts.
PY - 2018
SP - 32
EP - 38
T2 - International Journal of Interactive Multimedia and Artificial Intelligence
TI - An Integrated Learning Analytics Approach for Virtual Vocational Training Centers
UR - http://www.ijimai.org/journal/sites/default/files/files/2018/02/ijimai_5_2_4_pdf_97157.pdf
VL - 5
SN - 1989-1660
ER -