Wollny, SebastianSchneider, JanRittberger, MarcDrachsler, HendrikPinkwart, NielsKonert, Johannes2019-08-142019-08-142019978-3-88579-691-6https://dl.gi.de/handle/20.500.12116/24394Online educational Portals (OEPs) subsume a field of online repositories for a wide range of stakeholders. They are characterized by easily accessible structures that do not require visitor accounts. Most OEPs therefore provide content in one way to all visitors also known as “one size fits all” approach. With this study, we examine if Web Analytics data can be used to infer the modeling of learners for OEPs. This would be the basis for additional and more personalized ways of providing content to various stakeholders. In order to draw conclusions about opportunities and limitations of Web Analytics in this regard, the data structure of the Fachportal Pädagogik, as one of the largest educational OEPs in Germany, is compared with a common Learner Modeling Framework. The evaluation of the results finally leads to two major challenges that must be overcome in order to achieve personalized content and learning experiences on OEPs.enLearner ModelingPersonalizationAdaptive HypermediaLearning AnalyticsRecommender SystemsOpen Educational ResourcesOnline LibrariesOnline Educational PortalsDigital AssistantsChatbotsText/Conference Paper 10.18420/delfi2019_3481617-5468