Logo des Repositoriums

Auflistung nach Schlagwort "Learner Modeling"

1 - 2 von 2
  • Conference poster
    Relation between struggle and learning personality in programming exercises
    (Proceedings of DELFI 2024, 2024) Deriyeva, Alina; Dannath, Jesper; Paaßen, Benjamin
    Personality-related characteristics can have an impact on learning experiences and learning outcomes. Moreover, understanding learning approaches of students can help to make personalized pedagogical decisions. Particularly, this has a potential to improve learning outcomes and mitigate user attrition in digital learning environments (DLEs). We hypothesize that persistent individual characteristics may influence a learners’ tendency to struggle during programming exercises. In a study within a digital learning environment for Python programming (N=55), we evaluated the relation between learners’ self-reported personality characteristics and their tendency to struggle during the exercises. We find that, in our sample, some problem solving approaches and all learning preferences are related to struggle indicators. These results indicate that it may be helpful to include personality-related features, like problem solving strategies, as context information for pedagogical modeling in DLEs.
  • Conference Paper 
    “What can I help you with today?” - Exploring Opportunities of Learner Modeling for Online Educational Portals
    (DELFI 2019, 2019) Wollny, Sebastian; Schneider, Jan; Rittberger, Marc; Drachsler, Hendrik
    Online 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.