Menze, DennisSeidel, NielsKasakowskij, ReginaHenning, Peter A.Striewe, MichaelWölfel, Matthias2022-08-232022-08-232022978-3-88579-716-6https://dl.gi.de/handle/20.500.12116/38819Reading and assessment are elementary activities for knowledge acquisition in online learning. Assessments represented as quizzes can help learners to identify gaps in their knowledge and understanding, which they can then overcome by reading the corresponding text-based course material. Reversely, quizzes can be used to evaluate reading comprehension. In this paper, we examine the interactions between reading and quiz activities using scroll and log data from an online undergraduate course (N=142). By analyzing processes and sequential patterns in user sessions, we identified six session clusters for characteristic reading and quiz patterns potentially relevant for adaptive learning support. Using these session clusters, we further clustered students by their reading and quiz behavior over six time periods within the semester. The results hypothesize a personalization for seven groups of learners characterized by their temporal activity and predominant quiz and reading behavior.enreading analyticslearning analyticsassessmentsequential pattern miningText/Conference Paper10.18420/delfi2022-0111617-5468