Summary of dissertation project Development and evaluation of feedback-based online tasks for the subject of chemistry

The dropout rates in the entry phase of chemistry degree programmes, which have been persistently high since 2006 at approx. 42 %, reveal the need for action (Heublein et al., 2017). High requirements, an overwhelming amount of material and poor grades are just some of the reasons cited for dropping out. The fact that deficits in prior knowledge are not made up for in the first semester at UDE or at RUB (Averbeck et al., 2017) exacerbates the situation all the more.

In order to increase academic success among students, particularly those with little prior knowledge, this study aims to develop a study offering that takes greater account of individual prior knowledge among students by means of adaptive feedback, since feedback is a not insignificant factor influencing learning processes (Hattie & Timperley, 2007). To this end, students work on solving chemistry-specific online tasks and are provided with automated, error-specific informative tutorial feedback (ITF) as they do so (Narciss, 2006). In addition, the study will also examine the influence of prior knowledge on the learning effectiveness of different ITF components.

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