- LSF ID
- 53926
- ORCID
- 0000-0001-7302-3607
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
korrespondierende*r Autor*in
- LSF ID
- 60008
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
- GND
- 173940544
- LSF ID
- 48192
- ORCID
- 0000-0001-8866-6971
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
- GND
- 131968599
- LSF ID
- 11384
- ORCID
- 0000-0002-3761-1409
- Sonstiges
- der Hochschule zugeordnete*r Autor*in
Abstract in Englisch:
For various reasons, students receive less formative feedback at post-secondary institutions compared to secondary school. Considering feedback as one of the most important influencing factors on learning processes, formative feedback is a promising approach to improving students’ performances. In this context, new technologies, such as learning management systems (LMS) or intelligent tutoring systems (ITS), can make a valuable contribution to improving higher education teaching by providing automated and individualized error-specific just-in-time (JIT) feedback. However, the digitalization especially of paper-based open-ended tasks that can be used by LMS is currently still associated with a loss of quality. In this paper, we present an approach that allows us to transfer open-ended paper-based tasks in the field of chemistry into online tasks without losing quality and provide large university courses with automated and individualized error-specific JIT feedback. Results of a study of 238 first-year chemistry students reveal that the automated individualized error-specific JIT feedback had a significant positive influence on students’ performance.