Approaching Adaptive Support for Self-Regulated Learning
Seidel, N.
Karolyi, H.
Burchart, M.
de Witt, C.
begutachtete Konferenzbandbeiträge
erschienen in:
Innovations in Learning and Technology for the Workplace and Higher Education
@inproceedings{Seidel2021-SRL, abstract = {Students in distance education are expected to self-regulate their learning process. In this paper, we present a semester planning tool that enables learners to plan, monitor, and reflect on learning tasks over a semester. In this way, Zimmerman's model of self-regulated learning (SRL) could be mapped to an application that can be used in the established Moodle LMS. Furthermore, we introduce the Adaptation Rule Interface for implementing rule-based context-sensitive adaptations in Moodle. As a baseline for adaptive SRL support, we conducted two field studies (N{\thinspace}={\thinspace}157 and N{\thinspace}={\thinspace}93). In both studies, monitoring was used most frequently, while planning was mainly done at the beginning of the semester. Participants preferred to adjust provided milestones, instead of creating their own. Reflection played a minor role. The participants who used the tool extensively reported a strong affinity for time management and content elaboration in the LIST-K inventory. Using cluster analysis, participants with high learning activity and high SRL activity were grouped into one cluster, while the majority of participants combined into a second cluster. Through this empirical investigation of SRL processes, it is possible to design effective adaptive support for self-regulated learning.}, address = {Cham}, author = {Seidel, Niels and Karolyi, Heike and Burchart, Marc and de Witt, Claudia}, booktitle = {Innovations in Learning and Technology for the Workplace and Higher Education}, editor = {Guralnick, David and Auer, Michael E and Poce, Antonella}, isbn = {978-3-030-90677-1}, mendeley-groups = {Projects/APLE I}, pages = {409--424}, publisher = {Springer International Publishing}, title = {{Approaching Adaptive Support for Self-regulated Learning}}, year = {2021} }