Scaffolding self-directed learning with personalized learning goal recommendations

Tobias Ley, Barbara Kump, Cornelia Gerdenitsch

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

17 Citations (Scopus)


Adaptive scaffolding has been proposed as an efficient means for supporting self-directed learning both in educational as well as in adaptive learning systems research. However, the effects of adaptation on self-directed learning and the differential contributions of different adaptation models have not been systematically examined. In this paper, we examine whether personalized scaffolding in the learning process improves learning. We conducted a controlled lab study in which 29 students had to solve several tasks and learn with the help of an adaptive learning system in a within-subjects control condition design. In the learning process, participants obtained recommendations for learning goals from the system in three conditions: fixed scaffolding where learning goals were generated from the domain model, personalized scaffolding where these recommendations were ranked according to the user model, and random suggestions of learning goals (control condition). Students in the two experimental conditions clearly outperformed students in the control condition and felt better supported by the system. Additionally, students who received personalized scaffolding selected fewer learning goals than participants from the other groups.
Original languageEnglish
Title of host publicationUser Modeling, Adaptation, and Personalization
Subtitle of host publication18th International Conference, UMAP 2010, Big Island, HI, USA, June 20-24, 2010, Proceedings
Publication statusPublished - 2010
Externally publishedYes
Event18th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2010 - Big Island, United States
Duration: 20 Jun 201024 Jun 2010
Conference number: 18

Publication series

NameLecture Notes in Computer Science


Conference18th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2010
Abbreviated titleUMAP
Country/TerritoryUnited States
CityBig Island


  • n/a OA procedure


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