Investigating the effects of different levels of students' regulation support on learning process and outcome: In search of the optimal level of support for self-regulated learning
Year: 2024
Type: article
Abstract: Students in higher education who actively manage and control their own learning processes have better learning outcomes, more efficient learning progress, and other non-academic benefits than those who do not. However, students often have poor self-regulation practices, lack reflective thinking, and fail to monitor their learning against defined goals. Therefore, a variety of advanced learning technologies and features have been developed to support students with regulation. Nevertheless, the optimal level of regulation support and the most effective combination of these features remain unestablished in the existing research literature. Therefore, this study employs quantitative research to examine the effectiveness of two learning environments with different levels of self-regulation support (less and more) on students' learning academic outcomes, learning process, and satisfaction. Both variants combine the elements of learning dashboards, goal-setting activity, self-assessment task, reflection support, and personal recommendation, with differences in the level of supporting students' regulation. Our findings reveal that students who received higher levels of self-regulation support tended to be more active readers and visited online learning materials and course overviews more frequently. While they outperformed students in the control group, it's noteworthy that these students did not necessarily outperform their peers who received less support, particularly in the context of self-assessment tasks. This study has also highlighted the need for further research in this area (e.g., self-assessment accuracy), including the development of an instrument that can objectively measure and evaluate the level of self-regulated learning support.
Source: Computers & Education
Institution: FernUniversität in Hagen
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
Estimated APC paid: $4,690
OpenAlex ID: W4392968067