Digitally-assisted monitoring system (DAMS) and self-regulated learning in Science Education: A mixed-methods study

Date of Publication

11-11-2022

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Educational Psychology

Subject Categories

Science and Mathematics Education

College

Br. Andrew Gonzalez FSC College of Education

Department/Unit

Counseling and Educational Psychology

Thesis Advisor

John Addy S. Garcia

Defense Panel Chair

Ma. Alicia Bustos-Orosa

Defense Panel Member

Christine Joy A. Ballada
Oliver Baltazar Sta. Ana
Jasper Vincent Q. Alontaga
Violeta C. Valladolid

Abstract/Summary

The current Covid-19 pandemic has pushed online learning to the forefront and has become the dominant learning method over traditional face-to-face classes. This mode has allowed students to take an active role in their learning. Because of the autonomy associated with distance learning, self-regulation is essential to the success of online learning. Developing a mechanism and system through a technology-mediated mode to support self-regulation is considered important. For this study, a web-based platform for a Digitally Assisted Monitoring System (DAMS) specifically for students' online homework was developed and used to improve self-regulation. The design for the DAMS was based on the four phases: task definition, goals and plans, implementation of learning strategies, and adaptations of Winne and Hadwin's self-regulated learning theory. To assess the impact of the DAMS on self-regulated learning, this study used a quasi-experimental mixed-design convergence model in a graduate school statistics course.

Pre- and post-assessment surveys, focus groups, interviews, and a thematic analysis of daily reflections were used to assess the impact of self-regulation on academic outcomes. Regulation Learning Questionnaire (RLQ) pre- and post-test results did not differ significantly using Wilcoxon signed rank tests.

In addition, DAMS usability was not significantly different between participants with low SRL and high SRL on all items according to the Unified Theory of Acceptance and Use of Technology (UTAUT) in task understanding, goal setting and planning, monitoring, evaluating, and adapting. Under task understanding, only item 8 (z=-1.9, p = 0.05) showed a significant difference between low SRL and high SRL.

Qualitative topics identified for understanding the task were knowledge of the assigned task and appreciation of the system. The qualitative issues for goal setting and planning were the Time, Action, Standards and Content Framework (TASC), the formulation of goals, and time management. Self-monitoring's preview and feedback features were the qualitative issues for monitoring. An assessment component includes a range of topics: online journal, reassessment of previous approaches, self-monitoring of progress, usefulness of the system, and increased self-confidence. Lastly, under adapting were qualitative topics such as developing suitable strategies and completing the task.

In Qualitative and quantitative outcomes diverged when it came to task understanding, goal setting, monitoring, evaluation, and adaptation. There was no difference between the quantitative and qualitative data for all SRL components before and after the test, while the qualitative data indicated that a digitally assisted monitoring system enabled more detailed and differentiated evaluation of its impact on self-regulating learning.

Keywords: self-regulation, feedback, online learning

Abstract Format

html

Language

English

Format

Electronic

Keywords

Web-based instruction; Regulatory focus (Psychology); Statistics—Study and teaching

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