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Analytics of self-regulated learning scaffolding: effects on learning processes.

Tongguang Li1, Yizhou Fan2,3, Yuanru Tan4

  • 1Faculty of Information Technology, Monash University, Clayton, VIC, Australia.

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|August 21, 2023
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Summary
This summary is machine-generated.

Adaptive scaffolding enhances self-regulated learning (SRL) by promoting task-guided processes. This study used ordered network analysis to show adaptive scaffolding leads to different SRL patterns compared to fixed scaffolding or no scaffolding.

Keywords:
SRL processSRL scaffoldingordered network analysissegmentation analysisself-regulated learning

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Area of Science:

  • Educational Psychology
  • Learning Sciences
  • Human-Computer Interaction

Background:

  • Self-regulated learning (SRL) is crucial for academic success, involving cognitive, metacognitive, motivational, and emotional regulation.
  • Real-time scaffolding can support SRL, but research often overlooks adaptive scaffolding tailored to learner actions.
  • Previous studies have not clearly distinguished adaptive from fixed scaffolding effects or analyzed scaffolding at granular time segments.

Purpose of the Study:

  • To investigate the impact of adaptive scaffolding on self-regulated learning (SRL) processes during a multi-source writing task.
  • To compare the effects of adaptive scaffolding, fixed scaffolding, and a control condition on SRL patterns.
  • To utilize ordered network analysis (ONA) to model and visualize SRL changes in relation to scaffolding interventions at task and segment levels.

Main Methods:

  • Collected trace data of student activities during a multi-source writing task.
  • Employed ordered network analysis (ONA), a learning analytic technique, to model and visualize SRL processes.
  • Analyzed differences in SRL patterns between adaptive scaffolding, fixed scaffolding, and control groups at both task and segment levels.

Main Results:

  • Learners receiving adaptive scaffolding demonstrated significantly different SRL process patterns compared to fixed scaffolding and control groups at the task level.
  • At the task segment level, adaptive scaffolding was associated with earlier engagement in SRL processes, though not statistically significant.
  • Adaptive scaffolding promoted more task-guided learning behaviors, such as referencing instructions and rubrics, across reading and writing activities.

Conclusions:

  • Adaptive scaffolding significantly influences self-regulated learning processes, leading to more task-guided learning behaviors.
  • Ordered network analysis (ONA) is an effective tool for evaluating the nuanced effects of different scaffolding types on SRL.
  • Future research should consider the impact of scaffolding at various analytical levels to better understand its influence on learning.