Scaffolding Reshapes Dialogic Engagement in Collaborative Problem Solving: Comparative Analysis of Two Approaches

2025-12-08

AI Summary

This study addresses the gap in understanding how instructional scaffolding intensity differentially influences K–12 students’ dialogic engagement and behavioral distributions across phases of collaborative problem solving (CPS). Moving beyond static, aggregate analyses, we innovatively integrate heterogeneous interaction network analysis (HINA) with sequential pattern mining (SPM) to model multilevel, phase-sensitive interaction dynamics in authentic classroom settings. Results reveal a trade-off: strong scaffolding broadens overall participation but induces behavioral scriptification, whereas weak scaffolding enhances task focus and solution-oriented actions yet increases redundancy and off-task social digressions. Crucially, scaffolding intensity exerts structural regulation over CPS processes—shaping both interaction topology and behavioral sequencing—thereby uncovering phase-dependent mechanisms of scaffold efficacy. These findings provide empirical grounding and a methodological framework for designing adaptive, phase-aware instructional interventions in CPS learning environments.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Intelligent Robots: Behavior Learning & Control

Application Category

• Web Mining and Content Analysis: Bridging structured and unstructured data
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Supporting learners during Collaborative Problem Solving (CPS) is a necessity. Existing studies have compared scaffolds with maximal and minimal instructional support by studying their effects on learning and behaviour. However, our understanding of how such scaffolds could differently shape the distribution of individual dialogic engagement and behaviours across different CPS phases remains limited. This study applied Heterogeneous Interaction Network Analysis (HINA) and Sequential Pattern Mining (SPM) to uncover the structural effects of scaffolding on different phases of the CPS process among K-12 students in authentic educational settings. Students with a maximal scaffold demonstrated higher dialogic engagement across more phases than those with a minimal scaffold. However, they were extensively demonstrating scripting behaviours across the phases, evidencing the presence of overscripting. Although students with the minimal scaffold demonstrated more problem solving behaviours and fewer scripting behaviours across the phases, they repeated particular behaviours in multiple phases and progressed more to socialising behaviours. In both scaffold conditions, problem solving behaviours rarely progressed to other problem solving behaviours. The paper discusses the implications of these findings for scaffold design and teaching practice of CPS, and highlights the distinct yet complementary value of HINA and SPM approaches to investigate students' learning processes during CPS.

Problem

• Examining how scaffolding shapes dialogic engagement in CPS
• Comparing maximal vs minimal scaffolds' effects on student behaviors
• Analyzing behavior distribution across CPS phases using HINA and SPM

Innovation

• Applied Heterogeneous Interaction Network Analysis to study scaffolding effects
• Used Sequential Pattern Mining to analyze dialogic engagement phases
• Compared maximal versus minimal scaffolds in collaborative problem solving