How Knowledge Structure and Form Shape Scientific Divergent Thinking: Evidence from Semantic Network Analysis and the Scientific Divergent Application Task

Scientific creativity depends not only on what learners know but also on how knowledge is organized, yet evidence in scientific domains remains limited. Across two experiments, we examined whether knowledge structures predict scientific divergent thinking and whether knowledge form shapes creativity through its effects on these structures. Undergraduate students completed the Scientific Divergent Application Task (SDAT), which requires generating novel applications based on learned scientific principles. In Pilot Experiment (n = 39), semantic memory networks constructed from participants’ knowledge representations revealed that network connectivity and efficiency were positively associated with better SDAT performance, whereas recall accuracy was unrelated. In Experiment 2 (n = 126), holding informational content constant, knowledge forms significantly influenced performance: both associative and schematic knowledge promoted scientific divergent thinking more effectively than case-based knowledge, whereas schematic knowledge further demonstrated advantages in originality and knowledge network connectivity and efficiency. These findings suggest that knowledge organization, rather than retention alone, underlies individual differences in scientific creativity, and that schematic presentation may support creative application by fostering more efficient knowledge structures.

Authors

Institutions

Publication Details

Journal
Journal of Intelligence
Published
2026-06-25
DOI
https://doi.org/10.3390/jintelligence14070118
Primary Topic
Creativity in Education and Neuroscience
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How Knowledge Structure and Form Shape Scientific Divergent Thinking: Evidence from Semantic Network Analysis and the Scientific Divergent Application Task

Peiduo Liu, Yoed N. Kenett, Mujie Ma, Wenjing Yang et al.
Journal of Intelligence
Creativity in Education and Neuroscience
article

How Knowledge Structure and Form Shape Scientific Divergent Thinking: Evidence from Semantic Network Analysis and the Scientific Divergent Application Task

Peiduo Liu, Yoed N. Kenett, Mujie Ma, Wenjing Yang, Wenjin Zhang
article en

Abstract

Scientific creativity depends not only on what learners know but also on how knowledge is organized, yet evidence in scientific domains remains limited. Across two experiments, we examined whether knowledge structures predict scientific divergent thinking and whether knowledge form shapes creativity through its effects on these structures. Undergraduate students completed the Scientific Divergent Application Task (SDAT), which requires generating novel applications based on learned scientific principles. In Pilot Experiment (n = 39), semantic memory networks constructed from participants’ knowledge representations revealed that network connectivity and efficiency were positively associated with better SDAT performance, whereas recall accuracy was unrelated. In Experiment 2 (n = 126), holding informational content constant, knowledge forms significantly influenced performance: both associative and schematic knowledge promoted scientific divergent thinking more effectively than case-based knowledge, whereas schematic knowledge further demonstrated advantages in originality and knowledge network connectivity and efficiency. These findings suggest that knowledge organization, rather than retention alone, underlies individual differences in scientific creativity, and that schematic presentation may support creative application by fostering more efficient knowledge structures.

Journal of IntelligenceVol. 14(7)
Southwest University (CN), Technion – Israel Institute of Technology (IL)
National Natural Science Foundation of China, Southwest University, Fundamental Research Funds for the Central Universities
Quality Education
Openalex Percentile: Top 5%
Creativity in Education and Neuroscience
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.