Multigraph closeness centrality is the most consistent of the three configurations for correlating closeness with performance, though less robust than degree and eigenvector centralities¶
Claim · All claims
Evidence · 1 study · associationalr2·q3
Currency · newest study 2020 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2023: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q3 i? Multigraph closeness was positively and significantly correlated with performance in eleven of 12 courses (r = 0.57 to 0.74, except C8), while simplified and weighted closeness were significant in fewer courses and sometimes negative. → Mohammed Saqr 2020
Evidence¶
Mohammed Saqr 2020¶
Mohammed Saqr, et al. (2020). Capturing the participation and social dimensions of computer-supported collaborative learning through social network analysis: which method and measures matter? International Journal of Computer-Supported Collaborative Learning 15:227–248. https://doi.org/10.1007/s11412-020-09322-6
q3 · i? · associational · r2
Observational analysis of closeness centrality correlations with performance across the 12 PBL courses in three configurations. Multigraph closeness was significant in eleven courses ("r = 0.57, p < 0.01 to r = 0.74, p < 0.01 except for C8"); simplified was significant in seven raw courses, weighted in only four, and normalized closeness improved consistency.
"The multigraph configuration was positively and significantly correlated with student performance in eleven courses with a correlation coefficient that ranged from r = 0.57, p < 0.01 to r = 0.74, p < 0.01 except for C8 (r = −0.032, p = 0.82)."
Discussion¶
Related Claims¶
- Multigraph indegree centrality is consistently and positively correlated with student performance across 12 PBL courses, with stronger correlations than other configurations in eight courses
- Multigraph outdegree centrality is the most robust participation indicator, with significant positive correlations in all courses, while weighted outdegree was negatively correlated in two courses
- Betweenness centrality shows the least consistent correlation with performance, being largely insignificant or negative across configurations except in one course
- Courses with a low number of forum interactions show inconsistent participation-dimension results, while eigenvector centrality remains robust there.
- Prior SNA studies of centrality-achievement links in CSCL show inconsistent, mostly small-sample results, with betweenness and closeness the most inconsistent measures — related
- In a correlation meta-analysis across 69 course offerings, diffusion-based centralities correlated with academic achievement with high combined coefficients and predictive intervals — a broader claim this one bears on
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
multigraph-closeness-most-consistent-configuration |
title |
Multigraph closeness centrality is the most consistent of the three configurations for correlating closeness with performance, though less robust than degree and eigenvector centralities |
description |
Multigraph closeness centrality is the most consistent of the three configurations for correlating closeness with performance, though less robust than degree and eigenvector centralities |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2020 |
recheck_by |
2023 |
generated |
by process:wiki-ingest on 2026-10-18 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — mohammed-saqr-2020 |
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