Latent Class Analysis identifies six provisional manager typologies with heterogeneous readiness and barrier profiles¶
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Evidence · 1 study (2 entries) · associationalr1·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change
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.
q2 i? LCA identified six provisional classes, including the largest Competency-constrained class (25.6%) and Barrier-free skeptics (10.6%) who showed the highest readiness yet the highest AI distrust. → V.G. Kremen 2026
q2 i? Bootstrap stability of the six-class solution was poor (mean ARI = 0.385), so the typology is exploratory. → V.G. Kremen 2026 (2)
Evidence¶
V.G. Kremen 2026¶
V.G. Kremen, O.M. Spirin, O.I. Liashenko, S.H. Lytvynova, Y.I. Malovanyi, O.P. Pinchuk, O.M. Sokolyuk, S.O. Semerikov. (2026). AI adoption readiness among Ukrainian education managers: Barriers, typologies, and policy implications. Computers and Education: Artificial Intelligence 11 (2026) 100648. https://doi.org/10.1016/j.caeai.2026.100648
q2 · i? · associational · r1
Gaussian Mixture Model-based LCA on survey indicators from 395 managers, with class range 2–6 and BIC-based selection. Class profiles ranged from Competency-constrained (25.6%, largest) to Barrier-free skeptics (10.6%, highest readiness 3.52 with 74% AI distrust).
"LCA identified six provisional manager classes, supporting H2. Across the 2–6 class range, BIC decreased monotonically ( Table 5 ; Fig. 6 ) without reaching a clear minimum, so the six-class solution is best understood as the most granular interpretable partition examined rather than a BIC-identified optimum"
V.G. Kremen 2026 (2)¶
V.G. Kremen, O.M. Spirin, O.I. Liashenko, S.H. Lytvynova, Y.I. Malovanyi, O.P. Pinchuk, O.M. Sokolyuk, S.O. Semerikov. (2026). AI adoption readiness among Ukrainian education managers: Barriers, typologies, and policy implications. Computers and Education: Artificial Intelligence 11 (2026) 100648. https://doi.org/10.1016/j.caeai.2026.100648
q2 · i? · associational · r1
Bootstrap stability analysis with 100 resamples of the six-class LCA solution, evaluated with the Adjusted Rand Index. The authors report poor stability and treat the typology as exploratory and provisional.
"Bootstrap stability analysis indicated poor classification stability (mean ARI = 0.385, 95% CI [0.184, 0.702]), so the typology is interpreted throughout as exploratory and provisional, requiring confirmation with larger samples"
Discussion¶
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Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
six-provisional-manager-typologies-lca |
title |
Latent Class Analysis identifies six provisional manager typologies with heterogeneous readiness and barrier profiles |
description |
Latent Class Analysis identifies six provisional manager typologies with heterogeneous readiness and barrier profiles |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
recheck_by |
2031 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — vg-kremen-2026, vg-kremen-2026-2 |
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