Latent profile analysis of combined SR and OB factors identifies six distinct teacher profiles spanning overestimation, underestimation, and alignment¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · no dated study recorded · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? In the full sample (N = 288), a six-profile solution fit best, including an overestimation profile (high SR, lower OB; n = 43), an alignment profile (n = 40), an underestimation profile (low SR, near-average OB; n = 59), and profiles near the overall mean. → lpa-full

Evidence¶

lpa-full¶

Shan Zhang, Ruiwei Xiao, Anthony F. Botelho, Guanze Liao, Thomas K. F. Chiu, John Stamper, and Kenneth R. Koedinger. 2026. How to Assess AI Literacy: Misalignment Between Self-Reported and Objective-Based Measures. In LAK26: 16th International Learning Analytics and Knowledge Conference (LAK 2026). ACM, New York, NY, USA. https://doi.org/10.1145/3785022.3785088

q2 · i? · associational · r2

Latent profile analysis on combined SR and OB factors in the full sample (N = 288) found "the six-profile solution provided the best fit". Classification quality was high (mean confidence .935, mean entropy .25), with profile sizes n = 37, 62, 40, 43, 59, and 47.

"Model selection using both AIC and BIC indicated that the six-profile solution provided the best fit. The emergent profiles varied meaningfully in terms of both self-reported and objective-based AI literacy"

Discussion¶

Related Claims¶

• SR–OB profile patterns differ by prior AI literacy experience: overestimation appears only among experienced teachers and a low–low profile only among inexperienced teachers — related
• Teachers' self-reported AI literacy correlates only weakly with their objectively measured performance (r = 0.07–0.24) — a broader claim this one bears on
• Adding a cross-factor composite from a teacher study yields r = .079, still with an interval including zero, and latent profiles reveal over- and underestimation of competence — related
• Perceived and objectively demonstrated AI literacy show only limited alignment in the same samples (pooled r = .055, interval including zero) — related
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• The objective-based AI literacy assessment demonstrates psychometric stability with high reliability (KR-20 = 0.862) and approximate unidimensionality — related
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• Interest profiles combine homogeneous and heterogeneous patterns across the six dimensions — related