Latent profile analysis of pre-service teachers' CT skills identifies three profiles (Novice, Developing, Proficient), revealing heterogeneous, non-linear skill acquisition¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person · recheck by 2031: baselines and conditions change

Subclaims¶

q2 i? LPA on standardized digital literacy, problem-solving, and coding comfort scores identified a three-profile model (Novice 34%, Developing 45%, Proficient 21%) as optimal among 128 pre-service teachers. → Tanya Chichekian 2026

Evidence¶

Tanya Chichekian 2026¶

Tanya Chichekian, Maria Cutumisu, Annie Savard and Yi-Mei Zhang. (2026). Profiling Pre-service Teachers' Computational Thinking: The Role of Metacognition and Coding Experience. Journal of Learning Analytics, 13(1), 31–41. https://doi.org/10.18608/jla.2026.9077

q2 · i? · associational · r1

Latent profile analysis of survey data from 128 pre-service teachers identified three CT profiles. The three-profile model showed "high entropy (.84, threshold ≥ .80), significant BLRT ( p = .01)" and lower AIC (995.93) and BIC (1035.85) than the two-profile model; the four-profile model included a small 3% profile with marginal BLRT (p = .06).

"LPA on standardized CT_DL, CT_PS, and CT_CD scores identified a three-profile model (Novice, 34%, n = 43; Developing, 45%, n = 58; Proficient, 21%, n = 27) as optimal, based on statistical fit indices and theoretical alignment"

Discussion¶

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