Metacognitive strategies and prior coding experience significantly predict CT profile membership, with metacognition contributing more strongly¶

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

Subclaims¶

q2 i? In linear discriminant analysis, metacognitive strategies (standardized coefficient = .78) and prior coding experience significantly predicted Proficient profile membership. → 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

Linear discriminant analysis (Box's M = 4.747, p = .593, equal covariance assumption met) tested metacognitive strategies and coding experience as predictors of profile membership. The article reports "Wilks' λ = .62, p < .001" with metacognition contributing more strongly (standardized discriminant coefficient = .78). That coefficient is a weight within the discriminant function, not a between-group effect size, so no magnitude of the kind the i code reads (a d or equivalent) is printed; the analysis is associational and cannot show that metacognition or coding experience causes profile membership.

"MetaCog (M = 5.73, SD = .84) and CodExp significantly predicted Proficient profile membership (Wilks' λ = .62, p < .001), with MetaCog contributing more strongly (standardized coefficient = .78)."

Discussion¶

Learner Variables¶

• Self-Regulation — predictor: learners who differ on it differ in outcomes
• Metacognition — predictor: learners who differ on it differ in outcomes

Related Claims¶

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