Favorable overall self-reported perceptions coexisted with lower self-reported familiarity in specific technical areas: machine learning, prior block-based programming experience, and game-engine programming¶

Claim · All claims
Evidence · 1 study · causal r1 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Design limits · Susana Sánchez Castro 2026: no comparison group (read from the study by two models, 2026-10-29)

Subclaims¶

q2 i? Within the experimental group, item-level descriptives showed comparatively low self-reported familiarity on machine learning knowledge, prior university block-based programming experience, and game-engine programming ability. → Susana Sánchez Castro 2026

Evidence¶

Susana Sánchez Castro 2026¶

Susana Sánchez Castro, Mª Ángeles Pascual Sevillano, Rogelio Buceta Otero, Javier Fombona Cadavieco. (2026). Developing computational thinking in teacher education: a brief experience with coding, robotics, and machine learning. Education Tech Research Dev. https://doi.org/10.1007/s11423-026-10744-6

q2 · i? · causal · r1

Item-level descriptive analysis of all 20 questionnaire items within the experimental group (n = 105). The article also reports machine-learning knowledge (A2; M = 2.80, SD = 0.87; 38.1% lower-category) and game-engine programming (B5; M = 2.88, SD = 0.80; 33.3% lower-category) as less favorable items; these are descriptive statistics with no inferential test.

"The clearest area of lower self-reported familiarity concerned prior experience with visual block-based programming at university (A5; M = 2.50, SD = 0.95), for which 53.3% of participants selected one of the two lower response categories."

Discussion¶

Related Claims¶

• Among workshop participants, the three questionnaire dimensions were positively and significantly intercorrelated, with the highest association between block-based programming familiarity and active-learning perceptions — related
• Exploratory regression models showed both technical dimensions were significantly associated with active-learning perceptions, while only active learning was significantly associated with self-reported knowledge of programming and machine learning — related
• Cluster analysis identified three exploratory response profiles among workshop participants — reluctant, intermediate, and enthusiastic — with the reluctant profile showing low technical familiarity alongside favorable perceptions of several pedagogical applications — related
• A two-hour CCPS-informed coding, robotics, and machine-learning workshop was associated with higher post-intervention self-reported scores for pre-service teachers than a non-equivalent control group on all three questionnaire dimensions — related