AI-Generated Contexts for Teaching Robotics to Preservice Early Childhood Teachers

An experiment with 120 preservice teachers at Universidad Rey Juan Carlos in Madrid, Spain, tested a methodology using AI-generated contexts to teach robotics and improve Computational Thinking. The dataset likely contains results comparing an experimental group using AI assignments to a control group. The data was authored by Hijón-Neira, Raquel and last updated on October 14, 2025.

Use Cases

• Compare learning outcomes between AI-assisted and traditional teaching methods based on the described experimental design.
• Analyze the relationship between AI-generated practical assignments and gains in Computational Thinking based on the study results.
• Study the impact of pedagogical interventions on learning attitudes in preservice teachers based on the described metrics.
• Replicate or validate the methodology for teaching robotics in early childhood education programs.

Strengths

• Study design includes a control group of 120 preservice teachers, allowing for comparative analysis.
• Results show significantly higher gains in Computational Thinking and learning attitudes in the experimental group, providing a clear outcome measure.
• Specific geographic and institutional context is provided: Universidad Rey Juan Carlos in Madrid, Spain.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.
• The sample is specific to one university's Early Childhood Education degree program, which may limit generalizability.

Provenance

Source

e-cienciaDatos Harvested Dataverse

Collection Method

Likely collected via an educational experiment with preservice teachers.

Time Range

null

Freshness

Last updated 2025-10-14 21:41:53; freshness should be verified.

Geography

Madrid, Spain