Daniel Lapresa Ajamil

Universidad de La Rioja

Papers

5

Total Citations

32

H-Index

4

About

Daniel Lapresa Ajamil is a Spanish educational researcher whose work sits at the compelling intersection of early childhood education, computational thinking, and educational robotics. His research focuses on developing and analyzing methodologies that introduce young children — some as young as three years old — to foundational computational concepts through structured, problem-solving activities using programmable ground robots. Employing observational methodology as a core analytical framework, Lapresa Ajamil has made significant contributions to characterizing how computational thinking manifests and develops in Early Childhood Education settings, filling a recognized gap in the literature on this age group. Among his most notable achievements is a series of interconnected studies published in 2021 and 2022 that trace computational thinking development across different ages within early childhood education, combining rigorous observational design with carefully scaffolded problem sequences of increasing difficulty. His work also explores the nurturing of mathematical talent in young learners and the integration of storytelling contexts to make computational concepts more accessible and engaging. With his most-cited papers accumulating citations across the international research community, Lapresa Ajamil's contributions are helping shape evidence-based approaches to digital literacy and STEM education in the earliest years of formal schooling.

Research Focus

Key Achievements

4
H-Index
5
Papers
32
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Análisis observacional del desarrollo del pensamiento computacional en Educación Infantil-3 años mediante una propuesta de resolución de problemas con un robot de suelo de direccionalidad programada
8 citations · 2021
📈 Most Prolific Year: 2021 (4 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Universidad de La Rioja

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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