Research on Associative Cognition Networks with Educational Robotics for Learning Healthy Hydration Habits.

Introduction: Neuroeducation establishes the need to analyze cognitive structures in order to assess learning. The demand of technological advancement necessitates the increase of digital resources for teaching and scientific and digital literacy. Objective: Analyses Associative Cognitive Networks of pre-service teachers on bioscientific learning of healthy hydration habits after an intervention using educational robotics. Methodology: The study adopts a mixed approach and graph analysis using Gephi® and Cytoscape® software, and with the use of measures of degree, clustering coefficient, average shortest path length and modularity. Results: Milk is represented as the main Hub of the cognitive structures. The nodes with the highest Degree are in the center of the network, such as Milk, Natural juice, 2 liters of water, 200 ml of water or Sweetened beverages, while Energy drinks and Natural lemonade, which have the lowest relevance, are located further away. Discussion: There is a reasonable association between healthy and unhealthy drinks, as well as a strong association between water consumption and healthy drinks, especially milk. The pre-service teachers have a better understanding of the concept of recommended daily intake compared to the number of specific glasses. Conclusions: Scientific knowledge acquired after educational robotics intervention focuses on relevant content for healthy hydration habits. To improve assessment in higher education, we advocate more studies analyzing Associative Cognitive Networks on the effects of learning scientific content and the use of resources such as Educational Robotics.