Enhancing Robotic Perception through Synchronized Simulation and Physical Common-Sense Reasoning.

We introduce both conceptual and empirical findings arising from the amalgamation of a robotics cognitive architecture with an embedded physics simulator, aligning with the principles outlined in the intuitive physics literature. The employed robotic cognitive architecture, named CORTEX, leverages a highly efficient distributed working memory known as deep state representation. This working memory inherently encompasses a fundamental ontology, state persistency, geometric and logical relationships among elements, and tools for reading, updating, and reasoning about its contents. Our primary objective is to investigate the hypothesis that the integration of a physics simulator into the architecture streamlines the implementation of various functionalities that would otherwise necessitate extensive coding and debugging efforts. Furthermore, we categorize these enhanced functionalities into broad types based on the nature of the problems they address. These include addressing challenges related to occlusion, model-based perception, self-calibration, scene structural stability, and human activity interpretation. To demonstrate the outcomes of our experiments, we employ CoppeliaSim as the embedded simulator and both a Kinova Gen3 robotic arm and the Open-Manipulator-P as the real-world scenarios. Synchronization is maintained between the simulator and the stream of real events. Depending on the ongoing task, numerous queries are computed, and the results are projected into the working memory. Participating agents can then leverage this information to enhance overall performance.

A Systematic Review of Technologies to Teach Control Structures in Preschool Education.

There is growing interest in teaching computational thinking (CT) to preschool children given evidence that they are able to understand and use CT concepts. One of the concepts that is central in CT definitions, is the concept of control structures, but it is not clear which tools and activities are successful in teaching it to young learners. This work aims at (1) providing a comprehensive overview of tools that enable preschool children to build programs that include control structures, and (2) analyzing empirical evidence of the usage of these tools to teach control structures to children between 3 and 6. It consists of three parts: systematic literature review (SLR) to identify tools to teach CT to young children, analysis of tools characteristics and the possibilities that they offer to express control structures, and SLR to identify empirical evidence of successful teaching of control structures to young children using relevant tools. This work provides an understanding of the current state of the art and identifies areas that require future exploration.

Educational Robotics Intervention to Foster Computational Thinking in Preschoolers: Effects of Children's Task Engagement.

Computational thinking (CT) is a broadly used term in education to refer to the cognitive processes underlying the application of computer science concepts and strategies of problem-solving. Recent literature has pointed out the value of children acquiring computational thinking skills (i.e., understanding and applying concepts, such as conditionals, iteration, or generalization), especially while learning STEM subjects. Robotics has been used as a tool to introduce computational thinking and STEM knowledge to children. As physical objects, robots have been proposed as developmentally appropriate for the early childhood setting, promoting motivation and allowing young learners to represent abstract ideas in a concrete setting. This study presents a novel educational robotics (ER) intervention using RoboTito, a robot programmable through tangible elements in its environment designed for kindergarteners. We used a quasi-experimental design with an active control group. In addition, we conducted a structured observation of the filmed material of the sessions to gather data on children's attention and motivation throughout the activities. Fifty-one children (male = 33; mean age = 66 months, SD = 5.49 months) attending level 5 (kindergarten) at a Uruguayan public school participated in the study. Children in our experimental condition participated in an intervention programming RoboTito using tangible elements, while children in our control condition played with the robot through sensory-motor activities using a remote control and did not engage in programming. Motivational and attentional factors were assessed through video-recorded sessions of the ER activities. Four trained observers blind to the experimental conditions participated in the coding. Children's interactions were assessed in four categories: task engagement, distractibility, oral participation, and objective fulfillment. Our results suggest children's task engagement mediated their gains in CT after the intervention; post-hoc Tukey contrasts revealed non-significant pre-test to post-test gains for the control and low engagement groups, and significant for the high engagement group. Overall, we conclude task engagement played a central role in children's learning gains and our robotics intervention was successful in promoting CT for engaged children. We discuss the practical implications of our results for early childhood education and developmentally appropriate ER targeted for young learners.