Assessing the Effectiveness of Using Fab LabBased Learning in Schools on Kxe2x80x9312 Studentsxe2x80x99 Attitude Toward STEAM Contribution:  The NEWTON fabrication laboratory (Fab Lab) Education Initiative assesses the effectiveness of Fab Labbased learning on Kxe2x80x9312 studentsxe2x80x99 attitude toward learning science, technology, engineering, art, and mathematics (STEAM). It considers two aspects: 1) studentsxe2x80x99 motivation and affective state and 2) studentsxe2x80x99 observations and perception of Fab Labbased learning.  Background:  Fab Labs are described as small workshops equipped with a set of computercontrolled tools (e.g., 3D printers) that offer personalized digital fabrication. They have been shown to have a positive impact on learnersxe2x80x99 academic and personal growth when used in extracurricular activities, but little research examines whether integrating Fab Labs into school curricula can help raise student interest in STEAM education.  Research Question:  Can Fab Labbased learning foster studentsxe2x80x99 interest in STEM in primary and secondary schools? Would students be keen to use Fab Labs in their science classes?  Methodology:  Two case studies were carried out in two different schools as part of the European Horizon 2020 NEWTON project. The study had 39 participants; three different surveys were used to assess different constructs.  Findings:  Results show that after using the Fab Labbased learning: 1) students felt more interested in science classes as well as more engaged and less bored and 2) while some students struggled at first when manipulating Fab Lab tools, they adapted quickly and reported that they would like to use Fab Labs as part of their science classes.

Active Learning is About More Than HandsOn: A MixedReality AI System to Support STEM Education Along with substantial consensus around the power of active learning, comes some lack of precision in what its essential ingredients are. New educational technologies offer vehicles for systematically exploring benefits of alternative techniques for supporting active learning. We introduce a new genre of Intelligent Science Station technology that uses Artificial Intelligence (AI) to support children in learning science by doing science in the real world. We use this system in a randomized controlled trial that investigates whether active learning is best when it is implemented as guided deliberate practice, as constructive xe2x80x9chandsonxe2x80x9d activity, or as a combination of both. Automated, reactive guidance is made possible by a specialized AI computer vision algorithm we developed to track what children are doing in the physical environment as they do experiments and discoveries with physical objects. The results support deliberate practice and indicate that having some guided discovery based on effective learning mechanism such as selfexplanation, contrasting cases and personalized interactive feedback produces more robust learning compared to exploratory construction alone. Children learning through guided discovery achieve greater understanding of the scientific principles than children learning through handson construction alone (4 times more pretopost test improvement). Importantly, a combined guided discovery and handson construction condition leads to better learning of the very handson construction skills that are the sole focus of the handson constructive learning condition (u003e10 times more pretopost improvement). These results suggest ways to achieve powerful active learning of science and engineering that go beyond the widespread temptation to equate handson activity with effective learning.