This poster was presented at the 2021 NSF AISL Awardee Meeting.
Collaborative robots – cobots – are designed to work with humans, not replace them. What learning affordances are created in educational games when learners program robots to assist them in a game instead of being the game? What game designs work best?
The data collection procedure and process is one of the most critical components in a research study that affects the findings. Problems in data collection may directly influence the findings, and consequently, may lead to questionable inferences. Despite the challenges in data collection, this study provides insights for STEM education researchers and practitioners on effective data collection, in order to ensure that the data is useful for answering questions posed by research. Our engineering education research study was a part of a three-year, NSF funded project implemented in the Midwest
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TEAM MEMBERS:
Ibrahim YeterAnastasia Marie RynearsonHoda EhsanAnnwesa DasguptaBarbara FagundesMuhsin MeneskeMonica Cardella
Integrating science, technology, engineering, and mathematics (STEM) subjects in pre-college settings is seen as critical in providing opportunities for children to develop knowledge, skills, and interests in these subjects and the associated critical thinking skills. More recently computational thinking (CT) has been called out as an equally important topic to emphasize among pre-college students. The authors of this paper began an integrated STEM+CT project three years ago to explore integrating these subjects through a science center exhibit and a curriculum for 5-8 year old students. We
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TEAM MEMBERS:
Morgan HynesMonica CardellaTamara MooreSean BrophySenay PurzerKristina TankMuhsin MeneskeIbrahim YeterHoda Ehsan
Computational Thinking (CT) is an often overlooked, but important, aspect of engineering thinking. This connection can be seen in Wing’s definition of CT, which includes a combination of mathematical and engineering thinking required to solve problems. While previous studies have shown that children are capable of engaging in multiple CT competencies, research has yet to explore the role that parents play in promoting these competencies in their children. In this study, we are taking a unique approach by investigating the role that a homeschool mother played in her child’s engagement in CT
Given the growth of technology in the 21st century and the growing demands for computer science skills, computational thinking has been increasingly included in K-12 STEM (Science, Technology, Engineering and Mathematics) education. Computational thinking (CT) is relevant to integrated STEM and has many common practices with other STEM disciplines. Previous studies have shown synergies between CT and engineering learning. In addition, many researchers believe that the more children are exposed to CT learning experiences, the stronger their programming abilities will be. As programming is a
Increasing demand for curricula and programming that supports computational thinking in K-2 settings motivates our research team to investigate how computational thinking can be understood, observed, and supported for this age group. This study has two phases: 1) developing definitions of computational thinking competencies, 2) identifying educational apps that can potentially promote computational thinking. For the first phase, we reviewed literatures and models that identified, defined and/or described computational thinking competencies. Using the model and literature review, we then
For the past two decades, researchers and educators have been interested in integrating engineering into K-12 learning experiences. More recently, computational thinking (CT) has gained increased attention in K-12 engineering education. Computational thinking is broader than programming and coding. Some describe computational thinking as crucial to engineering problem solving and critical to engineering habits of mind like systems thinking. However, few studies have explored how computational thinking is exhibited by children, and CT competencies for children have not been consistently defined
Informal learning environments such as science centers and museums are instrumental in the promotion of science, technology, engineering, and mathematics (STEM) education. These settings provide children with the chance to engage in self-directed activities that can create a of lifelong interest and persistence in STEM. On the other hand, the presence of parents in these settings allows children the opportunity to work together and engage in conversations that can boost understanding and enhance learning of STEM topics. To date, a considerable amount of research has focused on adult-child
This guide describes what took place during NYSCI’s Big Data for Little Kids workshop series, Museum Makers: Designing With Data. In addition to detailed outlines of the activities implemented during the program, this guide includes a glossary of recurrent terms and resources used throughout the workshops.
In 2017, as part of a National Science Foundation funded project, the New York Hall of Science (NYSCI) set out to teach Big Data concepts to children ages 4 – 8 years old. NYSCI developed and piloted an after-school program for families to utilize the data cycle as a method of informed
The goal of this three-year project is to leverage NSF’s investment in both SciGirls and computer science education by engaging 8-13 year-old girls in computational thinking and coding through innovative transmedia programming which inspires and prepares them for future computer science studies and careers.