The executive summary of the Formative Research Report for the project: Fostering Joint Parent/Child Engagement in Preschool Computational Thinking by Leveraging Digital Media, Mobile Technology, and Library Settings in Rural Communities.
This is the formative research report for the project: Fostering Joint Parent/Child Engagement in Preschool Computational Thinking by Leveraging Digital Media, Mobile Technology, and Library Settings in Rural Communities
AHA! Island is a new project that uses animation, live-action videos, and hands-on activities to support joint engagement of children and caregivers around computational thinking (CT) concepts and practices. Education Development Center (EDC), WGBH’s research partner for the project, conducted an impact study with 108 English-speaking families (4- to 5-year-old children and their families) to test the promise of this CT learning intervention.
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TEAM MEMBERS:
Marisa WolskyHeather LavigneJessica AndrewsAshley Lewis-PresserLeslie CuellarRegan VidiksisCamille Ferguson
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
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
Children’s worlds are increasingly populated by intelligent technologies. This has raised a number of questions about the ways in which technology can change children’s ideas about important concepts, like what it means to be alive or smart. In this study, we examined the impact of experience with intelligent technologies on children’s ideas about robot intelligence. A total of 60 children aged 4 through 7 were asked to identify the intellectual, psychological, and biological characteristics of 8 entities that differed in terms of their life status and intellectual capabilities. Results
Research on human–robot interaction has often ignored the human cognitive changes that might occur when humans and robots work together to solve problems. Facilitating human–robot collaboration will require understanding how the collaboration functions system-wide. The authors present detailed examples drawn from a study of children and an autonomous rover, and examine how children’s beliefs can guide the way they interact with and learn about the robot. The data suggest that better collaboration might require that robots be designed to maximize their relationship potential with specific users