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Computational thinking (CT) is central to computer science, yet there is a gap in the literature on how CT emerges and develops in early childhood especially for children from historically marginalized communities. Yet, lack of access to computational materials and effective instruction can create inequities that have lasting effects on young children (Chaudry, et al., 2017). To alleviate the pervasiveness of such inequities and remedy the “pedagogical dominance of Whiteness” (Baines et al., 2018, p.
Computational thinking (CT) is central to computer science, yet there is a gap in the literature on how CT emerges and develops in early childhood especially for children from historically marginalized communities. Understanding how teachers provide asset-based, culturally responsive opportunities for CT in early childhood classrooms remains largely unknown. The purpose of this paper is to share a subset of findings from a qualitative, ethnographic study that explored the ways in which early childhood teachers (ECT) learned and implemented CT using asset-based pedagogies.
Computational thinking (CT) is central to computer science, yet there is a gap in the literature on the best ways to implement CT in early childhood classrooms. The purpose of this qualitative study was to explore how early childhood teachers enacted asset-based pedagogies while implementing CT in their classrooms. We followed a group of 28 early childhood educators who began with a summer institute and then participated in multiple professional learning activities over one year.
Computational thinking CT is central to computer science, yet there is a gap in the literature on the best ways to implement CT in early childhood classrooms. The purpose of this qualitative study was to explore how early childhood teachers enacted asset-based pedagogies while implementing CT in their classrooms.
This chapter features intersections of art, literacy, and creative computing. As a component of STEAM, creative computing augments story creation, or storymaking (Buganza et al., 2023; Compton & Thompson, 2018), prompting learners to explore expressive meaning making as collective interactions with texts. To signify a way of teaching that supports such learning activities, we propose expressive STEM as a design principle, illustrated here with examples from an elementary school and a preservice art education program in Texas, USA.
This chapter features intersections of art, literacy, and creative computing. As a component of STEAM, creative computing augments story creation, or storymaking (Buganza et al., 2023; Compton & Thompson, 2018), prompting learners to explore expressive meaning making as collective interactions with texts. To signify a way of teaching that supports such learning activities, we propose expressive STEM as a design principle, illustrated here with examples from an elementary school and a preservice art education program in Texas, USA.
Teach mathematics and science using materials for the weather-focused Community Collaborative Rain, Hail, & Snow Network project.
Teach mathematics and science using materials for the weather-focused Community Collaborative Rain, Hail, & Snow Network project.
This article portrays how citizen science (CS) projects can be integrated into elementary classrooms to enhance students’ sensemaking skills and connect to real-world science problems. For the last several years, we have been involved in a study, Teacher Learning for Effective School-Based Citizen Science (TL4CS), that developed materials for elementary school teachers to engage their students in data collection, analysis, and interpretation for two existing CS projects: Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) and the Lost Ladybug Project (LLP).
This article portrays how citizen science (CS) projects can be integrated into elementary classrooms to enhance students’ sensemaking skills and connect to real-world science problems.
The recent surge of artificial intelligence (AI) in science education has heightened interest among the NARST community—a curiosity about how technology can transform education that has lasted for decades. Founded in 1928, NARST is an international organization of thousands of members focused on improving science education through research. This growing interest is evidenced by the launch of the Research in Artificial Intelligence-Involved Science Education (RAISE) Research Interest Group in 2022 and the increasing number of AI-related studies presented at NARST conferences.
The recent surge of artificial intelligence (AI) in science education has heightened interest among the NARST community—a curiosity about how technology can transform education that has lasted for decades. This growing interest is evidenced by the launch of the Research in Artificial Intelligence-Involved Science Education (RAISE) Research Interest Group in 2022 and the increasing number of AI-related studies presented at NARST conferences. Despite the growth, limited studies have shed light on how the community members integrate AI into science education and the challenges. We systematically reviewed 36 AI-related papers presented at the 2024 NARST conference to address this gap.
