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Within the field of K-2 CS education, unplugged computational thinking (CT) activities have been suggested as beneficial for younger students and shown to impact young students’ skills and motivation to learn about CS. This study sought to examine how children demonstrate CT competencies in unplugged sequencing tasks and how children use manipulatives to solve unplugged sequencing tasks. This case study approach examined two unplugged sequencing tasks for six children ranging from ages four to seven (pre-kindergarten to 2nd grade). Children showed evidence of several CT competencies during the sequencing tasks: (1) pattern recognition, (2) algorithms and procedures, (3) problem decomposition, and (4) debugging. The strategies and use of manipulatives to showcase CT competencies seemed to evolve in complexity based on age and developmental levels. Taking into account children’s abilities to demonstrate CT competencies, this study suggests that sequencing is a developmentally appropriate entry point for young children to begin engaging in other CT competencies. In addition, these unplugged sequencing tasks can also be easily integrated into other activities commonly experienced in early childhood classrooms.
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Assessing Young Children’s Computational Thinking Using Cognitive Diagnostic Modeling.
This study illustrates how Cognitive Diagnostic Modeling (CDM) can be used to assess fine-grained levels of computational thinking (CT). We analyzed scored responses to the Computational and Spatial Thinking assessment (CaST) from 271 children. We identified four key attributes required to solve tasks: sequencing of codes, fixing a program, spatial orientation of an agent, and rotation on a point. Results indicated that younger children did not master all the attributes, particularly spatial orientation of an agent and rotation on a point. We identified four common mastery profiles of children that were associated with age. Our findings illustrate that mastering spatial orientation is critical to CT ability. Finally, the nuanced information about children’s mastery levels has potential to provide teachers with useful information about what concepts and skills their students are struggling with so that they can adjust instruction to emphasize those concepts.
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- Award ID(s):
- 1842116
- PAR ID:
- 10438349
- Date Published:
- Journal Name:
- International Conference of the Learning Sciences
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Background Computational thinking (CT) is a crucial domain for children to develop in their early years. To increase children's access to CT learning resources, educational programs like PBS KIDS “Lyla in the Loop” have been developed to incorporate CT concepts through narrative structures where characters solve problems using the CT cycle. However, children need explicit guidance to effectively process both educational and narrative content. Engaging children in dialogues that connect educational content with the narrative has proven to enhance comprehension. Aims This study explores the effectiveness of using AI to enable this type of dialogues between children and a media character, supporting children in learning CT by connecting these concepts with everyday situations in “Lyla in the Loop.” Method Through a between-subject randomized control study with 160 children aged four to eight, we will compare children's learning and applications of CT concepts as well as narrative comprehension from AI-assisted dialogues to those who watched the broadcast version of the show without such dialogues. The study also examines the role of children's cognitive abilities and prior CT knowledge in their learning from the show, with or without AI-assisted dialogues. Expected results The findings could enhance our understanding of AI-based scaffolding strategies in children's media and offer practical implications for improving children's learning experiences.more » « less
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Cohen, J; Solano, G (Ed.)The integration of Computational Thinking (CT) into K-12 education has gained significance in recent years as the field of education experiences the need to equip students with essential skills for the 21st century. This case study focused on two sequencing activities, involving plugged and unplugged tasks, conducted with four children aged four to seven, spanning pre-kindergarten to second grade. The central research question guiding the study was: "What computational thinking (CT) skills were demonstrated by K-2 students as they engaged in two different sequencing tasks?" The study identified competencies in sequencing, reverse sequencing, debugging, pattern recognition, and problem decomposition. The findings suggest that both unplugged and plugged sequencing tasks provide age-appropriate entry points for young children to develop various CT competencies. Furthermore, the study highlights the potential for plugged and unplugged sequencing tasks to be integrated into early childhood classroom activities, offering a practical approach to promoting CT skills in young learners.more » « less
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The purpose of this study was to investigate how computational modeling promotes systems thinking for English Learners (ELs) in fifth-grade science instruction. Individual student interviews were conducted with nine ELs about computational models of landfill bottle systems they had developed as part of a physical science unit. We found evidence of student engagement in four systems thinking practices. Students used data produced by their models to investigate the landfill bottle system as a whole (Practice 1). Students identified agents and their relationships in the system (Practice 2). Students thought in levels, shuttling between the agent and aggregate levels (Practice 3). However, while students could think in levels to develop their models, they struggled to engage in this practice when presented with novel scenarios (e.g., open vs. closed system). Finally, students communicated information about the system using multiple modalities and less-than-perfect English (Practice 4). Overall, these findings suggest that integrating computational modeling into standards-aligned science instruction can provide a rich context for fostering systems thinking among linguistically diverse elementary students.more » « less
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Many coding environments for young children involve using navigational arrow codes representing four movements: forward, backwards, rotate left, and rotate right. Children interpreting these four, seemingly simple codes encounter a complex interaction of spatial thinking and semantic meaning. In this study of how children interpret directional arrows, we found that they interpret each of the arrows as encoding many meanings and that the orientation of the agent plays a critical role in children’s interpretations. Through iterative rounds of qualitative coding and drawing on two examples, we unpack some common interpretations.more » « less
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