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This paper presents a model, the double integration model, for integrating Computer Science (CS) and mathematics in upper elementary instruction. Fifth-grade students (n=1,037) participated either in the double integrated model (Condition 1; integrated in both CS and Math instruction) or integrated lessons only in CS instruction (Condition 2). After each lesson, students rated their enjoyment, perceived ease, and perceptions of CS-math connections. Multilevel analyses revealed that Condition 1 students reported significantly more positive perceptions and stronger CS-math connections of the lessons than Condition 2 students. Girls in Condition 1 responded more positively than boys on enjoyment and connection items, and outperformed Condition 2 girls across all measures. These findings underscore the double integration model's effectiveness. 

As an integral part of qualitative research inquiry, field notes provide important data from researchers embedded in research sites. However, field notes can vary significantly, influenced by the researchers' immersion in the field, prior knowledge, beliefs, interests, and perspectives. As consequence, their interpretation presents significant challenges. This study offers a preliminary investigation into the potential of using large language models to assist researchers with the analysis and interpretation of field notes data. Our methodology consisted of two phases. First, a researcher deductively coded field notes of six classroom implementations of a novel elementary-level mathematics curriculum. In the second phase, we prompted ChatGPT-4 to code the same field notes, using the codebook, definitions, examples, and deductive coding approach employed by the researcher. We also prompted Chatgpt to provide justifications of its coding decisions We then, calculated agreements and disagreements between ChatGPT and the researcher, organized the data in a contingency table, computed Cohen's Kappa, structured the data into a confusion matrix; and using the researcher’s coding as the “gold standard”, we calculated performance measures, specifically: Accuracy, Precision, Recall, and F1 Score. Our findings revealed that while the researcher and ChatGPT appeared to generally agree on the frequency in applying the different codes, overall agreement, as measured by Cohen’s Kappa was low. In contrast, using measures from information science at the code level revealed more nuanced results. Moreover, coupled with ChatGPT justifications of coding decisions, these findings provided insights than can help support the iterative improvement of codebooks. 

The paper describes an intervention to support teachers and paraprofessionals to integrate mathematics and computer science. Expansive Framing is the theoretical framework used to support transfer. It might help to communicate clearly the connections between mathematics and computer science and how EF supports in making these connections. A couple of examples might help the reader understand what expansive framing means in the context of the problems and communicate the efficacy of the approach and limitations if any. It does add value to the discussions. This paper describes the engagement of teams to co-design of curriculum, drawing on Expansive Framing theory to encourage transfer of learning. Preliminary results are reported on the value of EF when clearly explicated in the lesson plans. This paper will be a valuable inclusion in this TSG. In reviewing this paper, check word and page length to adhere to template; if possible, it would be good to consider implications of your work with reference to scalability and sustainability. 

This paper presents a novel approach for predicting the outcomes of elementary students’ participation in computer science (CS) instruction by using exit tickets, a type of practical measure, where students provide rapid feedback on their instructional experiences. Such feedback can help teachers to inform ongoing teaching and instructional practices. We fit a Structural Equation Model to examine whether students' perceptions of enjoyment, ease, and connections between mathematics and CS in an integrated lesson predicted their affective outcomes in self-efficacy, interest, and CS identity, collected in a pre- post- survey. We found that practical measures can validly measure student experiences. 

The learning sciences community is currently exploring new ways to enact productive and equitable co-design research-practice partnerships that are sensitive to all the concerns and needs of stakeholders. The paper contributes to that still-growing literature through an interaction analysis of a co-design discussion involving school district partners that unfolded about cultural relevance and sensitivity in relation to the use of a specific image in an elementary school coding lesson. The episode involved looking moment-by-moment at how district educators recognized and acknowledged that a specific design decision could be harmful for a minoritized population of students enrolled in the district. However, once a key change was made to be more culturally responsive and considerate, new and unexpected pedagogical challenges appeared. This case serves to illustrate some of the unexpected tensions that can appear in real-time when unanticipated questions about cultural relevance are foregrounded during lesson and materials co-design. 

The learning sciences community is currently exploring new ways to enact productive and equitable co-design research-practice partnerships that are sensitive to all the concerns and needs of stakeholders. The paper contributes to that still-growing literature through an interaction analysis of a co-design discussion involving school district partners that unfolded about cultural relevance and sensitivity in relation to the use of a specific image in an elementary school coding lesson. The episode involved looking moment-by-moment at how district educators recognized and acknowledged that a specific design decision could be harmful for a minoritized population of students enrolled in the district. However, once a key change was made to be more culturally responsive and considerate, new and unexpected pedagogical challenges appeared. This case serves to illustrate some of the unexpected tensions that can appear in real-time when unanticipated questions about cultural relevance are foregrounded during lesson and materials co-design. 

This study examines how a rural-serving school district aimed to provide elementary level computer science (CS) by offering instruction during students’ computer lab time. As part of a research-practice partnership, cross-context mathematics and CS lessons were co-designed to expansively frame and highlight connections across – as opposed to integration within – the two subjects. Findings indicated that most students who engaged with the lessons across the lab and classroom contexts reported finding the lessons interesting, seeing connections to their mathematics classes, and understanding the programming. In contrast, a three-level logistic regression model showed that students who only learned about mathematics connections within the CS lessons (thus not in a cross-context way) reported statistically significant lower levels of interest, connections, and understanding 

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. 

This study examines how a rural-serving school district aimed to provide elementarylevel computer science (CS) by offering instruction during students’ computer lab, a class taught by paraprofessional educators with limited background in computing. As part of a researchpractice partnership, cross-context mathematics and CS lessons were co-designed to expansively frame and highlight connections across – as opposed to integration within – the two subjects. Findings indicate that the paraprofessionals teaching the lessons generally reported positive experiences and understanding of content; however, those less comfortable with the content reported lower student interest. Further, most students who engaged with the lessons across the lab and classroom contexts reported finding the lessons interesting, seeing connections to their mathematics classes, and understanding the programming. In contrast, students who only learned about mathematics connections within the CS lessons (thus not in a cross-context way) reported significantly lower levels of interest, connections, and understanding.