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With the increasing prevalence of large language models (LLMs) such as ChatGPT, there is a growing need to integrate natural language processing (NLP) into K-12 education to better prepare young learners for the future AI landscape. NLP, a sub-field of AI that serves as the foundation of LLMs and many advanced AI applications, holds the potential to enrich learning in core subjects in K-12 classrooms. In this experience report, we present our efforts to integrate NLP into science classrooms with 98 middle school students across two US states, aiming to increase students’ experience and engagement with NLP models through textual data analyses and visualizations. We designed learning activities, developed an NLP-based interactive visualization platform, and facilitated classroom learning in close collaboration with middle school science teachers. This experience report aims to contribute to the growing body of work on integrating NLP into K-12 education by providing insights and practical guidelines for practitioners, researchers, and curriculum designers. 

Through our work to examine mathematical and computational learning in authentic and convivial contexts that requires creativity, imagination, reasoning, and discourse, we have theorized an experiential learning cycle that attends to the development of voice, agency, and identity needed in young people for an earned insurgency—the right to demand change. Our work underscores how the current situation that many students face in classrooms amounts to a type of cognitive segregation that denies these students access to authentic and empowering intellectual agency. By facilitating a process whereby students, using their own creative and imaginative means, intentionally develop a type of ownership over the exploration and application of the mathematical concepts they are being taught, we help students move from simple surface level, syntactic understandings, to deeper semantic learning that is more personally significant and meaningful.

 

Effective professional learning communities (PLCs) are important in supporting teacher learning. This study investigated computer science (CS) teacher leaders’ perspectives on the lessons and the challenges in supporting CS teachers through local PLCs. We purposefully selected ten CSTA chapters and conducted focus group interviews with the chapter leaders between 2020 and 2022. Our findings indicated that these PLCs offered social-emotional support, continual networking opportunities, and rich professional learning resources. Also, they amplified teachers’ voices and supported CS teachers’ professional identity building. To engage CS teachers, the teacher leaders built trust, collaborated with other PLCs or organizations, and set an inclusive PLC culture. These PLCs had challenges in recruitment, leadership development and transition, and building group identity. 

Co-creative proccesses between people can be characterized by rich dialogue that carries each person's ideas into the collaborative space. When people co-create an artifact that is both technical and aesthetic, their dialogue reflects the interplay between these two dimensions. However, the dialogue mechanisms that express this interplay and the extent to which they are related to outcomes, such as peer satisfaction, are not well understood. This paper reports on a study of 68 high school learner dyads' textual dialogues as they create music by writing code together in a digital learning environment for musical remixing. We report on a novel dialogue taxonomy built to capture the technical and aesthetic dimensions of learners' collaborative dialogues. We identified dialogue act n-grams (sequences of length 1, 2, or 3) that are present within the corpus and discovered five significant n-gram predictors for whether a learner felt satisfied with their partner during the collaboration. The learner was more likely to report higher satisfaction with their partner when the learner frequently acknowledges their partner, exchanges positive feedback with their partner, and their partner proposes an idea and elaborates on the idea. In contrast, the learner is more likely to report lower satisfaction with their partner when the learner frequently accepts back-to-back proposals from their partner and when the partner responds to the learner's statements with positive feedback. This work advances understanding of collaborative dialogue within co-creative domains and suggests dialogue strategies that may be helpful to foster co-creativity as learners collaborate to produce a creative artifact. The findings also suggest important areas of focus for intelligent or adaptive systems that aim to support learners during the co-creative process. 

Motivation: Recent efforts to expand K-12 computer science education highlight the great need for well-prepared computer science (CS) teachers. Teacher identity theory offers a particular conceptual lens for us to understand computer science teacher preparation and professional development. The emerging literature suggests that teacher identity is central to sustaining motivation, efficacy, job satisfaction, and commitment, and these attributes are crucial in determining teacher retention. While the benefits associated with a strong sense of teacher identity are great, teachers face unique challenges and tensions in developing their professional identity for teaching computer science. Objectives: This exploratory study attempts to operationalize computer science teacher identity through discussing the potential domains, proposing and testing a quantitative instrument for assessing computer science teachers’ professional identity. Method: We first discussed the potential domains of computer science teacher identity based on recent teacher identity literature and considerations on some unique challenges for computer science teachers. Then we proposed the computer science teacher identity scale, which was piloted through a national K-12 computer science teacher survey with 3,540 completed responses. The survey results were analyzed with a series of factor analyses to test the internal structure of the computer science teacher identity scale. Results: Our analyses reveal a four-factor solution for the computer science teacher identity scale, which is composed of CS teaching commitment, CS pedagogical confidence, confidence to engage students, and sense of community/belonging. There were significant differences among the teachers with different computer science teaching experiences. In general, teachers with more computer science teaching experience had higher computer science teacher identity scores on all four factors. Discussion: The four-factor model along with a large national dataset invites a deeper analysis of the data and can provide important benchmarks. Such an instrument can be used to explore developmental patterns in computer science teacher identity, and function as a pedagogical tool to provoke discussion and reflection among teachers about their professional development. This study may also contribute to understanding computer science teachers’ professional development needs and inform efforts to prepare, develop, and retain computer science teachers. 

This paper reports a study of CSTA chapter leaders' perceptions of their chapter's roles in supporting computer science (CS) teachers. Intent on understanding the impact of member-ship in a professional organization on the development of teacher professional identity, our research revealed that in the chapter leaders' perceptions local CSTA chapters had an important role in supporting the development of their members' professional identity as a CS teacher.