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This paper explores a comprehensive framework to develop students’ data literacy by guiding them in making sense of complex data visualizations. With the growing complexity and prevalence of data visualizations in media, it’s crucial to equip students with the skills to critically analyze and engage with these visual forms of data. This toolkit emphasizes the importance of fostering data habits of mind, rather than mere computational proficiency, and encourages students to consider what a visualization is conveying, how it was created, and why it was created. 

In this study, 82 middle and high school teachers engaged with the InSTEP online professional learning platform to develop their expertise in teaching data science and statistics. We investigated teachers’ engagement within the platform, aspects of the platform that were most and least effective in building teachers’ expertise, and the extent to which teachers’ self-efficacy changed. Using mixed methods, we collected, analyzed and integrated multiple data sources. 

Rapid advancements in computing have enabled automatic analyses of written texts created in educational settings. The purpose of this symposium is to survey several applications of computerized text analyses used in the research and development of productive learning environments. Four featured research projects have developed or been working on (1) equitable automated scoring models for scientific argumentation for English Language Learners, (2) a real-time, adjustable formative assessment system to promote student revision of uncertaintyinfused scientific arguments, (3) a web-based annotation tool to support student revision of scientific essays, and (4) a new research methodology that analyzes teacher-produced text in online professional development courses. These projects will provide unique insights towards assessment and research opportunities associated with a variety of computerized text analysis approaches. 

Abstract We present a comprehensive study of the nonproportionality of NaI(Tl) scintillation detectors within the context of dark matter search experiments. Our investigation, which integrates COSINE-100 data with supplementary$$\gamma $$ $\gamma$spectroscopy, measures light yields across diverse energy levels from full-energy$$\gamma $$ $\gamma$peaks produced by the decays of various isotopes. These$$\gamma $$ $\gamma$peaks of interest were produced by decays supported by both long and short-lived isotopes. Analyzing peaks from decays supported only by short-lived isotopes presented a unique challenge due to their limited statistics and overlapping energies, which was overcome by long-term data collection and a time-dependent analysis. A key achievement is the direct measurement of the 0.87 keV light yield, resulting from the cascade following electron capture decay of$$\mathrm {^{22}Na}$$ ${}^{22}\mathrm{Na}$from internal contamination. This measurement, previously accessible only indirectly, deepens our understanding of NaI(Tl) scintillator behavior in the region of interest for dark matter searches. This study holds substantial implications for background modeling and the interpretation of dark matter signals in NaI(Tl) experiments.