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Although there have been efforts to broaden the participation of underrepresented students in Science, Technology, Engineering, and Mathematics (STEM), few studies have focused on how Latine bilingual students in rural contexts can access computer programming. The purpose of this case study is to examine how translanguaging facilitates understanding among emergent bilingual students. The findings showed how translanguaging is more than translation, how students used their linguistic repertoire to negotiate meaning, and the use of language brokering as a pedagogical tool. Implications for translanguaging in STEM have the potential for a deep understanding of computer programming concepts. 

The paper develops datasets and methods to assess student participation in real-life collaborative learning environments. In collaborative learning environments, students are organized into small groups where they are free to interact within their group. Thus, students can move around freely causing issues with strong pose variation, move out and re-enter the camera scene, or face away from the camera. We formulate the problem of assessing student participation into two subproblems: (i) student group detection against strong background interference from other groups, and (ii) dynamic participant tracking within the group. A massive independent testing dataset of 12,518,250 student label instances, of total duration of 21 hours and 22 minutes of real-life videos, is used for evaluating the performance of our proposed method for student group detection. The proposed method of using multiple image representations is shown to perform equally or better than YOLO on all video instances. Over the entire dataset, the proposed method achieved an F1 score of 0.85 compared to 0.80 for YOLO. Following student group detection, the paper presents the development of a dynamic participant tracking system for assessing student group participation through long video sessions. The proposed dynamic participant tracking system is shown to perform exceptionally well, missing a student in just one out of 35 testing videos. In comparison, a stateof- the-art method fails to track students in 14 out of the 35 testing videos. The proposed method achieves 82.3% accuracy on an independent set of long, real-life collaborative videos. 

This commentary focuses on reflections involving the special issue on Teaching and Learning Mathematics and Computing in Multilingual Contexts and the important role that Teachers College Record has played in fostering creative interdisciplinary collaborations among researchers, graduate students, teachers, K-12 students, and parents. A discussion is included on how participating as a Guest Lead Editor of this special issue afforded opportunities to learn more about projects that integrate mathematics and computing as well as transformations that have impacted the work we do in our respective fields. Multilingual contexts contribute much to our understanding of global perspectives on mathematics education. Taking up a memorable moment that involved such a context, I discuss future directions for the Teachers College Record as we consider reaching to multilingual audiences. 

We present an integrated mathematics and computer programming curriculum for teaching bilingual middle school students how to code using digital video representations. Building on the student's familiarity with digital video, we introduce them to number representations (e.g., binary and hexadecimals), NumPy arrays, coordinate systems, color, frames, and how to combine them into digital video content. The curriculum is fully integrated with middle school mathematics. Middle school students who completed the curriculum joined undergraduate students to co-teach the curriculum in a small group collaborative learning environment. We found evidence of successful implementations based on video recordings of student and facilitator interactions, attitude scales, student exit interviews, and samples of student work.