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1. Examining interactions between dominant discourses and engineering educational concepts in teachers' pedagogical reasoning

   https://doi.org/10.1002/jee.20563  

   De Lucca, Natalie ; Watkins, Jessica ; Swanson, Rebecca D. ; Portsmore, Merredith ( November 2023 , Journal of Engineering Education)

   N/A (Ed.)

   Background:Engineering's introduction into K–12 classrooms has been purported to support meaningful and inclusive learning environments. However, teachers must contend with dominant discourses embedded in US schooling that justify inequitable distributions of resources. Purpose:Drawing on Gee's notion of discourses, we examine how teachers incorporate language legitimizing socially and culturally constructed values and beliefs. In particular, we focus on the discourse of ability hierarchy—reflecting dominant values of sorting and ranking students based on perceived academic abilities—and the discourse of individual blame—reflecting dominant framings of educational problems as solely the responsibility of individual students or families. We aim to understand how these discourses surface in teachers' reasoning about teaching engineering. Method:We interviewed 15 teachers enrolled in an online graduate program in engineering education. Utilizing critical discourse analysis, we analyzed how teachers drew on discourses of blame and ability hierarchy when reasoning about problems of practice in engineering. Results:Teachers drew on engineering education concepts to reinforce dominant discourses (echoing specific language and preserving given roles) as well as to disrupt (utilizing different language or roles that [implicitly] challenge) dominant discourses. Importantly, teachers could also retool discourses of ability hierarchy (arguing for a more equitable distribution of resources but problematically preserving the values of ranking and sorting students). Conclusions:K–12 schooling's sociohistorical context can shape how teachers make sense of engineering in ways that implicate race, gender, disability, and language, suggesting a need to grapple with how discourses from schooling—and engineering culture—maintain marginalizing environments for students. 

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2. FEARLESS STEPS: ADVANCEMENTS IN SPEECH TECHNOLOGY AND CORPUS DEVELOPMENT FOR NATURALISTIC AUDIO

   Joglekar, A. ; Hansen, J.H.L. ; Yousefi, M. ; Chandra Shekar, M. ; Chen, S.-J. ; Belitz, C. ( February 2023 , NASA Human Research Program Investigators Conference)

   INTRODUCTION: CRSS-UTDallas initiated and oversaw the efforts to recover APOLLO mission communications by re-engineering the NASA SoundScriber playback system, and digitizing 30-channel analog audio tapes – with the entire Apollo-11, Apollo-13, and Gemini-8 missions during 2011-17 [1,6]. This vast data resource was made publicly available along with supplemental speech & language technologies meta-data based on CRSS pipeline diarization transcripts and conversational speaker time-stamps for Apollo team at NASA Mission Control Center, [2,4]. In 2021, renewed efforts over the past year have resulted in the digitization of an additional +50,000hrs of audio from Apollo 7,8,9,10,12 missions, and remaining A-13 tapes. Cumulative digitization efforts have enabled the development of the largest publicly available speech data resource with unprompted, real conversations recorded in naturalistic environments. Deployment of this massive corpus has inspired multiple collaborative initiatives such as Web resources ExploreApollo (https://app.exploreapollo.org) LanguageARC (https://languagearc.com/projects/21) [3]. ExploreApollo.org serves as the visualization and play-back tool, and LanguageARC the crowd source subject content tagging resource developed by UG/Grad. Students, intended as an educational resource for k-12 students, and STEM/Apollo enthusiasts. Significant algorithmic advancements have included advanced deep learning models that are now able to improve automatic transcript generation quality, and even extract high level knowledge such as ID labels of topics being spoken across different mission stages. Efficient transcript generation and topic extraction tools for this naturalistic audio have wide applications including content archival and retrieval, speaker indexing, education, group dynamics and team cohesion analysis. Some of these applications have been deployed in our online portals to provide a more immersive experience for students and researchers. Continued worldwide outreach in the form of the Fearless Steps Challenges has proven successful with the most recent Phase-4 of the Challenge series. This challenge has motivated research in low level tasks such as speaker diarization and high level tasks like topic identification. IMPACT: Distribution and visualization of the Apollo audio corpus through the above mentioned online portals and Fearless Steps Challenges have produced significant impact as a STEM education resource for K-12 students as well as a SLT development resource with real-world applications for research organizations globally. The speech technologies developed by CRSS-UTDallas using the Fearless Steps Apollo corpus have improved previous benchmarks on multiple tasks [1, 5]. The continued initiative will extend the current digitization efforts to include over 150,000 hours of audio recorded during all Apollo missions. ILLUSTRATION: We will demonstrate WebExploreApollo and LanguageARC online portals with newly digitized audio playback in addition to improved SLT baseline systems, the results from ASR and Topic Identification systems which will include research performed on the corpus conversational. Performance analysis visualizations will also be illustrated. We will also display results from the past challenges and their state-of-the-art system improvements. 

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3. Physical Education and English Language Arts Based K-12 Engineering Outreach in Software Defined Networking (Extended Version)

   Ozogul, Gamze ; Thyagaturu, Akhilesh S. ; Reisslein, Martin ; Scaglione, Anna ( January 2020 , arXiv:2006.05545)

   K-12 engineering outreach has typically focused on elementary electrical and mechanical engineering or robot experiments integrated in science or math classes. In contrast, we propose a novel outreach program focusing on communication network principles that enable the ubiquitous web and smart-phone applications. We design outreach activities that illustrate the communication network principles through activities and team competitions in physical education (PE) as well as story writing and cartooning in English Language Arts (ELA) classes. The PE activities cover the principles of store-and-forward packet switching, Hypertext Transfer Protocol (HTTP) web page download, connection establishment in cellular wireless networks, as well as packet routing in Software-Defined Networking (SDN). The proposed outreach program has been formatively evaluated by K-12 teachers. A survey for the evaluation of the impact of the outreach program on the student perceptions, specifically, the students' interest, self-efficacy, utility, and negative stereotype perceptions towards communication network engineering, is also presented. 

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4. Rethinking instructional strategies with English learners in the content areas

   https://doi.org/10.1002/tesj.557  

   Grapin, Scott E. ; Llosa, Lorena ; Haas, Alison ; Lee, Okhee ( October 2020 , TESOL Journal)

   The latest content standards in U.S. K–12 education are academically rigorous for all students, including a fast‐growing population of English learners (ELs). Because these standards are different from previous standards in terms of not only their rigor but also their theoretical underpinnings, enacting instruction aligned to the standards will require shifts in how teachers conceptualize the nature of content and language learning. In this article, the authors argue that instructional strategies traditionally used with ELs in the content areas need to be rethought in light of contemporary theoretical perspectives. After providing a brief overview of these perspectives in content area education and language education, the authors highlight three instructional strategies: (a) preteaching vocabulary, (b) providing sentence frames and starters, and (c) using visual aids. They describe how each strategy has traditionally been used and tensions that may arise in using the strategy in light of contemporary perspectives. Drawing on examples from their curriculum development work in linguistically diverse elementary science classrooms, the authors propose ways that teachers can adapt when and how they use each of these strategies to deliver more theoretically sound instruction. Implications of the adapted strategies for teachers working with ELs in content classrooms are discussed.

    

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5. Using transformers to provide teachers with personalized feedback on their classroom discourse: The TalkMoves application

   Suresh, A. ; Jacobs, J. ; Lai, V. ; Tan, C. ; Ward, W. ; Martin, J.H. ; Sumner, T. ( January 2021 , Association for the Advancement of Artificial Intelligence)

   null (Ed.)

   TalkMoves is an innovative application designed to support K-12 mathematics teachers to reflect on, and continuously improve their instructional practices. This application combines state-of-the-art natural language processing capabilities with automated speech recognition to automatically analyze classroom recordings and provide teachers with personalized feedback on their use of specific types of discourse aimed at broadening and deepening classroom conversations about mathematics. These specific discourse strategies are referred to as “talk moves” within the mathematics education community and prior research has documented the ways in which systematic use of these discourse strategies can positively impact student engagement and learning. In this article, we describe the TalkMoves application’s cloud-based infrastructure for managing and processing classroom recordings, and its interface for providing teachers with feedback on their use of talk moves during individual teaching episodes. We present the series of model architectures we developed, and the studies we conducted, to develop our best-performing, transformer-based model (F1 = 79.3%). We also discuss several technical challenges that need to be addressed when working with real-world speech and language data from noisy K-12 classrooms. 

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