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1. Translanguaging in Mathematics Learning: Teacher Instructional and Attentional Supports

   Gilmore, M. (January 2020, ProQuest dissertations theses global)

   Students from less-dominant linguistic backgrounds generally have less opportunity to participate in classroom mathematical discourse compared to their English-dominant peers. An issue raised by mathematics education researchers concerned with issues of equity and opportunities for students is that status quo classroom practices and norms supported by teachers may be less familiar to students from non-dominant linguistic groups, or even detrimental to their classroom participation. Additionally, students who position themselves as doers of mathematics usually come from dominant cultural and linguistic groups (Abreu & Cline, 2002; Hand, 2012), potentially disposing students to perceive classroom mathematics learning through the lens of dominant cultural norms and practices. Thus, students who do not come from dominant linguistic backgrounds might perceive the mathematics classroom differently than their English dominant peers. However, less research has been conducted on how mathematics teachers attend to or notice norms around language and introduce new ones that encourage a multitude of linguistic practices, therefore heightening student participation. Heightening student participation can have implications for students being more likely to identify with mathematics. Additionally, examining students’ participation when using a multitude of linguistic practices or translanguaging is helpful for teachers attending to their own practice to support emerging bilingual students and bilingual students when engaging in mathematical sensemaking. 

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2. Quantifying Engagement in Preschool Classrooms: Conversational Turn-Taking & Topic Initiations

   Tao, S.A.; Dutta, S.; Seven, Y.; Kothalkar, P.; Irvin, D.W.; Buzhardt, J.; Hansen J.H.L. (March 2022, ASEE-GSW–2022: American Soc. of Engineering Education – Gulf-SouthWest Section Conf.)

   Adult-child interaction is an important component for language development in young children. Teachers responsible for the language acquisition of their students have a vested interest in improving such conversation in their classrooms. Advancements in speech technology and natural language processing can be used as an effective tool by teachers in pre-school classrooms to acquire large amounts of conversational data, receive feedback from automated conversational analysis, and amend their teaching methods. Measuring engagement among pre-school children and teachers is a challenging task and not well defined. In this study, we focus on developing criteria to measure conversational turn-taking and topic initiation during adult-child interactions in preschool environments. However, counting conversational turns, conversation initiations, or vocabulary alone is not enough to judge the quality of a conversation and track language acquisition. It is necessary to use a combination of the three and include a measurement of the complexity of vocabulary. The next iterative of this problem is to deploy various solutions from speech and language processing technology to automate these measurements. * (2022 ASEE Best Student Paper Award Winner) 

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3. Hao Fayin: Developing Automated Audio Assessment Tools for a Chinese Language Course

   Varatharaj, A.; Botelho, A. F.; Lu, X.; Heffernan, N. T. (January 2019, Proceedings of The Twelfth International Conference on Educational Data Mining)

   We present and evaluate a machine learning based system that automatically grades audios of students speaking a foreign language. The use of automated systems to aid the assessment of student performance holds great promise in augmenting the teacher’s ability to provide meaningful feedback and instruction to students. Teachers spend a significant amount of time grading student work and the use of these tools can save teachers a significant amount of time on their grading. This additional time could be used to give personalized attention to each student. Significant prior research has focused on the grading of closed-form problems, open-ended essays and textual content. However, little research has focused on audio content that is much more prevalent in language study education. In this paper, we explore the development of automated assessment tools for audio responses in a college-level Chinese language-learning course. We analyze several challenges faced while working with data of this type as well as the generation and extraction of features for the purpose of building machine learning models to aid in the assessment of student language learning. 

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4. Hao Fayin: Developing Automated Audio Assessment Tools for a Chinese Language Course

   Varatharaj, A.; Botelho, A. F.; Lu, X.; Heffernan, N. T. (July 2019, The Twelfth International Conference on Educational Data Mining)

   We present and evaluate a machine learning based system that automatically grades audios of students speaking a foreign language. The use of automated systems to aid the assessment of student performance holds great promise in augmenting the teacher’s ability to provide meaningful feedback and instruction to students. Teachers spend a significant amount of time grading student work and the use of these tools can save teachers a significant amount of time on their grading. This additional time could be used to give personalized attention to each student. Significant prior research has focused on the grading of closed-form problems, open-ended essays and textual content. However, little research has focused on audio content that is much more prevalent in the language-study education. In this paper, we explore the development of automated assessment tools for audio responses in a college-level Chinese language-learning course. We analyze several challenges faced while working with data of this type as well as the generation and extraction of features for the purpose of building machine learning models to aid in the assessment of student language learning. 

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5. Exploring teachers’ design and enactment of rigorous lessons through a collaborative design experience

   Coker, R.; Akçil-Okan, Ö.; Rhemer, D.; Morandi, S.; Schellinger, J.; Tekkumru-Kisa, M.; Southerland, S. A. (January 2023, National Association for Research in Science Teaching Annual Meeting 2023)

   Reform efforts targeting science instruction emphasize that students should develop scientific proficiency that empowers them to collaboratively negotiate science ideas as they develop meaningful understandings about science phenomena through science practices. The lessons teachers design and enact play a critical role in engaging students in rigorous science learning. Collaborative design, in which teachers work together to design, enact, and reflect on their teaching, holds potential to support teachers’ learning, but scarce research examines the pathways by which collaborative design can influence teachers’ instructional practices. Examining the teaching and reflective thinking of two science teachers who engaged in collaborative design activities over two years, we found that their enactment practices became more supportive of students’ rigorous learning over time, and that they perceived collaborative efforts with teacher educators and partner teachers to plan lessons and analyze videos of instruction as supportive of their learning to enact rigorous instruction. 

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