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Visualizing Child-Adult engagement in preschool classrooms using Chord Diagrams

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Conference

2022 ASEE Gulf Southwest Annual Conference

Location

Prairie View, Texas

Publication Date

March 16, 2022

Start Date

March 16, 2022

End Date

March 18, 2022

Page Count

8

DOI

10.18260/1-2--39222

Permanent URL

https://peer.asee.org/39222

Download Count

223

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Paper Authors

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Sathvik Datla UT Dallas

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Sathvik Datla is pursuing BS degree in Software Engineering at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas (UTD), Richardson. He is an active member of the Cyber Security Club. Currently he is recipient of National Science Foundation's Research Experience in Undergraduate Education award on the Cyberlearning project, under the supervision of Dr. John H. L. Hansen. As an undergraduate researcher in Center for Robust Speech Systems, his research interests focus on Computer Science and Software Development for STEM Education.

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Prasanna Vasant Kothalkar UT Dallas

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Prasanna Kothalkar received the B.S. degree in Computer Engineering from Mumbai University, Mumbai, India in 2010, M.S. degree in Computer Science from University of Texas at Dallas, Dallas, United States, in 2014. He has interned at technology companies for research positions in the areas of Speech Processing and Machine Learning. Currently he is pursuing his Ph.D. degree as a Research Assistant in the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas (UTD), Richardson, United States under supervision of Dr. John H. L. Hansen. His research interests focus on Child Speech Pronunciation Modeling, Speech Recognition and Diarization, Machine Learning and Deep Learning.

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John H. L. Hansen University of Texas at Dallas Orcid 16x16 orcid.org/0000-0003-1382-9929

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John H.L. Hansen, received Ph.D. & M.S. degrees from Georgia Institute of Technology, and B.S.E.E. degree from Rutgers Univ. He joined Univ. of Texas at Dallas (UTDallas) in 2005, where he is Associate Dean for Research, Prof. of Electrical & Computer Engineering, and holds a joint appointment in School of Behavioral & Brain Sciences (Speech & Hearing). At UTDallas, he established Center for Robust Speech Systems (CRSS). He is an ISCA Fellow, IEEE Fellow, past TC-Chair of IEEE Signal Proc. Society, Speech & Language Proc. Tech. Comm.(SLTC), and Technical Advisor to U.S. Delegate for NATO (IST/TG-01). He currently serves as President of ISCA (Inter. Speech Comm. Assoc.). He has supervised 92 PhD/MS thesis candidates, was recipient of 2020 UT-Dallas Provost’s Award for Grad. Research Mentoring, 2005 Univ. Colorado Teacher Recognition Award, and author/co-author of +750 journal/conference papers in the field of speech/language/hearing processing & technology.

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Dwight Irvin

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Jay Buzhardt University of Kansas

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As an Associate Research Professor at the University of Kansas, Dr. Buzhardt’s research interests focus on developing and testing technology solutions to support data-driven intervention decision making in early childhood education. At Juniper Gardens Children’s Project (JGCP), he leads the Technology Innovation Development & Research (TIDR) Lab, which is a hybrid of onsite fulltime application developers and externally contracted developers, where online and mobile applications are designed, developed, tested, and maintained for nearly all JGCP interventions that utilize technology. Through grants funded through OSEP and IES and led by Dr. Buzhardt, the TIDR Lab developed and currently maintains the MOD and IGDI platform where it is hosted. Additionally, Dr. Buzhardt has led or co-led 10 federal grants from the Department of Education (5 from Office of Special Education Programs, 5 from Institute of Education Sciences) and four from the National Institute on Disability, Independent Living, and Rehabilitation Research. He currently directs a project funded by the Institute of Education Sciences to develop a web application that guides educators' data-driven intervention decision making. He also leads a $2.5M project funded by the Office of Special Education Programs to develop and test strategies and applications grounded in Implementation Science to scale-up sustained use of data-driven decision-making practices by infant-toddler service providers. He recently completed a 2nd successful RCT of the MOD across four states to test web-based decision-making support vs. self-guided decision making in Early Head Start home visiting settings. Other relevant projects include investigations of the construct and predictive validity of infant-toddler IGDI assessments, development of web-based professional development for elementary educators, and a current NSF-funded project to develop technology to automatically measure child and adult language in preschool and informal learning contexts.

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Abstract

The ability to assess conversational interactions creates a challenge in assessing speaker turns over time, including frequency of occurrence, duration of each turn, and connecting speakers in a multi-speaker context. This is of particular interest in the analysis of teacher-student or adult-child interactions in learning spaces. The creation of a visualization mechanism capable of providing a high-level representation of the overall conversational interactions without overburdening educators in reviewing student/child learning engagement would be valuable. In this study, we explore the creation of chord diagrams as a way to analyze talk time between a child and adult speakers in learning spaces. The proposed illustration is suggested to provide an opportunity to study the variations in speech duration and the interaction among speakers that are involved in the communication with each other over a certain time learning duration. The data set in this study contains a spontaneous conversational speech which was recorded with aid of the LENA device. Here we analyze conversations having engagement for one session as transcribed by the UT Dallas-CRSS transcription team. Figure 1 illustrates the proposed Chord Diagram which consists of the following three speaker categories: PC, SC, and AD/TE. Red is used to represent the adult speaker (or teacher, AD/TE), blue is used to represent the secondary child speaker (SC), and lastly green is shown to represent the primary child speaker (PC). Each arc island along the circumference represents a specific conversational exchange. The width of the arc island represents the total duration of the talk time between the related speakers. For example, in the figure it shows that the thickest arc is the highlighted one having a total duration of 49.1 seconds of engagement between the speakers. The length of the circumference of the Diagram represents the total talk time duration for considered speaker (e.g., 525 sec for PC).

Datla, S., & Kothalkar, P. V., & Hansen, J. H. L., & Irvin, D., & Buzhardt, J. (2022, March), Visualizing Child-Adult engagement in preschool classrooms using Chord Diagrams Paper presented at 2022 ASEE Gulf Southwest Annual Conference, Prairie View, Texas. 10.18260/1-2--39222

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