Current Research Projects
Children’s STEM Learning with Conversational Technologies
This project, headed by Dr. Mark Warschauer and Dr. Ying Xu, and partnered with PBS kids, investigates the use of conversational agents to support children’s learning during interactive educational television consumption. The end goal of this project is to distribute the conversational videos as publicly accessible content via PBS KIDS platforms to millions of children across the country.
Conversational Agents as Bilingual Reading Partners
To enhance children’s home literacy environments, this project, led by Ying Xu, explores the use of conversational agents to promote language learning through interactive, bilingual English-Spanish storybook reading. Drawing on the principles of dialogic reading, Xu has developed, implemented, and evaluated fully automated smart speaker reading companions that not only narrate stories to children but also engage them in meaningful, open-ended conversations in both languages.
Patterns of Neural Engagement During Reading with AI
This project investigates the neural responses of children during interactions with both AI and human partners. The current study, led by Dr. Chi-Lin Yu of OSU, looks at how children's developing brains process social interactions with both humans and AI, focusing on the differences in neural and behavioral responses. By combining neuroimaging techniques like functional near-infrared spectroscopy (fNIRS) with naturalistic tasks such as story-listening and real-time verbal interactions, the project aims to uncover the mechanisms underlying children’s social communication in ecologically valid contexts.
Evaluating Automatic Speech Recognition for Young Bilinguals
This project investigates how automatic speech recognition recognizes bilingual speech and what factors drive potential disparities. We are especially interested in how variability in acoustic features of bilingual speech and bilingual language proficiency may influence ASR accuracy.
Educational Storytelling: The Role of Generative AI in Children's Learning
This research, led By Dr. Ying Xu, aims to explore how large language models (LLMs) and generative AI can impact children's learning. As an initial step, we have launched a study that involves using generative AI to co-create STEM-focused narratives with children. To ensure the AI-generated content is educationally enriching, we experimented with various strategies, including theory-based prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques. These methods help optimize the AI's dialogue output to better support children's educational experiences.
Past Projects:
2019-2023: Does who you are talking to affect what you remember?
For my doctoral research, I used behavioral and electrophysiological techniques to explore how speaker characteristics affect cognitive processes in attention and memory. I am primarily interested in how increases in listening effort can affect information encoding and retention. I also use EEG to study how the brain treats accent information at different levels of discourse processing.
2016-2017: Age-related changes in cognitive and sensory processing
As a full-time Research Associate on a collaborative project between the Department of Psychological Sciences and the Speech and Hearing Sciences Department at Indiana University Bloomington, I administered cognitive batteries, and auditory and visual tests to an elderly population of approximately 200 participants, collecting and analyzing longitudinal data to investigate links between sensory processing and cognition in aging adults.
2014-2017: Phonotactic repairs in L2 learners of English
For my undergraduate honors thesis, I programmed a Lexical Decision Task to study the lexical encoding of perceptual epenthetic vowels in English as a second language learner by examining whether the sound sequences permitted in one’s L1 influence the way L2 words are represented in the mental lexicon.
2013-2017: Visual perception and chronic cannabis use
As an undergraduate research assistant in Dr. Tom Busey’s Visual Perception and Electrophysiological Lab at Indiana University Bloomington, I collected EEG and eye tracking data from cannabis users as part of a multi-lab study to better understand the effects of long-term cannabis use on perceptual, structural and cognitive processes.