LETR Lab
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LETR Lab

Research

We explore the processes underlying learning across contexts and for all learners โ€” examining individual differences in cognition, language, and motivation.

Current Focus

New Projects

Two new projects launching in the coming year bring eye-tracking and multimodal AI into the lab's research program.

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Patricia Miller Fund
Profiling Readers with Eye Tracking

Readers differ meaningfully in the cognitive, motivational, and knowledge-based resources they bring to a text โ€” yet prior research on reader profiles has relied almost entirely on self-report and performance measures, leaving eye movement data largely absent. This project integrates gaze behavior into a person-centered investigation of reading comprehension, comparing neurotypical readers and readers on the autism spectrum. Using the Microsoft HoloLens with VeYezer Graph eye tracking software, participants can move freely during reading โ€” overcoming a key limitation of traditional static trackers that are especially burdensome for individuals with ASD. The study examines fixations, regressions, span of recognition, and fixation duration alongside background knowledge, prior interest, and engagement, asking whether existing reader profiles hold, require refinement, or differ across populations.

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Ken Fong Translational Research Award
Vision[AI]ry: Emotion & Attention Analytics for Education

Students' emotional states directly shape learning โ€” yet instructors in online environments lack the moment-to-moment visibility needed to detect confusion, frustration, or disengagement. In collaboration with Dr. Sanchita Ghose (Computer Engineering, AI-LAMP Lab), this project develops Vision[AI]ry, a multimodal platform that fuses facial expression analysis, vocal emotion recognition, and gaze-based attention tracking into real-time engagement scores. The system integrates three components โ€” facial landmark detection via CNN, audio Mel-spectrogram analysis, and posture-based attention tracking โ€” through a novel multimodal fusion algorithm deployed on edge computing hardware with low latency. The psychological component focuses on validating Vision[AI]ry against established self-report measures of learning-relevant affect (confusion, frustration, boredom, engaged concentration), with classroom deployment planned in online psychology and engineering courses. The platform will be released as open-source software for educational institutions.


Ongoing Work

Other Research Areas

Alongside the new projects, the lab continues work in three areas developed over the past several years.

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Reading Across Mediums

Does reading format โ€” print, digital screen, or audio โ€” shape what readers take away from a text? This line of work examines comprehension, engagement, and metacognition across formats, with completed studies on audiobook vs. print comprehension and multiple digital source use.

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Knowledge, Beliefs & Reasoning

How and why do people revise โ€” or resist revising โ€” their beliefs about controversial scientific topics? This work investigates knowledge updating, argumentative writing, and the interplay between evidence, emotion, and prior beliefs, using Bayesian network modeling and qualitative methods.

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Mental Health in Academia

Funded by an American Psychological Foundation (APF) Grant, this project examines the mental health and well-being of early career academics, investigating systemic, relational, and individual factors that shape stress, belonging, and career sustainability.


Methods

How We Work

We use a range of quantitative and qualitative methods depending on the question.

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Quantitative Methods

Survey methods, experimental designs, psychometric modeling, Bayesian network analysis, and statistical approaches appropriate to the research question.

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Qualitative Methods

Think-aloud protocols, interviews, and discourse analysis to examine the processes underlying learning, argumentation, and belief revision.

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Mixed Methods

Many projects combine quantitative and qualitative approaches to capture both the breadth and depth of learning phenomena.


Join the Lab

Working with Students

I'm always excited to work with students who are genuinely curious about the world and eager to ask meaningful questions. More than prior experience, I value intellectual curiosity, intrinsic motivation, and a willingness to engage with complex, open-ended problems where the answers are not immediately obvious.

Research often begins with big ideas. But meaningful progress comes from carefully breaking those ideas into questions that can be studied systematically. I'm looking for students who enjoy thinking deeply, discussing ideas, and are equally willing to put in the sustained effort required to design studies, analyze data, and refine their thinking. If you enjoy learning, embrace ambiguity, and are excited by the challenge of turning difficult questions into rigorous research, I'd love to hear from you.


Interested in Collaborating?

We welcome inquiries from researchers, practitioners, and students interested in our work.

asingh56@sfsu.edu
View Publications โ†’

ยฉ 2025 LETR Lab ยท Department of Psychology, San Francisco State University

 

asingh56@sfsu.edu