Research

Welcome to the Learning Analytics & Psychology in Education Lab (LAPeL)!
Our aim is to help ensure that digital technologies can be used to promote equitable outcomes for underserved populations.
Learning Analytics

We use big data generated in digital learning environments to help design, build, and evaluate technologies that support learning in various educational contexts.

Educational Data Science

Data science techniques, such as natural language processing (NLP), enable us to study various phenomena that potentially impact learning and/or learners at scale.

Visualizing Learning Data

Data driven educational insights are often communicated through visualizations. Our lab studies how visualizations can impact learning and motivation.

Refutation Texts

Keeping to our roots in psychology, we also design studies focused on refuting various misconceptions that may impact on policy, teaching, and learning.

About LAPeL

Our Team

Learn more about the members of the Learning Analytics and Psychology Lab
Stephen J. Aguilar
Stephen J. Aguilar
Assistant Professor of Education
Founder of LAPeL. Stephen’s research focuses on the design and efficacy learning analytics technologies, and how they can be used in ways that promote digital equity and educational achievement among ethnic and racial minority students.
Clare Baek
Clare Baek
Ph.D. Student
Urban Education Policy
(Educational Psychology)
Clare has worked as a mentor teacher and department chair at a STEM academy, and as an AP Computer Science reader for Educational Testing Service. At USC, she is excited to research issues related to motivation in STEM, digital technologies and students with disabilities, and bridging educational equity gaps for underserved communities.
Anamely Salgado
Anamely Salgado
Ph.D. Student
Urban Education Policy
(Educational Psychology)
Tariro Nussinov
Tariro Nussinov
Ph.D. Student
Urban Education Policy
(Educational Psychology)
Tariro’s research interests lie in social cognition and critical consciousness in terms of identity + educational development in the digital age.
Aidan Gray
Aidan Gray
Research Assistant
Aidan is a computer science undergrad interested in artificial intelligence and machine learning. He hopes to continue his time in academia as a data science researcher.

Publications

2020

Associations between learning analytics dashboard exposure and motivation and self-regulated learning. Computers & Education

When school comes home: How low-income families are adapting to distance learning.

Guidelines and tools for bridging the digital divide. Information and Learning Sciences

A research-based approach for evaluating resources for transitioning to teaching Online. Information and Learning Sciences

 Sexual harassment in academe is underreported, especially by students in the physical sciences. PLoS ONE.

2019

Survey-software implicit association tests: A methodological and empirical analysis. Behavior Research Methods.

Refutation texts: A new approach to changing public misconceptions about education policy. Educational Researcher

Hispanic students’ sense of control in relation to post-secondary enrollment outcomes. Social Sciences

2018

Examining the relationship between comparative vs. self-Focused academic data visualizations in at-risk college students’ academic motivation. Journal of Research on Technology in Education

Learning analytics: At the nexus of big data, digital innovation, and social justice in education. TechTrends, 62:37-45

Game-inspired design: Empirical evi- dence in support of gameful learning environments. Games and Culture

2015

Investigating student motivation in the context of a learning analytics intervention during a summer bridge program. Computers in Human Behavior

Read more of Dr. Aguilar's work