Research Interests

Broadly speaking, I am interested in understanding aspects of human reasoning, information processing, decision making, and metacognition. More specific interests include:

  • detection and resolution of contradictions between multiple representations

  • integration of multiple representations and multiple documents

  • self-regulated learning

  • science text comprehension

  • neurodivergent experiences

  • construction of literary interpretations

  • engagement in authentic literary reasoning

Research Mentoring

Mentoring student research projects is one of my favorite things to do. Many of the students I have mentored over the last few years are featured on our SCCAM lab page. I consider student interests and passions to be critical drivers of their work so I strive to tailor each experience to the individual student. I hope this approach helps students see research as a creative and enjoyable way to explore the questions that matter most to them.

I have had the pleasure of working on individual research projects with many students at the following levels:

  • Undergraduate students (independent & collaborative projects)

  • Honors undergraduate students (theses & independent projects)

  • Master's students (theses & independent projects)

  • PsyD students (dissertations)

Research Experience & Training

Study of Cognition, Contradictions, and Misconceptions (SCCAM) Research Lab

Lab Founder and Faculty Director; 2023-present; University of Indianapolis, Department of Psychological Sciences

The Study of Cognition, Contradictions, and Misconceptions (SCCAM) Lab is a (cognitively focused) psychology research lab. Broadly speaking, we explore how people process, represent, and act on complex information across textual and multi-media materials. Projects span diverse topics that focus on mechanisms of memory, reasoning and decision making, often examining how contradictions and processed or misunderstandings emerge. Several studies investigate how the presentation format of materials influence perception and decision-making, particularly when information is ambiguous or misleading. The lab also engages in applied research on classroom experiences, ADHD-related cognitive load, and accommodations in higher education.

Learning Sciences Research Institute

Graduate Research Assistant, 2011-2020; University of Illinois Chicago; Advisor: Susan Goldman, Ph.D.

Project: Reading for Understanding Across Grades 6 through 12: Evidence-based Argumentation for Disciplinary Learning (Project READi): Collaborative project with Northern Illinois University, Northwestern University, WestEd and Inquirium, LLC

  • Description: Project READi was a 5-year study trying to improve students’ abilities to create arguments from multiple text sources in the content areas of history, science, and literature.

  • Primary Tasks: coding student essays for argumentation and literary reasoning, running experiments in the classroom, conducting think-alouds and focused interviews with students grade 6-12, coding think-alouds and text annotations for evidence of processing types and discipline specific processing indicators (e.g., scientific reading practices, literary interpretations and notice of literary device)

Institute for Intelligent Systems

Research Assistant; 2009-2011; University of Memphis, Advisor: Arthur Graesser, Ph.D.

Project: Operation ARIES! (Acquiring Research Investigative and Evaluative Skills): Collaborative project with Northern Illinois University, Claremont McKenna University, and University of Memphis

  • Description: ARIES is an intelligent tutoring system that teaches critical thinking skills in a game-like atmosphere.

  • Primary Tasks: coordinating the scheduling and running of participants, data organization and management, usability testing, writing/revising pedagogical agent scripts, testing and revising Regular Expressions

Project: Auto Mentor: Collaborative project with University of Wisconsin, University of Maryland, University of Memphis, and Mass Audubon Society

  • Description: Auto Mentor is an intelligent tutoring system designed to automate professional mentoring in epistemic games for STEM learning.

  • Primary Tasks: co-site manager, Coh-Metrix and LIWC analyses on chat logs, coding for SKIVE epistemic elements (i.e., Skills, Knowledge, Identity, Values, Epistemology) and evidence of personality traits

Cognition and Technology Lab

Research Assistant, 2008-2010; University of Memphis; Advisor: Roger Azevedo, Ph.D.

Project: Meta Tutor (NSF REESE Grant)

  • Description: Meta Tutor is a multi-agent, hypermedia-based intelligent tutoring system that scaffolds self-regulated learning processes during learning about complex science topics.

  • Primary Tasks: coordinating and running studies with complex experimental set-up, concurrent think-aloud protocols, log-file data, eye-tracking, and facial recognition for affect classification, transcription of experimental sessions, data organization and management, and creating data visualizations, coding for self-regulated learning indicators