Date of Award


Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Applied Cognitive Science and Human Factors (PhD)

Administrative Home Department

Department of Cognitive and Learning Sciences

Advisor 1

Edward T. Cokely

Advisor 2

Rocio Garcia-Retamero

Committee Member 1

Scott Kuhl

Committee Member 2

Robert Pastel

Committee Member 3

Kelly Steelman


Simple graphical visual aids have now been shown to be among the most effective means of quickly improving people’s ability to evaluate and understand risks (i.e., risk literacy), particularly for diverse and vulnerable groups (e.g., older adults, less educated, less numerate, minority and immigrant samples). Although well-developed theory and standards for user-friendly graph design exist, guidelines are often violated by designers faced with constraints like conflicts of interest (e.g., persuasion and marketing vs. informed decision making). Even when information is presented in well-designed graphs, many people struggle with appropriate data interpretation. Can basic computerized graph literacy training improve essential graph and risk evaluation skills? To begin to answer this question, I conducted three studies that developed and validated psychometric tests of three component graph literacy skills, namely (1) graph type knowledge, (2) selecting appropriate graphs, and (3) knowledge of graph distortions. I then developed a computerized graph literacy training platform and conducted a mixed-factorial experiment investigating a wide-range of training effects. Results indicate that even in a sample of tech savvy college students one hour of basic computerized training can dramatically improve graph literacy (Cohen’s d = 1.10). Results also provide some of the first evidence that graph literacy training can improve general decision making skills that involve spatial or visualization-relevant processing, such as resistance to sunk costs, framing effects, and class-inclusion illusions. Discussion focuses on practical and theoretical implications, including usability modeling that should inform continuing development of the Decision Making Skills Training Program.