Effectively designed data visualizations allow viewers to use their powerful visual systems to
understand patterns in data across science, education, health, and public policy. But …

Taking advantage of the vast history of theoretical and empirical findings in the learning
literature we have inherited, this research offers a synthesis of prior findings in the domain of …

With machine learning models being increasingly used to aid decision making even in high-
stakes domains, there has been a growing interest in develo** interpretable models …

As the use of machine learning (ML) models in product development and data-driven
decision-making processes became pervasive in many domains, people's focus on building …

Many of the guidelines that inform how designers create data visualizations originate in
studies that unintentionally exclude populations that are most likely to be among the'data …

While visualizations are an effective way to represent insights about information, they rarely
stand alone. When designing a visualization, text is often added to provide additional …

Today, machine learning (ML) technologies have penetrated almost every aspect of
people's lives, yet public understandings of these technologies are often limited. This …

Slanted framing in news article titles induce bias and influence recall. While recent studies
found that viewers focus extensively on titles when reading visualizations, the impact of titles …

When an analyst or scientist has a belief about how the world works, their thinking can be
biased in favor of that belief. Therefore, one bedrock principle of science is to minimize that …

People naturally bring their prior beliefs to bear on how they interpret the new information,
yet few formal models exist for accounting for the influence of users' prior beliefs in …