Xiuyuan Flora Zhang

Thinking about ownership

From a coffee mug to a line of lyric, we take ownership of many different objects and readily infer if an object is owned by others. Ownership serves as a great test case for studying human social cognition, especially since the maintenance and transfer of ownership requires coordination and mutual recognition of owners' rights. My work aims to look at how people integrate different social and perceptual cues to make ownership judgments, and pinpoint where conflicts might arise. I am further interested in people's ownership judgments beyond physical property and how the sense of ownership could license people to interact with objects differently.

How do people decide when ownership is transferred?

with Paul Bloom and Julian Jara-Ettinger in Psychological Science

[link to paper] [OSF repository]

Many objects we interact with are owned by someone, but ownership information is not always in plain sight. Intuitively, it’s important for people within a society to share intuitions about how ownership works—otherwise they wouldn’t be useful. However, disputes about ownership happen (and societies have legal systems to resolve them). What’s the source of these conflicts?

Across four experiments, we show that people's ownership judgments reflect at least two different underlying intuitive theories: one where mental state information is central while the other prioritizes physical possession. Differences in ownership judgments further predict people's acceptability of using, altering, controlling, and destroying the owned object.

Thinking about learning

Unlike the often binary nature of acquiring ownership, acquiring a new skill takes time and practice. From learning to ride a bike, play chess, to code up a computer program, humans face a lot of decisions to persist (e.g., invest more time and effort) or give up (e.g., task switch) on a given skill throughout our lifetime. Since progress during learning could be opaque, it is up to the learner (and the teacher) to motivate continued learning. I am passionate about leveraging cognitive science to enhance learners' learning experience. As a start, I look into how people represent the basic process of learning, and how their beliefs about whether and how they learn affect what they choose to learn.

How do people predict the learning curve for a new skill?

with Sam McDougle and Julia Leonard in Cognition

[link to paper] [OSF repository]

Decades of research have shown that skill learning often unfolds exponentially: People improve rapidly early on, and then performance gradually levels off. Given how important expectations of learning are for actual learning, we explore whether people accurately intuit this canonical time course of skill learning.

We show that people accurately predict the shape of learning curves for themselves and a naive player on a new task, being sensitive to both player effort and task difficulty. Meanwhile, people still misestimate specific parameters of the curve. These misestimations further fuel negative affects for people, especially at the beginning of learning.

Do young children understand that mastery takes practice?

with Brandon Carrillo, AC Christakis, and Julia Leonard in press at Child Development

[link to preprint] [OSF repository]

Learning takes time: Performance usually starts poorly and improves over repeated attempts. Do children intuit this basic phenomenon of learning? Using a novel paradigm with minimal verbal demands, we probe 4- to 8-year-old children's trial-by-trial predictions of their future performance on a new task.

We first find that 7- and 8-year-old children predicted improvement across five trials, whereas younger children predicted near-ceiling performance. We next show that 4- to 6-year-old children could predict improved performance with additional scaffolding to lower task demands and incentives to reduce over-optimism.