Welcome! Please read the application requirements, criteria, and project descriptions completely before applying. Once you know which project you would like to apply for (and it's ok if it's more than one), please fill out our application here.
Summer 2019 Internship Applications
This is an unpaid internship from Monday, June 3rd 2019-Friday, July 26th 2019. Interns will be expected to work roughly 30 hours per week. UC Berkeley students are encouraged to apply. Research interns will work with graduate students on multiple ongoing research projects and with the lab manager on administrative tasks. Interns will be responsible for coding data, recruiting and testing child and/or adult participants, and reading and discussing relevant theoretical and empirical papers. There will be weekly reading groups and lab meetings. Research interns should be comfortable working independently and managing their time effectively.
Application Requirements and Criteria
Accepting applications Now - Friday, March 29, 2019.
Please only apply if you are willing to make a commitment to work in our lab:
* 30 hours per week for 2 months
For UC Berkeley Undergraduate Students: *Check back in the fall if you want to apply for URAP credit. *UC Berkeley students are encouraged to apply for 2019 summer internship. Volunteers: *This is not a paid position. *Must be self-motivated and able to commit the same amount of hours as UC Berkeley undergraduate students. *Must be attending another school OR have a bachelors degree.
All research in the Gopnik Cognitive Development and Learning Lab is broadly focused on children's development of cause and effect reasoning and how they learn from and about other people. We are looking for dedicated and motivated undergraduate students interested in pursuing a graduate degree in developmental psychology or a related field. RAs will work closely with a graduate student assisting them on all aspects of the research process. RAs will help with experimental and stimuli design; recruiting participants 3 - 14 years old and adults; and collecting, organizing, coding, and analyzing data. RAs will meet regularly with their mentors to discuss the theoretical motivations of the studies they are working on as well as the findings of other empirical papers both related to the studies in the lab and important to the field in general.
What We Are Looking For in an Applicant
* Must be excited about Cognitive Development research
* Organized, self-motivated, independent, and hard working
* Prior experience with children (both formal and informal experience is great)
* Comfort acting silly around children (a bit of acting or improv experience is helpful but not essential)
* Prior research experience is not required (though it is a plus)
* Artistic, mechanical, electrical engineering or programming experience is not necessary, but would be great!
Please do not contact us about your application. If you are selected for an interview, you will receive an email.
Cognitive Development Research on Causal Reasoning, Relational Understanding, Imitation, and Imaginative Play
The first project is part of ongoing research on how children learn cause and effect relationships from observing others actions. How do they decide which actions lead to which outcomes? How do they decide which of those actions to imitate in order to bring about an effect?
The second project investigates how children use different types of evidence to form theories about causal relationships. How do children build theories about the world around them and what evidence causes them to revise these theories? How do children simultaneously form theories that explain the relationships between concepts and the concepts that make up those theories?
Supervisor: Katie Kimura, Graduate Student
Cognitive Development and Artificial Intelligence
Artificial intelligence and machine learning are entering a new era where they are all being based on famous child dev. experiments. We will be working with faculty/students over in BAIR (Berkeley Artificial Intelligence Research) on:
1. Designing maze like games for kids to play on the computer that allow us to test the curiosity and exploration limits of children and AI! See here for more info: https://pathak22.github.io/noreward-rl/
2. Working with faculty at MIT and NYU and furthering work done here: (https://web.mit.edu/cocosci/Papers/Science-2015-Lake-1332-8.pdf). We are curious to see how machine learning can inform us about children's abilities to learn how to write and recognize letters.
Supervisor: Eliza Kosoy, Graduate Student
Exploratory Decision-Making Across Development
Project Description: Conventional wisdom holds that children are “more curious” than adults. However, we know very little about how children decide to explore the world around them. This project is part of ongoing research on how children reason about potential information when making the decision to explore. Are children sensitive to different qualities of the potential information to be gained (e.g., how easy it is to learn, how useful it is, how likely it is to lead to reward), and how does this change their exploration? How does this exploratory decision- making change across development?
Supervisor: Emily Liquin, Graduate Student
In this study we are interested in understanding how children's knowledge of gender stereotypes influences their explanations for another person's behavior. In one task your child will sort various activities into bins based on gender. In a second task, they will be presented with different scenarios in which male and female dolls play on some toys and avoid other toys and the child will be asked to explain the dolls' behaviors.
Supervisor: Shaun O'Grady, Graduate Student
This study looks at preschoolers' understanding of metaphors in causal contexts. Previous research shows that preschoolers have a tricky time understanding metaphors (i.e. “a cloud is a sponge”; “her perfume was bright sunshine”) because they prefer literal language and struggle to think about deeper conceptual relations between objects. However, recent research from the Gopnik lab also shows that framing objects in a causal context facilitates relational reasoning in preschoolers. Thus, in the current study, we explore whether a causal context can also facilitate metaphor comprehension in young children. Children play an interactive computer game in which they predict what an object will turn into, and then make judgments about whether metaphors and nonsense statements are smart or silly.
Supervisor: Rebecca Zhu, Graduate Student
Understanding of Metaphors in Causal Contexts
Is there a relationship between hypothetical reasoning and pretend play in preschool aged children? The virtual universality of pretend play among children suggests it is important for development. Perhaps pretend play could be helping develop children’s ability to reason counterfactually, a skill which is important in planning and decision making. In this game, children are introduced to a stuffed animal monkey and must figure out how to turn on a machine that plays Happy Birthday music to surprise the monkey. Children are asked counterfactual questions about how to turn on the machine and later they use a pretend machine instead of the real one to imagine they are surprising the monkey. Based on previous research, children who are able to answer the counterfactual questions correctly will also be able to more easily imagine using the pretend machine instead of the real one, suggesting that there is a relationship between the two types of thought. We now extend this research to different populations of children, including cross-cultural and cross-SES samples.
Supervisor: Teresa Garcia, Lab Manager