Angela L. Duckworth’s research while affiliated with University of Pennsylvania and other places

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Publications (93)


Open-mindedness predicts racial, political, and socioeconomic diversity of real-world friendship networks
  • Article

April 2025

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5 Reads

Group Processes & Intergroup Relations

Yeji Park

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Angela L. Duckworth

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Even in environments offering ample opportunities to interact with people from diverse backgrounds, people differ in their tendency to form intergroup friendships. Whereas some develop intergroup friendships, others prefer befriending ingroup members, contributing to prejudice and polarization. We identify open-mindedness—an inclination to engage with and understand different perspectives—as an individual difference predicting the racial, political, and socioeconomic diversity of real-world friendship networks. In a longitudinal study of 1,423 eighth–ninth graders, more open-minded adolescents developed more racially diverse friendship networks over 2 years. Two additional studies (total N = 1,585 adults) replicated and extended this finding: Open-mindedness predicted greater racial, political, and socioeconomic diversity of friends, and was more consistently associated with friendship diversity than Big Five openness to experience. The associations between open-mindedness and friendship diversity were partly explained by open-minded individuals’ lower avoidance of interaction with outgroup members. Building open-mindedness may be one individual-level approach to promote friendships across divides.


Keeping It Together: Hourly Dynamics of Children’s Behavioral Regulation at School in a Decades-Long Cohort Study

March 2025

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8 Reads

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Elizabeth T. Gershoff

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[...]

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Allyson Mackey

Though theoretical accounts describe self-regulation as dynamic, empirical studies typically rely on static measures that fail to capture changes in self-regulation from day to day or moment to moment. As a result, little is known about how or why children’s self-regulation may vary within-person, despite clear relevance for educators. In this paper, we capitalized on repeated observations from wearable devices to test the idea that daily increases in activity (DIA) across the school day could reflect a school-age child’s inability to regulate their physical activity to be appropriate to the school setting. In a national sample followed from birth to age 26 (N = 747; 49% female, 76% White, 13% Black, 6% Hispanic, 5% Other), children showing greater DIA in third grade, objectively measured using actigraphy at school and charted across hourly intervals, were rated as more impulsive and disruptive by teachers and classroom observers, had lower academic achievement in high school (β = -0.11), and completed fewer years of education as adults (β = -0.05). These findings reveal a temporal dimension to children’s behavioral regulation at school. Findings suggest that children’s behavioral regulation, proxied by the ability to inhibit motor activity, deteriorates across the school day and that children who can sustain behavioral regulation for longer go on to greater educational success long-term. Findings also reveal temporal patterns of behavior in third grade that motivate future investigations into daily experiences that could restore children’s behavioral regulation.


A national megastudy shows that email nudges to elementary school teachers boost student math achievement, particularly when personalized

March 2025

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52 Reads

Proceedings of the National Academy of Sciences

In response to the alarming recent decline in US math achievement, we conducted a national megastudy in which 140,461 elementary school teachers who collectively taught 2,992,027 students were randomly assigned to receive a variety of behaviorally informed email nudges aimed at improving students’ progress in math. Specifically, we partnered with the nonprofit educational platform Zearn Math to compare the impact of 15 different interventions with a reminder-only megastudy control condition. All 16 conditions entailed weekly emails delivered to teachers over 4-wk in the fall of 2021. The best-performing intervention, which encouraged teachers to log into Zearn Math for an updated report on how their students were doing that week, produced a 5.06% increase in students’ math progress (3.30% after accounting for the winner’s curse). In exploratory analyses, teachers who received any behaviorally informed email nudge (vs. a reminder-only megastudy control) saw their students’ math progress boosted by an average of 1.89% during the 4-wk intervention period; emails referencing personalized data (i.e., classroom-specific statistics) outperformed emails that did not by 2.26%. While small in size, these intervention effects were consistent across school socioeconomic status and school type (public, private, etc.) and, further, persisted in the 8-wk post-intervention period. Collectively, these findings underscore both how difficult it is to change behavior and the need for large-scale, rigorous, empirical research of the sort undertaken in this megastudy.


Fig. S1. Interrater correlations and correlations between AI and human ratings.
Fig. S2. Correlations between the relative likelihood of interview and AI-generated writing quality scores.
Fig. S3. Feedback prompt
Fig. S4. Participants who had practiced with the AI tool outperformed those who had practiced without it and those who had not practiced at all. Error bars represent means ± 1 SE. (N = 2,238).
Fig. S5. Levenshtein distance (number of additions, modifications or deletions) between the original text and the text passed along to the AI tool (Input); and between the AI's output text and what users submitted as their final work (Output).

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Learning from examples: AI assistance can enhance rather than hinder skill development
  • Preprint
  • File available

February 2025

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81 Reads

It is widely believed that outsourcing cognitive work to AI boosts immediate productivity at the expense of long-term human capital development. An opposing possibility is that AI tools can support skill development by providing just-in-time, high-quality, personalized examples. This work explores whether using an AI writing tool undermines or supports performance on later unaided writing. In Study 1, forecasters predicted that practicing writing cover letters with an AI tool would impair learning compared to practicing alone. However, in Study 2, participants randomly assigned to practice writing with AI improved more on a subsequent writing test than those assigned to practice without AI (d = 0.40***) -- despite exerting less effort, whether measured by time on task, keystrokes, or subjective ratings. In Study 3, participants who had practiced writing with AI again outperformed those who practiced without AI (d = 0.31***). Consistent with the positive impact of exposure to high-quality examples, these participants performed just as well as those who viewed -- but could not edit -- an AI-generated cover letter (d = 0.03, ns). In both Studies 2 and 3, the benefits of practicing with AI persisted in a one-day follow-up writing test. Collectively, these findings constitute an existence proof that, contrary to participants' intuition, using AI tools can improve, rather than undermine, learning.

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Effect Size Magnification: No Variable Is as Important as the One You’re Thinking About—While You’re Thinking About It

October 2024

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20 Reads

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5 Citations

Current Directions in Psychological Science

The goal of psychological science is to discover truths about human nature, and the typical form of empirical insights is a simple statement of the form x relates to y. We suggest that such “one-liners” imply much larger x- y relationships than those we typically study. Given the multitude of factors that compete and interact to influence any human outcome, small effect sizes should not surprise us. And yet they do—as evidenced by the persistent and systematic underpowering of research studies in psychological science. We suggest an explanation. Effect size magnification is the tendency to exaggerate the importance of the variable under investigation because of the momentary neglect of others. Although problematic, this attentional focus serves a purpose akin to that of the eye’s fovea. We see a particular x-y relationship with greater acuity when it is the center of our attention. Debiasing remedies are not straightforward, but we recommend (a) recalibrating expectations about the effect sizes we study, (b) proactively exploring moderators and boundary conditions, and (c) periodically toggling our focus from the x variable we happen to study to the non- x variables we do not.


People judge others more harshly after talking to bots

September 2024

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44 Reads

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3 Citations

PNAS Nexus

People now commonly interact with Artificial Intelligence (AI) agents. How do these interactions shape how humans perceive each other? In two pre-registered studies (total N = 1,261), we show that people evaluate other humans more harshly after interacting with an AI (compared with an unrelated purported human). In Study 1, participants who worked on a creative task with AIs (versus purported humans) subsequently rated another purported human’s work more negatively. Study 2 replicated this effect and demonstrated that the results hold even when participants believed their evaluation would not be shared with the purported human. Exploratory analyses of participants’ conversations show that prior to their human evaluations they were more demanding, more instrumental and displayed less positive affect towards AIs (versus purported humans). These findings point to a potentially worrisome side effect of the exponential rise in human-AI interactions.



Keeping It Together: Hourly Dynamics of Children’s Behavioral Regulation at School in a Decades-Long Cohort Study

July 2024

Though theoretical accounts describe self-regulation as dynamic, empirical studies typically rely on static measures that fail to capture changes in self-regulation from day to day or moment to moment. As a result, little is known about how or why children’s self-regulation may vary within-person, despite clear relevance for educators. In this paper, we capitalized on repeated observations from wearable devices to test the idea that daily increases in activity (DIA) across the school day could reflect a school-age child’s inability to regulate their physical activity to be appropriate to the school setting. In a national sample followed from birth to age 26 (N = 747; 49% female, 76% White, 13% Black, 6% Hispanic, 5% Other), children showing greater DIA in third grade, objectively measured using actigraphy at school and charted across hourly intervals, were rated as more impulsive and disruptive by teachers and classroom observers, had lower academic achievement in high school (β = -0.11), and completed fewer years of education as adults (β = -0.05). These findings reveal a temporal dimension to children’s behavioral regulation at school. Findings suggest that children’s behavioral regulation, proxied by the ability to inhibit motor activity, deteriorates across the school day and that children who can sustain behavioral regulation for longer go on to greater educational success long-term. Findings also reveal temporal patterns of behavior in third grade that motivate future investigations into daily experiences that could restore children’s behavioral regulation.


Citations (73)


... Our high-powered and preregistered field study suggests that certain nudges indeed appear to work as intended, even in "noisy" real-world settings, but that their impact might be materially smaller than what has been previously assumed and admittedly smaller than what we originally anticipated. Indeed, our mean and median differences between the tongs and spoon conditions correspond to a 3.1 % or 14 g (mean) and 4.5 % or 20 g (median) reduction in the amount of food purchased per meal, or a modest effect size of d = 0.09, making the current research much closer to the estimates from the nudging units, as reported in DellaVigna and Linos (2022), and other recent estimates (Maier et al., 2022;Szaszi et al., 2022; see also Gandhi, Manning, & Duckworth, 2024). ...

Reference:

Trying Tongs and Spoiling Spoons: Effort Nudges Influence Food Consumption and May Motivate Healthier Food Decisions
Effect Size Magnification: No Variable Is as Important as the One You’re Thinking About—While You’re Thinking About It
  • Citing Article
  • October 2024

Current Directions in Psychological Science

... Existing research has focused on the productivity effects of GPT chatbots (Noy and Zhang, 2023;Dell'Acqua et al., 2023). Separately, others investigate how AI changes people's perceptions, beliefs, and behaviors (Tey et al., 2024;Costello et al., 2024). ...

People judge others more harshly after talking to bots
  • Citing Article
  • September 2024

PNAS Nexus

... Surprisingly little research has examined the exact relationship between trait and state self-control in previous years [14]. Napolitano and colleagues now present a process model of self-control that aims to reconcile different understandings of how state self-control and trait selfcontrol are associated [15]. They do so by examining how trait self-control may inform the employment of different self-control strategies at different stages of an unfolding self-control conflict. ...

Trait Self-Control: A Process Model Perspective
  • Citing Article
  • August 2024

Current Opinion in Psychology

... Enablers for increasing vaccine uptake include utilizing reminder/recall systems with persuasive health communication [54][55][56], establishing standing orders for both inpatient and ambulatory settings [57,58], improving access (e.g., organizing workplace vaccination clinics [59], establishing ad hoc vaccination outreach services [60], and empowering pharmacists to vaccinate patients [61]), and providing incentives [62]. It is nonetheless important that reward systems are designed in a way that does not unfairly favor late adopters of vaccination [63]. ...

Megastudy shows that reminders boost vaccination but adding free rides does not

Nature

... According to Duckworth (2024), grit is defined as the tenacity and perseverance that individuals or teams demonstrate in the relentless pursuit of their goals to measure one's commitment and determination toward a cause. The respondents' grit levels, as measured by the 8-item Grit Scale, were high, addressing the first research question effectively. ...

Commentary on Personal Perspectives on Mindsets, Motivation, and Psychology by Carol S. Dweck

Motivation Science

... Likewise, when AI is used to make important decisions, such as in personnel evaluation and student admissions or assessments, fairness is crucial. Acknowledging its definitional plurality [47], it is essential to verify that these systems do not inadvertently favor or disadvantage any group due to biased data or algorithms [48]. In practice, AI systems might deliver differential benefits for different groups, so equal outcomes may not be possible, and selective deployments might be more practical [49]. ...

Using artificial intelligence to assess personal qualities in college admissions
  • Citing Article
  • October 2023

Science Advances

... Several studies have shown parental involvement to have an influence on the math performance of students, but the conclusions researchers have reached regarding whether this effect is positive or negative are inconsistent (Silinskas and Kikas, 2019;Panaoura, 2021). Some researchers have stated that parental involvement positively influences the math performance of students (Enih, 2018;Moon, 2020;Koepp et al., 2022), while others have argued that it has a negative influence (Viljaranta et al., 2018;Abu Bakar et al., 2021;Park et al., 2023). Fiskerstrand (2022) argued that it is necessary to conduct a meta-analysis on the influence of parental involvement on students' math performance. ...

Parental Intrusive Homework Support and Math Achievement: Does the Child’s Mindset Matter?

Developmental Psychology

... Collaborating with behavioral scientists and public health experts can enhance the effectiveness of these models, ensuring that they address the multidimensional nature of habit formation. Additionally, machine learning can identify context variables associated with habit formation, which can inform targeted interventions to increase gym attendance, thereby optimizing the personalization and efficacy of these interventions [29]. ...

What can machine learning teach us about habit formation? Evidence from exercise and hygiene

Proceedings of the National Academy of Sciences

... In fact, text-based reminders effectively promoted initial COVID-19 vaccinations within the same population as the current sample during the early stages of vaccine distribution 26 . However, prior studies in the healthcare context have also shown that not all reminders are equally effective 16,30,31 , they may yield inconsistent findings when encouraging the same behaviour 26,32 , the size of their effects may depend on the barriers faced by the targeted audience 33,34 , and they may even have unintended negative consequences 35 . These mixed findings highlight the importance of gathering additional evidence to better understand how to design reminder interventions for improved effectiveness. to a general website that listed various locations offering the bivalent booster (the two Broad Link arms). ...

Targeting Behavioral Interventions Based on Baseline Motivation Increases Vaccine Uptake
  • Citing Preprint
  • February 2023