Cited by 140Social Robot Interaction and HRIEducational Robotics and EngineeringChild and Animal Learning Development

The DOI matches its Crossref record; 34 of the 36 references it cites were found in a registry or an index.

Growing Growth Mindset with a Social Robot Peer

Open access
Park, Hae Won, Rosenberg-Kima, Rinat, Rosenberg, Maor, Gordon, Goren, Breazeal, Cynthia·2017·Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

Abstract

Mindset has been shown to have a large impact on people's academic, social, and work achievements. A growth mindset, i.e., the belief that success comes from effort and perseverance, is a better indicator of higher achievements as compared to a fixed mindset, i.e., the belief that things are set and cannot be changed. Interventions aimed at promoting a growth mindset in children range from teaching about the brain's ability to learn and change, to playing computer games that grant brain points for effort rather than success. This work explores a novel paradigm to foster a growth mindset in young children where they play a puzzle solving game with a peer-like social robot. The social robot is fully autonomous and programmed with behaviors suggestive of it having either a growth mindset or a neutral mindset as it plays puzzle games with the child. We measure the mindset of children before and after interacting with the peer-like robot, in addition to measuring their problem solving behavior when faced with a challenging puzzle. We found that children who played with a growth-mindset robot 1) self-reported having a stronger growth mindset and 2) tried harder during a challenging task, as compared to children who played with the neutral-mindset robot. These results suggest that interacting with peer-like social robot with a growth mindset can promote the same mindset in children.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/2909824.3020213

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 36 references

Research works printed but not linked: 3

  1. 10.5555/3016387.3016461 · DOI
  2. J. Jirout . 'i try to learn as much as i can' vs. 'i try to get the best grade i can': A study of children's ideas about learning and school . In Cognitive Development Society Meeting , 2015 . J. Jirout. 'i try to learn as much as i can' vs. 'i try to get the best grade i can': A study of children's ideas about learning and school. In Cognitive Development Society Meeting, 2015.
  3. 10.5555/2906831.2906979 · DOI

Cited by

Sorted by citations

Metadata

Authors
Park, H. W., Rosenberg-Kima, R., Rosenberg, M., Gordon, G., & Breazeal, C.
Affiliations
  • MIT Media Lab (US)
  • Tel Aviv University, Israel, Tel Aviv, Israel
  • Tel Aviv University (IL)
Venue
Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction
Publisher
ACM
Published
2017-03-06
Volume
2017
Pages
137-145
OpenAlex
W2594091522
Cited by
140
References
36
Citations by year
2026: 8 · 2025: 10 · 2024: 12 · 2023: 15 · 2022: 25 · 2021: 25 · 2020: 16 · 2019: 17 · 2018: 9 · 2017: 3
FWCI
19.95
Type
conference paper
Language
en
Open access
Locations
  • ACM/IEEE International Conference on Human-Robot Interaction (HRI) (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
Funders
National Institutes of Health (5R01HD086899-02)
Topics
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Social Sciences › Education › Educational Robotics and Engineering
  • Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
Keywords
growth mindset, fixed mindset, social robots, children, puzzle solving, effort, problem-solving behavior, autonomous robot behavior

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review