Hannah Andrews

ORCID: 0000-0003-1091-5645
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About
Contact & Profiles
Research Areas
  • Early Childhood Education and Development
  • Cognitive and developmental aspects of mathematical skills
  • Cognitive Science and Mapping
  • Innovative Human-Technology Interaction
  • Child Development and Digital Technology
  • Cognitive Abilities and Testing
  • Synthesis and properties of polymers
  • Impact of Technology on Adolescents

University of Oxford
2024-2025

Abstract Executive functions (EF) are crucial to regulating learning and predictors of emerging mathematics. However, interventions that leverage EF improve mathematics remain poorly understood. 193 four-year-olds (mean age = 3 years; 11 months pre-intervention; 111 female, 69% White) were assessed 5 apart, with 103 children randomised an integrated intervention. Our pre-registered hypotheses proposed the intervention would more than practice as usual. Multi-level modelling network analyses...

10.1038/s41539-025-00302-9 article EN cc-by npj Science of Learning 2025-02-18

Digital self-control tools (DSCTs) help people control their time and attention on digital devices, using interventions like distraction blocking or usage tracking. Most studies of DSCTs' effectiveness have focused whether a single intervention reduces spent device. In reality, may require combinations DSCTs to achieve more subjective goals across multiple devices. We studied how can address individual needs university students (n = 280), workshop where reflect before exploring relevant...

10.1145/3613904.3642946 article EN cc-by-nc 2024-05-11

<title>Abstract</title> Executive functions (EF) are crucial to regulating learning and predictors of emerging mathematics. However, interventions that integrate improve mathematics remain poorly understood. 193 four-year-olds (mean age = 3 years:11 months pre-intervention; 111 female, 69% White) were assessed 5 apart, with 103 children randomized an integrated EF intervention. We hypothesized the intervention would scores more than practice-as-usual. Multi-level modelling network analyses...

10.21203/rs.3.rs-4486431/v1 preprint EN Research Square (Research Square) 2024-06-27
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