Evidence map›Paper›PMID 38790430›Full record

ArticleBrain sciences2024

Incorporating Evidence-Based Gamification and Machine Learning to Assess Preschool Executive Function: A Feasibility Study.

Cassondra M Eng, Aria Tsegai-Moore, Anna V Fisher

Abstract read
In one paragraph

Article in Brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Cassondra M EngDepartment of Psychiatry & Behavioral Sciences, Stanford University, 1520 Page Mill Road Stanford, Stanford, CA 94304, USA.ORCID 0000-0002-9825-8864
Aria Tsegai-MooreDepartment of Psychology, Columbia University, 406 Schermerhorn Hall, 1190 Amsterdam Avenue, New York, NY 10027, USA.
Anna V FisherDepartment of Psychology, Carnegie Mellon University, 5000 Forbes Avenue, 335I Baker Hall, Pittsburgh, PA 15213, USA.

Funding

TRAINING FOR CHILD PSYCHIATRY AND CHILD DEVELOPMENTT32MH019908 · NIMH · STANFORD UNIVERSITY · PI IAN H GOTLIB, DAVID S HONG · 1993 to 2026
$6.3M
Institute of Education Sciences R305B150008NIMH NIH HHS T32 MH019908NIMH NIH HHS T32MH019908
6 · The paper itself

Abstract

Computerized assessments and digital games have become more prevalent in childhood, necessitating a systematic investigation of the effects of gamified executive function assessments on performance and engagement. This study examined the feasibility of incorporating gamification and a machine learning algorithm that adapts task difficulty to individual children's performance into a traditional executive function task (i.e., Flanker Task) with children ages 3-5. The results demonstrated that performance on a gamified version of the Flanker Task was associated with performance on the traditional version of the task and standardized academic achievement outcomes. Furthermore, gamification grounded in learning science and developmental psychology theories applied to a traditional executive function measure increased children's task enjoyment while preserving psychometric properties of the Flanker Task. Overall, this feasibility study indicates that gamification and adaptive machine learning algorithms can be successfully incorporated into executive function assessments with young children to increase enjoyment and reduce data loss with developmentally appropriate and intentional practices.

Indexed as

assessmentexecutive functionflankergamificationmachine learning

Identifiers

PMID38790430
PMCPMC11119088

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.