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ERIC Number: ED663019
Record Type: Non-Journal
Publication Date: 2024
Pages: 16
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Incorporating Evidence-Based Gamification and Machine Learning to Assess Preschool Executive Function: A Feasibility Study
Cassondra M. Eng; Aria Tsegai-Moore; Anna V. Fisher
Grantee Submission, Brain Sciences v14 Article 451 2024
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.
Publication Type: Journal Articles; Reports - Research
Education Level: Early Childhood Education; Preschool Education
Audience: N/A
Language: English
Sponsor: Institute of Education Sciences (ED); National Institutes of Health (NIH) (DHHS)
Authoring Institution: N/A
Identifiers - Location: Pennsylvania (Pittsburgh)
IES Funded: Yes
Grant or Contract Numbers: R305B150008; T32MH019908