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Designing AI-Powered Learning: Adult Learners' Expectations for Curriculum and Human-AI Interaction

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Title: Designing AI-Powered Learning: Adult Learners' Expectations for Curriculum and Human-AI Interaction
Language: English
Authors: Jinhee Kim, Seongryeong Yu, Rita Detrick, Xi Lin, Na Li (ORCID 0000-0003-2395-3499)
Source: Educational Technology Research and Development. 2025 73(6):3397-3421.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 25
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Tests/Questionnaires
Education Level: Adult Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Adult Learning, Student Needs, Curriculum, Student Attitudes
DOI: 10.1007/s11423-025-10549-z
ISSN: 1042-1629
1556-6501
Abstract: Despite the potential benefits offered by GenAI technologies to provide innovative solutions to address distinct challenges faced by working adult learners (ALs) in higher education and beyond, there is limited understanding of how best to structure AI-powered learning for this population while ensuring their distinct needs and perspectives are considered. Hence, this study aimed to determine what curriculum and student-AI interaction would be required by situating ALs' views. Through analyzing 48 e-portfolios and in-depth interviews with 20 ALs from diverse educational and professional backgrounds, the study found that ALs perceived content mastery and developing a lifelong habit of learning as the optimal learning goals for AI-powered learning. AI-powered learning can be facilitated through personalized mastery-based learning and collaborative performance-based tasks, in tandem with scenario-based assessment, unobtrusive gamified assessment, and competency-based assessment. Along this line, AL articulated various necessary supports to foster AL-AI interactions. While AL identified metacognition and developing diverse and high-quality questions as crucial to support AL-AI cognitive interaction, they also highlighted that building ethical AL-AI relationships is important for enhancing AL-AI socio-emotional interaction. In addition, AL perceived immersive game-based platforms and interactive interfaces could serve as effective mediums for enhancing student-AI interactions. These findings can provide a more comprehensive understanding of AI-powered adult learning and implications for the design of educational AI, as well as instructional design to improve the educational experience for ALs.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1499622
Database: ERIC
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: Despite the potential benefits offered by GenAI technologies to provide innovative solutions to address distinct challenges faced by working adult learners (ALs) in higher education and beyond, there is limited understanding of how best to structure AI-powered learning for this population while ensuring their distinct needs and perspectives are considered. Hence, this study aimed to determine what curriculum and student-AI interaction would be required by situating ALs' views. Through analyzing 48 e-portfolios and in-depth interviews with 20 ALs from diverse educational and professional backgrounds, the study found that ALs perceived content mastery and developing a lifelong habit of learning as the optimal learning goals for AI-powered learning. AI-powered learning can be facilitated through personalized mastery-based learning and collaborative performance-based tasks, in tandem with scenario-based assessment, unobtrusive gamified assessment, and competency-based assessment. Along this line, AL articulated various necessary supports to foster AL-AI interactions. While AL identified metacognition and developing diverse and high-quality questions as crucial to support AL-AI cognitive interaction, they also highlighted that building ethical AL-AI relationships is important for enhancing AL-AI socio-emotional interaction. In addition, AL perceived immersive game-based platforms and interactive interfaces could serve as effective mediums for enhancing student-AI interactions. These findings can provide a more comprehensive understanding of AI-powered adult learning and implications for the design of educational AI, as well as instructional design to improve the educational experience for ALs.
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