Designing AI-powered learning: adult learners’ expectations for curriculum and human-AI interaction

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.

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Publication Details

Journal
Educational Technology Research and Development
Published
2025-09-26
DOI
https://doi.org/10.1007/s11423-025-10549-z
Citations
4
Primary Topic
Educational Games and Gamification
Type
article
Field-Weighted Citation Impact
13.78
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article

Designing AI-powered learning: adult learners’ expectations for curriculum and human-AI interaction

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4 citations
Educational Technology Research and Development
Educational Games and Gamification
13.78
article

Designing AI-powered learning: adult learners’ expectations for curriculum and human-AI interaction

Xi Yu Lin, Na Li, Jinhee Kim, Seongryeong Yu, Rita Detrick
article en
4 citations

Abstract

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.

Educational Technology Research and DevelopmentVol. 73(6)
East Carolina University (US), Xi’an Jiaotong-Liverpool University (CN), Old Dominion University (US)
Openalex Percentile: Top 1%
Educational Games and Gamification
13.78
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