Date
Publisher
arXiv
As artificial intelligence becomes increasingly integrated into digital
learning environments, the personalization of learning content to reflect
learners' individual career goals offers promising potential to enhance
engagement and long-term motivation. In our study, we investigate how career
goal-based content adaptation in learning systems based on generative AI
(GenAI) influences learner engagement, satisfaction, and study efficiency. The
mixed-methods experiment involved more than 4,000 learners, with one group
receiving learning scenarios tailored to their career goals and a control
group. Quantitative results show increased session duration, higher
satisfaction ratings, and a modest reduction in study duration compared to
standard content. Qualitative analysis highlights that learners found the
personalized material motivating and practical, enabling deep cognitive
engagement and strong identification with the content. These findings
underscore the value of aligning educational content with learners' career
goals and suggest that scalable AI personalization can bridge academic
knowledge and workplace applicability.
Study at a glance
- Question: Does adapting AI-generated learning scenarios to students' individual career goals improve engagement, satisfaction, and learning efficiency?
- Setting and data: IU International University of Applied Sciences, distance learning bachelor's and master's students, winter semester 2024, 4,003 participants across six weeks.
- Method: Randomized controlled A/B field experiment and qualitative analysis of open-ended feedback (Mixed methods).
Why it matters
Traditional one-size-fits-all education often leaves learners unable to see the relevance of academic material to their future careers. Adapting content to learners' professional goals using generative AI could increase engagement and real-world knowledge transfer.
Key findings
- Learners receiving career-tailored scenarios reported slightly higher satisfaction ratings (9.02 versus 8.84 out of 10) than those receiving standard content.
- Exam scores were nearly identical between groups, but personalized learners finished their courses 7.51% faster, though this difference was not statistically significant.
- Personalized learners engaged in slightly longer sessions and more total sessions, though these engagement differences were not statistically significant.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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Study design
